Hot off the presses! Aug 01 Nat Med

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• Difficult decisions
  - Nat Med 17(8):901 (2011)
  Nature Medicine | Editorial Difficult decisions Journal name:Nature MedicineVolume: 17,Page:901Year published:(2011)DOI:doi:10.1038/nm0811-901Published online04 August 2011 Conditional approval aims to speed the delivery of drugs to patients in need. But when full approval is denied, complications arise for patients, companies and regulatory agencies alike. View full text Additional data
• Exploratory grant scheme abandoned after failing to meet its goals
  - Nat Med 17(8):903 (2011)
  Article preview View full access options Nature Medicine | News Exploratory grant scheme abandoned after failing to meet its goals * Hannah WatersJournal name:Nature MedicineVolume: 17,Page:903Year published:(2011)DOI:doi:10.1038/nm0811-903Published online04 August 2011 Last year, tissue bioengineer Jeffrey Borenstein decided to pursue a long-incubating idea. He wanted to create an artificial lung that that could work for months on end without recipients having to take blood-thinning drugs like they do with existing models. None of his existing grants included funding to cover this project. And with little preliminary data to show for his fledgling idea, he figured he didn't stand much of a chance at securing an R01 grant, the most widely used funding vehicle at the US National Institutes of Health (NIH) for specific research projects. So Borenstein, director of the biomedical engineering center at the Charles Stark Draper Laboratory in Cambridge, Massachusetts, applied for an R21 grant, which provides transitionary funding for researchers with little initial data to explore high-risk, high-reward projects. The grant only provides up to $275,000 over two years, but the idea is that investigators are then in a better position to secure much more lucrative R01 funding. The US National Heart, Lung, and Blood Institute (NHLBI) funded Borenstein's grant in November to the tune of $260,000. On the basis of previous funding, he reported in April how microfluidic technologies enable high levels of gas exchange in a densely packed structure—a far more efficient method than the current bulky mechanical ventilators (Biomed. Microdevices, 315–23, 2011). With the R21 grant, he is now developing strategies for lining the microscopic vessels with endothelial cells to reduce the common problem of blood clots on artificial surfaces. "Our goal is to use this new technology platform for a host of artificial organ applications," Borenstein says. Had he waited much longer to apply, however, Borenstein might never have received the funding, because on 12 July the NHLBI announced that the institute would no longer accept unsolicited R21 grant applications after October because the funding was not serving its intended purpose. The R1 grants are meant "to get you to the point where you can apply for an R01," explains Susan Shurin, acting director of the NHLBI, headquartered in Bethesda, Maryland. But the funded ideas "weren't transitioning into independent, investigator-controlled grants," she says. Many young investigators view R21s as stepping stones to R01s. But at a 15 June NHLBI advisory council meeting, the institute's acting deputy director Carl Roth presented data showing that early-career researchers obtain R21s at half the success rate of their more senior counterparts, whereas new and experienced investigators receive R01s at a similar rate. "The R21s are interesting in that a lot of people thought, 'Oh boy, these are easy pickings,'" says Howard Garrison, deputy executive director for policy at the Federation of American Societies for Experimental Biology in Washington, DC. Their popularity stems largely from their "reputation for being easier than R01s," he notes, rather than the proof-of-principle projects they were meant to finance. Although the NHLBI will stop funding unsolicited exploratory grants, according to Shurin the institute will continue to occasionally put out calls for R21 applications for specific research projects defined by the institute—but only from established researchers with at least two R01s under their belts. Exploring all options It's not the first time that agency officials have abandoned a funding scheme. In the late 1990s, the NIH discontinued the R29 grant program—a low-budget alternative to R01s designed to give young investigators easier access to the funding system—after a working group found that R29 recipients were no more likely to secure R01s than those new researchers who never held a bridge grant. Charles Stark Draper Laboratory The R21-funded "lung". "To bring new investigators in on the cheap was a bad idea then, and it's a bad idea now," says Marvin Cassman, former director of the US National Institute of General Medical Sciences who co-chaired the working group that led to the R29 grant's demise. "Unless you give people the amount of time and amount of money they need, there's no reason you should expect them as a group to be successful." Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Author Details * Hannah Waters Search for this author in: * NPG journals * PubMed * Google Scholar
• Overstretched medical mystery program takes a breather
  - Nat Med 17(8):904 (2011)
  Nature Medicine | News Overstretched medical mystery program takes a breather * Elie DolginJournal name:Nature MedicineVolume: 17,Page:904Year published:(2011)DOI:doi:10.1038/nm0811-904Published online04 August 2011 Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg A major initiative aimed at tracking down the causes of mysterious illnesses seems to be a victim of its own success. Less than five months after the US National Institutes of Health's Undiagnosed Diseases Program published its first clinical victory, program organizers announced a temporary moratorium on new applications, effective 1 July, to give the agency time to clear its backlog of petitions. "We're inundated," says the program's director William Gahl, clinical head of the country's National Human Genome Research Institute in Bethesda, Maryland. The three-year-old, $3.5-million-a-year program has so far received more than 5,000 inquiries and about 1,900 full submissions, complete with medical records, images and, often, biopsied tissue. Of those, the program has accepted close to 500 applicants but only had time to investigate around 350 cases. The pause is an effort to catch up. "We always have to set priorities," says Gahl, "and right now we feel we should invest in the really good cases we've already seen." The vetting process is labor intensive: the staff rejects as many as eight out of every ten applications owing to a lack of clinical data upon which to launch a full study. Gahl expects to start accepting new requests again in the fall. Marsha Lanes, a genetic counselor and medical editor for the National Organization for Rare Disorders in Danbury, Connecticut, advises people with unknown medical problems to get their applications ready for when the pause ends. "I would encourage anyone who was planning to submit to sit in there," she says. "This is a really unique service and program that isn't available anywhere else." In the meantime, the NIH program's staff will continue to investigate the unsolved diseases already in the queue and will also follow up with some of the individuals who obtained clinical diagnoses through the effort. One such person is Louise Benge, 56, of Brodhead, Kentucky. Earlier this year, Gahl, together with vascular biologist Manfred Boehm from the National Heart, Lung and Blood Institute, discovered the gene responsible for a rare artery-hardening condition that afflicts Benge and her four siblings as well as individuals from two unrelated families. Reporting in the New England Journal of Medicine (, 432–442, 2011), the researchers showed that a mutation in a gene called NT5E, which regulates levels of the enzyme alkaline phosphatase, was responsible for arterial calcium deposits, leading to leg and joint pain. Breakthrough inhibition Since the paper's publication in February, Boehm says his team has tested a series of drugs previously shown to inhibit the enzyme—including bisphosphonates, protein-pump inhibitors and the deworming agent levamisole—on cultured skin cells taken from Benge and others in the study. Their unpublished in vitro data indicates that treatment with bisphosphonates such as Didronel (etidronate) and Boniva (ibandronate), both of which are commonly used to treat osteoporosis and other bone diseases, hold the most promise at preventing calcification in Benge and the other eight people in the study, Boehm says. "I was really amazed that they found out what was causing our problem as quick as they did," says Benge, "and even more amazed that they found something that they thought could help us." She explains that her only current drug option is painkillers for the extreme discomfort caused by her condition. The researchers are now preparing a clinical trial to give the affected individuals one of the drugs, although they haven't decided which one yet. They are also bringing the study subjects back to the NIH clinic to obtain additional health data about their disease progression. "We are trying to put together a baseline for these patients, so when we start the treatment we can better see the changes in one or the other direction," says Boehm, who expects the trial to begin before the end of the year. Yet despite some early research triumphs, not everyone thinks the program has achieved all that it could to increase the accuracy and timeliness of diagnosing diseases. "Now that they have their feet on the ground, they need to stand back and say, 'What more can we do?'" argues Marianne Genetti, executive director of In Need of Diagnosis, a Florida-based patient-resource organization. Genetti thinks the program could boost its impact by developing diagnostic computer software, training clinical biochemists and other diagnosticians, and creating an autopsy program—"the quality control of diagnosis," as she calls it. Jeannine Mjoseth, NHGRI Louise Benge (left). "Diagnosis is the weak link in medicine," Genetti says, "and the big picture has got to come from NIH." New legislation could strengthen that link. As Nature Medicine went to press, US lawmakers, led by Texas Representative John Carter (Republican), were slated to reintroduce a bill on 27 July that would create a national registry of undiagnosed diseases that physicians could search to cross-reference mysterious disorders with similar symptoms. A previous version of the legislation, which stalled in congressional committees two years ago, proposed to house the resource at the US Centers for Disease Control and Prevention. But, given the success of the Undiagnosed Diseases Program, the new bill, if passed, now proposes to establish the $5 million registry at the NIH as early as September 2013. "I'm hopeful that this bill will create something that will be beneficial for families," says Amy Clugston, president of the Michigan-based advocacy and support group Syndromes Without a Name USA. "Maybe this is a way to stop this type of thing from happening—where a program is started but then it has to halt or go away because of lack of funding." Additional data Author Details * Elie Dolgin Search for this author in: * NPG journals * PubMed * Google Scholar
• Abuse-resistant painkillers get mixed FDA response
  - Nat Med 17(8):905 (2011)
  Article preview View full access options Nature Medicine | News Abuse-resistant painkillers get mixed FDA response * Hannah WatersJournal name:Nature MedicineVolume: 17,Page:905Year published:(2011)DOI:doi:10.1038/nm0811-905aPublished online04 August 2011 With painkiller addiction on the rise, drugmakers have come up with clever ways to discourage such behavior. As recently as 20 June, the US Food and Drug Administration (FDA) approved a new abuse-deterrent formulation of oxycodone called Oxecta, developed by Pfizer and Acura Pharmaceuticals of Palatine, Illinois. The new pill becomes gummy when crushed, making the oxycodone harder for addicts to extract as a powder and snort for a quick, potent high. "It lends itself less well to standard practices of laypeople trying to abuse it," explains anesthesiologist Howard Smith of Albany Medical Center in upstate New York. Devising a better painkiller is big business. Doctors wrote more than 200 million prescriptions for opioid medications in the US during 2009. Meanwhile, the number of people entering substance abuse programs for opioid addiction increased fivefold between 1998 and 2008, and a July 2010 report from the US Centers for Disease Control and Prevention points to painkillers as the leading cause of fatal drug overdoses. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Author Details * Hannah Waters Search for this author in: * NPG journals * PubMed * Google Scholar
• Politicians get tough in wake of fatal pharmacy thefts
  - Nat Med 17(8):905 (2011)
  Article preview View full access options Nature Medicine | News Politicians get tough in wake of fatal pharmacy thefts * Hannah WatersJournal name:Nature MedicineVolume: 17,Page:905Year published:(2011)DOI:doi:10.1038/nm0811-905bPublished online04 August 2011 The street value of oxycodone continues to skyrocket, with individual pills selling for as much as $80, according to some law enforcers. Not surprisingly, news headlines bear out the desperate, and sometimes deadly, measures that some addicts or their drug dealers will go to for these painkillers. The pharmacy robbery in Long Island, New York on 19 June that left four people dead brought the issue to the forefront of the public's attention. But legislators had already noticed. In May, US Senator Charles Schumer, a Democrat representing New York, proposed toughening the penalties for individuals who steal, traffic and tamper with medical products, including pharmaceuticals. The Prescription Drug Abuse Prevention and Treatment Act of 2011, now in committee, would increase the prison sentences for medical cargo theft from 10 to 20 years and permit law enforcement to wiretap suspects to collect evidence. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Author Details * Hannah Waters Search for this author in: * NPG journals * PubMed * Google Scholar
• New technologies aim to take shock out of treating irregular hearts
  - Nat Med 17(8):906 (2011)
  Article preview View full access options Nature Medicine | News New technologies aim to take shock out of treating irregular hearts * Genevieve WanuchaJournal name:Nature MedicineVolume: 17,Page:906Year published:(2011)DOI:doi:10.1038/nm0811-906aPublished online04 August 2011 To rescue an abnormally beating heart, a defibrillator must deliver a whopping 1,000 volts to reset the electric charge in every cell in the organ and allow the heart to resume its rhythm. Such sizeable jolts cause pain and destroy irreplaceable cardiac tissue. Yet they are "the only effective method of salvaging someone from sudden death," according to Peng-Sheng Chen, director of the Krannert Institute of Cardiology at the Indiana University School of Medicine in Indianapolis. Researchers have long sought a painless, less damaging alternative to the standard defibrillator. In the 1980s, implantable defibrillators that provided lower-energy electrical pulses from inside the body in response to fast or disorganized heart rhythms came onto the market. Such devices were far less painful than their external predecessors, but they required invasive surgery and frequent battery changes. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Author Details * Genevieve Wanucha Search for this author in: * NPG journals * PubMed * Google Scholar
• US switch to first-to-file patents could cause minor shake-up
  - Nat Med 17(8):906-907 (2011)
  Article preview View full access options Nature Medicine | News US switch to first-to-file patents could cause minor shake-up * Hannah WatersJournal name:Nature MedicineVolume: 17,Pages:906–907Year published:(2011)DOI:doi:10.1038/nm0811-906bPublished online04 August 2011 The US is poised to become the last country in the world to give up the 'first-to-invent' patent framework. On 23 June, the country's House of Representatives joined the Senate in passing the America Invents Act, which outlines new rules for patent application and, crucially, adopts the first-to-file system used by patent regulators in all other nations. The new framework will award a patent to the first inventor to turn in his or her application, ditching the lengthy and expensive disputes over who invented a product first. At the same time, a central concern within the biomedical community is that the race to file first will produce slapdash patent applications, leaving room for mistakes that can cause headaches for all involved. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Author Details * Hannah Waters Search for this author in: * NPG journals * PubMed * Google Scholar
• Combo antibody efforts up, despite regulatory uncertainties
  - Nat Med 17(8):907 (2011)
  Article preview View full access options Nature Medicine | News Combo antibody efforts up, despite regulatory uncertainties * Roxanne KhamsiJournal name:Nature MedicineVolume: 17,Page:907Year published:(2011)DOI:doi:10.1038/nm0811-907Published online04 August 2011 Antibody therapies have traditionally consisted of drugs that can deliver a strong blow to a single target, such as a cancer cell, with great specificity. But companies have made recent investments to improve these molecules by equipping them with multipronged attacks—developing so-called 'multispecific' antibodies that have two or more simultaneous targets. "There's definitely a trend of multispecific therapies," says immunologist Gregory Adams of the Fox Chase Cancer Center in Philadelphia. And that trend has reached big pharma. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Author Details * Roxanne Khamsi Search for this author in: * NPG journals * PubMed * Google Scholar
• Shuttle's end could spell a bumpy ride for biomedicine in space
  - Nat Med 17(8):908 (2011)
  Article preview View full access options Nature Medicine | News Shuttle's end could spell a bumpy ride for biomedicine in space * Emma MarrisJournal name:Nature MedicineVolume: 17,Page:908Year published:(2011)DOI:doi:10.1038/nm0811-908aPublished online04 August 2011 NASA's Space Shuttle program is officially over. The final flight of the US National Aeronautics and Space Administration's program—a 13-day jaunt by the Shuttle Atlantis to the International Space Station (ISS) and back—touched down last month, marking the end of an era for space exploration. It also marks the end of an era for the small group of life sciences researchers whose mice, bacteria and plants have flown on the orbital spacecrafts. Without any US government–run manned spaceflights planned for the foreseeable future, those in the field of space biomedicine have fewer options for getting their research samples into orbit and back home again. But some scientists are optimistic that the recent completion of the ISS will mark the beginning of a new golden age for biology ex terra. "I don't think space biomedicine is going to go away," says Jeffrey Sutton, director of the National Space Biomedical Research Institute, a Houston-based consortium of NASA's extramural biomedical research partners. "I think it can only really go one way, and that is we need to advance." Lingering too long in the weightlessness of space can cause bones to weaken, hearts to shrink and muscles to atrophy. So, most space-based biomedical research has tested ways to keep astronauts healthy, especially over longer missions. But more basic experiments that have looked at the effects of microgravity on genes, cells and whole organisms have also flown to the final frontier. To date, though, both kinds of investigation have been largely afterthoughts—small experiments squeezed onto shuttles and conducted in a few scraps of the astronauts' spare time. Similarly, NASA officials have placed funding for life sciences research low on the priority list, particularly after former President George W. Bush asked the agency to refocus on exploration in 2004. An exciting development came in 2007 when the US National Institutes of Health (NIH) signed a memorandum of understanding with the space agency wherein projects funded by the NIH could get room in the ISS laboratories and transport from NASA (see Nat. Med.13, 1123, 2007). But according to Joan McGowan, director of the musculoskeletal diseases division at the NIH, only three awards have been given out so far, and none of them is close to flying. For the long haul NASA Vaccine research in space. Now, without NASA's taxi service, biomedical researchers will need to find new ways for their samples to reach orbit. US astronauts will continue to reach the space station aboard Russian Soyuz space capsules, but these are designed to move people, not cargo. Another option is to use commercial space cargo services, such as Space Exploration Technologies' Dragon or Orbital Sciences' Cygnus spacecrafts, both of which are running demo flights this year. However, Cygnus can only take cargo up, not down, while Dragon splashes down in the Pacific Ocean when it comes back to Earth. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Author Details * Emma Marris Search for this author in: * NPG journals * PubMed * Google Scholar
• One giant leap for biomedical research
  - Nat Med 17(8):908 (2011)
  Article preview View full access options Nature Medicine | News One giant leap for biomedical research * Emma MarrisJournal name:Nature MedicineVolume: 17,Page:908Year published:(2011)DOI:doi:10.1038/nm0811-908bPublished online04 August 2011 Getting a biomedical experiment into orbit takes years, but there's nothing like watching your organisms head for the stars. "I teared up at the launch," says Mary Bouxsein, a bone biomechanics researcher at the Beth Israel Deaconess Medical Center in Boston who led one of the research projects sent into space last month. "You are quite excited for the launch, and then you take a step back and say, 'We put mice into orbit.'" Here we describe some of the health-related studies that hitched a ride to the International Space Station and back last month aboard Shuttle Atlantis. US and Belgian researchers, in partnership with the California biotech Amgen, launched 30 mice into orbit, half of which were injected with a sclerotin-targeted antibody designed to boost bone formation. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Author Details * Emma Marris Search for this author in: * NPG journals * PubMed * Google Scholar
• Straight talk with... María Blasco
  - Nat Med 17(8):909 (2011)
  Nature Medicine | News Straight talk with... María Blasco * Elie DolginJournal name:Nature MedicineVolume: 17,Page:909Year published:(2011)DOI:doi:10.1038/nm0811-909Published online04 August 2011 Abstract Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Life hasn't been easy at the Spanish National Cancer Research Centre (CNIO) since the founding director Mariano Barbacid announced his intention to step down in 2009. Two campaigns to find a successor had to be halted—the first for lack of international candidates, and the second because nominees' names were leaked to the press. The leaks occurred amidst a high-profile dispute over Barbacid's controversial plan to use private funds to develop cancer drugs—a move that the country's Ministry of Science and Innovation said contradicted state financing rules for a public foundation. But things seem to have settled down since CNIO insider María Blasco was unanimously chosen to lead the 13-year-old center. Blasco, best known for her research on the enzymes that maintain telomeres, had directed the center's molecular oncology program since 2003, and had been vice director for basic research at the center since 2005. She became the CNIO's new director on 22 June. spoke to the new cancer capitán about her plans for the agency. View full text Additional data Author Details * Elie Dolgin Search for this author in: * NPG journals * PubMed * Google Scholar
• News in brief: Biomedical briefing
  - Nat Med 17(8):910-911 (2011)
  Article preview View full access options Nature Medicine | News News in brief: Biomedical briefing Journal name:Nature MedicineVolume: 17,Pages:910–911Year published:(2011)DOI:doi:10.1038/nm0811-910Published online04 August 2011 On 12 July, Gilead Sciences became the first pharmaceutical company to license products to the Medicines Patent Pool, an intellectual property–sharing scheme established last year by UNITAID to boost access to more affordable HIV medicines in the developing world. The deal permits generic manufacturers to produce four antiretroviral drugs, two of which are still in clinical development, as well as combinations that include these medicines. "This is very significant," says Ellen 't Hoen, executive director of the Geneva-based Medicines Patent Pool. "The fact that the negotiations with Gilead have led to an agreement will help bring other companies on board." In the midst of an ongoing legal challenge to the US National Institutes of Health's policy of funding human embryonic stem cell research, lawmakers led by House Representative Diana DeGette, a Democrat from Colorado, reintroduced a bill in late June that would provide Congress with the authority to use taxpayer dollars to support such science. But Louis Guenin, who teaches ethics at Harvard Medical School in Boston, notes that the proposed legislation "exceeds what the present political consensus will support" because it permits the government to fund efforts to create new embryonic stem cell lines and studies of cells obtained from cloned embryos that are not implanted. "It doesn't seem as if they truly get it in terms of how you should word things to make things unequivocal," says John Gearhart, director of the Institute for Regenerative Medicine at the University of Pennsylvania in Philadelphia. Under state law in the US, drug companies must inform consumers about new information on potential side effects. But federal regulations require generic manufacturers to carry the exact same label details as their branded equivalents. In a 5–4 decision in June, the US Supreme Court ruled that federal law trumps state law. As a result, generic firms cannot be sued for medication injuries that could have been avoided by updated warning labels. "What we have now is a situation where the regulatory framework means that generic manufacturers cannot make their drugs safe," says Stacey Lee, a legal scholar who studies the pharmaceutical industry at the Johns Hopkins Carey Business School in Baltimore. Facing pressure from academic and industry experts, the US Food and Drug Administration (FDA) agreed to ease safety restrictions on clinical trials for Alzheimer's drugs that aim to lower levels of amyloid-β. The agency mandated stricter enrollment criteria three years ago after a study testing an amyloid-targeted antibody led to around 5% of participants developing brain swelling. However, the FDA now says those rules were overly restrictive and agreed to follow recommendations made in a policy document published 12 July in Alzheimer's & Dementia (, 367–385, 2011), which proposed improved protocols for monitoring and detecting brain abnormalities. "The monitoring allows people to participate in the trial in the safest possible way," says Maria Carrillo, senior director of medical and scientific relations at the Chicago-based Alzheimer's Association. Protracted negotiations over a wide-ranging free trade agreement between India and the EU have stalled, in part over disagreements surrounding intellectual property rights in areas such as pharmaceuticals. But last month, Indian officials vowed that the proposed plan would not affect the country's production of cheap HIV drugs. "The government reaffirms its full commitment to ensure that quality generic medicines, including antiretroviral drugs, are seamlessly available," India's Commerce Minister Anand Sharma said in a statement issued by the Joint United Nations Programme on HIV/AIDS. India's pharmaceutical industry currently produces more than 85% of the world's first-line HIV treatments at a cost of less than $100 per person per year. Saybrook Ending months of wrangling to find a suitable successor to founding chairman Bob Klein, the board members of the California Institute for Regenerative Medicine (CIRM) in June elected bond financier Jonathan Thomas as their new leader. Taking over during an ongoing state budget crisis, Thomas pledged to secure stable funding for the $3 billion agency and to launch a communications effort aimed at bolstering the public's image of stem cell science. Thomas, who will earn around $400,000 per year for the position, also told Nature Medicine that he plans to "work with the FDA to establish a regulatory pathway for stem cell research and to markedly increase industry involvement in CIRM's funding program." Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data
• Double-duty discovery
  - Nat Med 17(8):912-915 (2011)
  Nature Medicine | News | News Feature Double-duty discovery * Cassandra Willyard1Journal name:Nature MedicineVolume: 17,Pages:912–915Year published:(2011)DOI:doi:10.1038/nm0811-912Published online04 August 2011 International collaborations are common in science. But some researchers go one step further, holding formal appointments in two (or more) countries—in some cases, on opposite sides of the globe. examines what researchers have to gain from such far-flung arrangements. View full text Additional data Affiliations * Cassandra Willyard is a science writer based in Brooklyn, New York. Author Details * Cassandra Willyard Search for this author in: * NPG journals * PubMed * Google Scholar
• A ballsy search for cancer targets
  - Nat Med 17(8):916-918 (2011)
  Nature Medicine | News | News Feature A ballsy search for cancer targets * Megan Scudellari1Journal name:Nature MedicineVolume: 17,Pages:916–918Year published:(2011)DOI:doi:10.1038/nm0811-916Published online04 August 2011 There are no magic bullets in the fight against cancer. But by targeting proteins found almost exclusively in tumor cells and the testes, researchers may have discovered the closest thing yet. explores how a handful of young investigators hope to turn magic into reality. View full text Additional data Affiliations * Megan Scudellari is a science journalist based in Durham, North Carolina. Author Details * Megan Scudellari Search for this author in: * NPG journals * PubMed * Google Scholar
• It's time for a centralized registry of laboratory-acquired infections
  - Nat Med 17(8):919 (2011)
  Nature Medicine | News | Opinion It's time for a centralized registry of laboratory-acquired infections * Kamaljit Singh1Journal name:Nature MedicineVolume: 17,Page:919Year published:(2011)DOI:doi:10.1038/nm0811-919Published online04 August 2011 A recent serious outbreak of Salmonella linked to clinical and teaching microbiology laboratories highlights the dangers of working with laboratory pathogens—but it is probably not an isolated occurrence. Without a better system for reporting infections resulting from laboratory exposures, we risk seeing more of these types of outbreaks. View full text Author information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Kamaljit Singh is assistant director of clinical microbiology at Rush University Medical Center in Chicago. Author Details * Kamaljit Singh Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• The heart of the matter
  - Nat Med 17(8):920 (2011)
  Article preview View full access options Nature Medicine | Book Review The heart of the matter * Roger J Hajjar1Journal name:Nature MedicineVolume: 17,Page:920Year published:(2011)DOI:doi:10.1038/nm0811-920Published online04 August 2011 Open Heart: The Radical Surgeons Who Revolutionized Medicine David Cooper Kaplan Publishing, 2010 448 pp., hardcover, $26.99 ISBN: 1607144905 Buy this book: USUKJapan Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The golden age of innovation in cardiac surgery was marked by unprecedented medical risks, a high level of academic competition and the determination of key personalities who dared to test the boundaries of healing the human heart. With the sixtieth anniversary of the first open heart surgery under hypothermia upon us, the book Open Heart provides a chronological map of the last 70 years in cardiac surgery, with an emphasis on the field's leading surgeons and their quests to cure diseases that were, at the time, considered incurable. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Affiliations * Roger J. Hajjar is at the Mount Sinai School of Medicine, New York, New York, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Roger J Hajjar Author Details * Roger J Hajjar Contact Roger J Hajjar Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• To march in or not to march in
  - Nat Med 17(8):921 (2011)
  Article preview View full access options Nature Medicine | Correspondence To march in or not to march in * C Allen Black Jr1Journal name:Nature MedicineVolume: 17,Page:921Year published:(2011)DOI:doi:10.1038/nm.2440Published online04 August 2011 To the Editor: In Nature Medicine's May editorial, "March on, not in" (Nat. Med.17, 515, 2011), the journal asserts that ending patent exclusivity for Fabrazyme and introducing generic competition in the US "could do far more harm than good." Yet, judging by the situation outside the US, where a competitive market already exists, this position is misplaced. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Law Office of C. Allen Black, Allison Park, Pennsylvania, USA. * C Allen Black Jr Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * C Allen Black Jr Author Details * C Allen Black Jr Contact C Allen Black Jr Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Reply to: To march in or not to march in
  - Nat Med 17(8):921-922 (2011)
  Article preview View full access options Nature Medicine | Correspondence Reply to: To march in or not to march in Journal name:Nature MedicineVolume: 17,Pages:921–922Year published:(2011)DOI:doi:10.1038/nm0811-921Published online04 August 2011 Nature Medicine replies: We thank Dr. Black for his thoughtful correspondence. Although we agree that alternate drug products could benefit patients with Fabry's disease in the US, we continue to think that marching in on Genzyme's intellectual property is not necessarily the way to achieve a competitive marketplace. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data
• Immune response also connects autism and epilepsy
  - Nat Med 17(8):922 (2011)
  Article preview View full access options Nature Medicine | Correspondence Immune response also connects autism and epilepsy * Abhay Sharma1Journal name:Nature MedicineVolume: 17,Page:922Year published:(2011)DOI:doi:10.1038/nm.2445Published online04 August 2011 To the Editor: In her timely news feature on the comorbidity of epilepsy and autism, Miley1 cites evidence that altered mTOR signaling may underlie these disorders. There is, however, another potential link between autism and epilepsy; increasing evidence implicates the immune response in the pathogenesis of these disorders. In a recently discovered epileptogenic cascade, injured neurons and glia can release a protein known as high-mobility group box-1 (HMGB1) (ref. 2). Interaction of this protein with Toll-like receptor 4 (TLR4) can affect voltage- and ligand-gated ion channels, which in turn enhance neuronal excitability. The HMGB1-TLR4 interaction has also been implicated in transcriptional activation of genes related both to inflammation and to neurotransmission and synaptic plasticity, which can result in perpetual inflammation and increased seizure susceptibility3. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Institute of Genomics and Integrative Biology, Council of Scientific and Industrial Research, Delhi, India. * Abhay Sharma Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Abhay Sharma Author Details * Abhay Sharma Contact Abhay Sharma Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Carvedilol tweaks calcium release to ease arrhythmias
  - Nat Med 17(8):923-924 (2011)
  Article preview View full access options Nature Medicine | Article Carvedilol and its new analogs suppress arrhythmogenic store overload–induced Ca2+ release * Qiang Zhou1, 2, 8 * Jianmin Xiao1, 8 * Dawei Jiang1 * Ruiwu Wang1 * Kannan Vembaiyan3 * Aixia Wang3 * Chris D Smith3 * Cuihong Xie1, 2, 8 * Wenqian Chen1 * Jingqun Zhang2 * Xixi Tian1 * Peter P Jones1, 8 * Xiaowei Zhong1 * Ang Guo4 * Haiyan Chen2 * Lin Zhang1 * Weizhong Zhu5 * Dongmei Yang6 * Xiaodong Li7 * Ju Chen7 * Anne M Gillis1 * Henry J Duff1 * Heping Cheng6, 8 * Arthur M Feldman5 * Long-Sheng Song4 * Michael Fill2 * Thomas G Back3 * S R Wayne Chen1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:1003–1009Year published:(2011)DOI:doi:10.1038/nm.2406Received10 February 2011Accepted23 May 2011Published online10 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * 日本語要約 * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Carvedilol is one of the most effective beta blockers for preventing ventricular tachyarrhythmias in heart failure, but the mechanisms underlying its favorable antiarrhythmic benefits remain unclear. Spontaneous Ca2+ waves, also called store overload–induced Ca2+ release (SOICR), evoke ventricular tachyarrhythmias in individuals with heart failure. Here we show that carvedilol is the only beta blocker tested that effectively suppresses SOICR by directly reducing the open duration of the cardiac ryanodine receptor (RyR2). This unique anti-SOICR activity of carvedilol, combined with its beta-blocking activity, probably contributes to its favorable antiarrhythmic effect. To enable optimal titration of carvedilol's actions as a beta blocker and as a suppressor of SOICR separately, we developed a new SOICR-inhibiting, minimally beta-blocking carvedilol analog, VK-II-86. VK-II-86 prevented stress-induced ventricular tachyarrhythmias in RyR2-mutant mice and did so more effectivel! y when combined with either of the selective beta blockers metoprolol or bisoprolol. Combining SOICR inhibition with optimal beta blockade has the potential to provide antiarrhythmic therapy that can be tailored to individual patients. Figures at a glance * Figure 1: Carvedilol inhibits SOICR in HEK293 cells. () The percentage of HEK293 cells (120–370 cells tested) in which SOICR was completely inhibited (n = 3–7). Cells were treated with the indicated beta blockers (30 μM) () or with prazosin (30 μM), phentolamine (30 μM), N-(2-mercaptopropionyl)-glycine (MPG, 1 mM), α-tocopherol (600 μM) or DMSO (control) (). () Fura-2 ratios of representative HEK293 cells treated with carvedilol () or metoprolol () (n = 3–8). () The percentage of cells with SOICR treated with metoprolol (210 cells tested) or carvedilol (1,027 cells tested) at the indicated concentrations. Error bar values are means ± s.e.m. **P < 0.01; versus metoprolol. * Figure 2: Carvedilol modifies the gating of single RyR2 channels. () Open probability (Po), mean open time (OT), mean closed time (CT) and event frequency (s−1) of native RyR2s from rat sarcoplasmic reticulum microsomes () or purified recombinant RyR2 R4496C channels () without (control) or with carvedilol. Tracings show single-channel currents. Openings are downward. Baselines are indicated (short bars). *P < 0.05; **P < 0.01; versus control. Error bar values are means ± s.e.m. * Figure 3: Carvedilol suppresses SOICR in mouse ventricular cardiomyocytes. () Line-scan confocal imaging of R4496C-heterozygous ventricular cardiomyocytes treated with the indicated agents for 30 min in the presence of 6 mM external Ca2+ (the height of each image represents 71.4 μm). (–) In cells treated with the indicated agents, the percentage of cells with SOICR (), the frequency of SOICR () and sarcoplasmic reticulum (SR) Ca2+ content (). () Single-cell epifluorescence imaging of SOICR in the presence of DMSO, metoprolol or carvedilol. (,) In cells (187–202 cells tested) treated with the indicated agents for 30 min (n = 6 separate experiments), the percentage of cells with SOICR () and SOICR frequency (). (,) In cells (147–225 cells tested) treated with the indicated agents for 3 h (n = 4–6 separate experiments), the percentage cells with SOICR () and SOICR frequency (). *P < 0.05; **P < 0.01; versus DMSO. Error bar values are means ± s.e.m. * Figure 4: Effect of VK-II-86 on heart rate, SOICR and single RyR2 channels. () Chemical structures of carvedilol and VK-II-86. () Isoproterenol (Iso)-stimulated heart rate () and unstimulated heart rate () in R4496C-heterozygous mice (n = 7–12 in each group) treated with the indicated agents (mg per kg body weight (BW) or mg per kg (BW) per day for 5 d). () The percentage of HEK293-R4496C cells with SOICR after treatment with DMSO or VK-II-86 (30 μM) (515 cells tested; n = 10 separate experiments. () Line-scan confocal imaging of SOICR in R4496C-heterozygous ventricular cardiomyocytes treated with VK-II-86 for 30 min. The percentage of cells with SOICR, the frequency of SOICR and sarcoplasmic reticulum (SR) Ca2+ content with the indicated agents are shown. (,) Single-cell epifluorescence imaging of SOICR in R4496C-heterozygous cardiomyocytes (177–208 cells tested) treated with VK-II-86 for 30 min (n = 6 separate experiments; ) or for 3 h (n = 6 separate experiments; ). The percentage of cells with SOICR and the frequency of SOICR with the indic! ated agents are shown. () Po, mean OT, mean CT and event frequency (s−1) of single purified RyR2 R4496C channels preincubated (1 h) with VK-II-86 (1 μM) or control (no treatment). *P < 0.05; **P < 0.01; versus DMSO or control. #P < 0.05; ##P < 0.01; versus carvedilol. Error bar values are means ± s.e.m. NS, not significant. * Figure 5: Effects of VK-II-86 on CPVT in R4496C-heterozygous or homozygous mice. () Representative electrocardiogram (ECG) recordings of WT () and R4496C-heterozygous mutant () mice before and after intraperitoneal injection of epinephrine (1.6 mg per kg body weight (BW)) and caffeine (120 mg per kg body weight) (epi/caff). () Ventricular tachyarrhythmia (VT) duration in WT or in R4496C-heterozygous mice (n = 12–33) per 3-min () or 30-min period () of ECG recordings (**P < 0.01 versus WT). () Representative ECG recordings of R4496C-heterozygous mice treated with VK-II-86 before and after the administration of arrhythmic triggers. () VT duration in R4496C-heterozygous mice treated with the indicated agents (mg kg−1 d−1 for 5 d). *P < 0.01 versus DMSO. () VT duration per 3-min period in RyR2 R4496C-homozygous mice post-treated with the indicated agents (*P < 0.05; **P < 0.01; versus DMSO). () VT duration in R4496C-heterozygous mice treated with the indicated agents (mg per kg body weight per day for 5 d). *P < 0.05; **P < 0.01; versus DMSO. ##P < 0.0! 1; versus VK-II-86 plus metoprolol. $P < 0.05; $$P < 0.01; versus VK-II-86 plus bisoprolol. Error bar values are means ± s.e.m. * Figure 6: Effects of CS-I-34 and CS-I-59 on heart rate, SOICR and CPVT. () Chemical structures of CS-I-34 and CS-I-59. () Isoproterenol (Iso)-stimulated heart rate and () unstimulated heart rates in R4496C-heterozygous mice treated with the indicated agents (mg per kg body weight (BW) or mg per kg (BW) per day for 5 d). () Single-cell epifluorescence imaging of SOICR in R4496C-heterozygous ventricular cardiomyocytes (141–144 cells tested) treated with drugs for 30 min (n = 4 separate experiments). The percentage of cells with SOICR and the frequency of SOICR with the indicated agents are shown. () The percentage of HEK293 cells expressing RyR2 R4496C (137–457 cells tested) with SOICR in the presence of the indicated agents (n = 5–9 separate experiments) at the indicated concentrations. () Ventricular tachyarrhythmia duration in R4496C-heterozygous mice treated with drugs (mg kg−1 d−1 for 5 d). *P < 0.05; **P < 0.01; versus DMSO or control. ##P < 0.01; versus carvedilol. Error bar values are means ± s.e.m. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information * Abstract * Author information * Supplementary information Affiliations * Libin Cardiovascular Institute of Alberta, Department of Physiology and Pharmacology, University of Calgary, Calgary, Alberta, Canada. * Qiang Zhou, * Jianmin Xiao, * Dawei Jiang, * Ruiwu Wang, * Cuihong Xie, * Wenqian Chen, * Xixi Tian, * Peter P Jones, * Xiaowei Zhong, * Lin Zhang, * Anne M Gillis, * Henry J Duff & * S R Wayne Chen * Department of Molecular Biophysics and Physiology, Rush University Medical Center, Chicago, Illinois, USA. * Qiang Zhou, * Cuihong Xie, * Jingqun Zhang, * Haiyan Chen, * Michael Fill & * S R Wayne Chen * Department of Chemistry, University of Calgary, Calgary, Alberta, Canada. * Kannan Vembaiyan, * Aixia Wang, * Chris D Smith & * Thomas G Back * Division of Cardiovascular Medicine, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA. * Ang Guo & * Long-Sheng Song * Department of Medicine, Center for Translational Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, USA. * Weizhong Zhu & * Arthur M Feldman * Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA. * Dongmei Yang & * Heping Cheng * Department of Medicine, University of California at San Diego, La Jolla, California, USA. * Xiaodong Li & * Ju Chen * Present addresses: Department of Cardiology of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (Q.Z.); Department of Cardiology, Taiping People's Hospital of Dongguan, Guangdong, China (J.X.); Department of Emergency of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (C.X.); Department of Physiology, University of Otago, Dunedin, New Zealand (P.P.J.); Institute of Molecular Medicine, Peking University, Beijing, China (H. Cheng). * Qiang Zhou, * Jianmin Xiao, * Cuihong Xie, * Peter P Jones & * Heping Cheng Contributions Q.Z., J.X., D.J., R.W., K.V., A.W., C.D.S., W.Z., D.Y., J.C., A.M.G., H.J.D., H. Cheng, A.M.F., L.-S.S., M.F., T.G.B. and S.R.W.C. designed research; Q.Z., J.X., D.J., R.W., K.V., A.W., C.D.S., C.X., W.C., J.Z., W.Z., X.T., P.P.J., X.Z., A.G., H. Chen, L.Z., D.Y. and X.L. carried out research; Q.Z., J.X., D.J., C.X., W.C., J.Z., W.Z., X.T., P.P.J., X.Z., A.G., H. Chen, L.Z. and D.Y. analyzed data; and Q.Z., R.W., C.D.S., W.Z., M.F., T.G.B. and S.R.W.C. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * S R Wayne Chen Author Details * Qiang Zhou Search for this author in: * NPG journals * PubMed * Google Scholar * Jianmin Xiao Search for this author in: * NPG journals * PubMed * Google Scholar * Dawei Jiang Search for this author in: * NPG journals * PubMed * Google Scholar * Ruiwu Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Kannan Vembaiyan Search for this author in: * NPG journals * PubMed * Google Scholar * Aixia Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Chris D Smith Search for this author in: * NPG journals * PubMed * Google Scholar * Cuihong Xie Search for this author in: * NPG journals * PubMed * Google Scholar * Wenqian Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Jingqun Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Xixi Tian Search for this author in: * NPG journals * PubMed * Google Scholar * Peter P Jones Search for this author in: * NPG journals * PubMed * Google Scholar * Xiaowei Zhong Search for this author in: * NPG journals * PubMed * Google Scholar * Ang Guo Search for this author in: * NPG journals * PubMed * Google Scholar * Haiyan Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Lin Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Weizhong Zhu Search for this author in: * NPG journals * PubMed * Google Scholar * Dongmei Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Xiaodong Li Search for this author in: * NPG journals * PubMed * Google Scholar * Ju Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Anne M Gillis Search for this author in: * NPG journals * PubMed * Google Scholar * Henry J Duff Search for this author in: * NPG journals * PubMed * Google Scholar * Heping Cheng Search for this author in: * NPG journals * PubMed * Google Scholar * Arthur M Feldman Search for this author in: * NPG journals * PubMed * Google Scholar * Long-Sheng Song Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Fill Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas G Back Search for this author in: * NPG journals * PubMed * Google Scholar * S R Wayne Chen Contact S R Wayne Chen Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–10, Supplementary Table 1 and Supplementary Methods Additional data
• A step toward slaying the hydra of second cancers
  - Nat Med 17(8):924-925 (2011)
  Article preview View full access options Nature Medicine | Brief Communication Variants at 6q21 implicate PRDM1 in the etiology of therapy-induced second malignancies after Hodgkin's lymphoma * Timothy Best1 * Dalin Li2 * Andrew D Skol3 * Tomas Kirchhoff4 * Sarah A Jackson3 * Yutaka Yasui5 * Smita Bhatia6 * Louise C Strong7 * Susan M Domchek8 * Katherine L Nathanson8 * Olufunmilayo I Olopade3 * R Stephanie Huang3 * Thomas M Mack2, 9 * David V Conti2 * Kenneth Offit4 * Wendy Cozen2, 9 * Leslie L Robison10 * Kenan Onel1, 11 * Affiliations * Contributions * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:941–943Year published:(2011)DOI:doi:10.1038/nm.2407Received11 January 2011Accepted24 May 2011Published online24 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * 日本語要約 * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Survivors of pediatric Hodgkin's lymphoma are at risk for radiation therapy–induced second malignant neoplasms (SMNs). We identified two variants at chromosome 6q21 associated with SMNs in survivors of Hodgkin's lymphoma treated with radiation therapy as children but not as adults. The variants comprise a risk locus associated with decreased basal expression of PRDM1 (encoding PR domain containing 1, with ZNF domain) and impaired induction of the PRDM1 protein after radiation exposure. These data suggest a new gene-exposure interaction that may implicate PRDM1 in the etiology of radiation therapy-induced SMNs. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information * Abstract * Author information * Supplementary information Affiliations * Committee on Cancer Biology, University of Chicago, Chicago, Illinois, USA. * Timothy Best & * Kenan Onel * Department of Preventive Medicine, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA. * Dalin Li, * Thomas M Mack, * David V Conti & * Wendy Cozen * Department of Medicine, University of Chicago, Chicago, Illinois, USA. * Andrew D Skol, * Sarah A Jackson, * Olufunmilayo I Olopade & * R Stephanie Huang * Department of Medicine, Clinical Genetics Service, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. * Tomas Kirchhoff & * Kenneth Offit * Department of Public Health Sciences, University of Alberta, Edmonton, Alberta, Canada. * Yutaka Yasui * Department of Population Sciences, City of Hope, Duarte, California, USA. * Smita Bhatia * Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA. * Louise C Strong * Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA. * Susan M Domchek & * Katherine L Nathanson * Department of Pathology, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA. * Thomas M Mack & * Wendy Cozen * Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee, USA. * Leslie L Robison * Department of Pediatrics, University of Chicago, Chicago, Illinois, USA. * Kenan Onel Contributions T.B. and K. Onel designed the study and wrote the manuscript with substantial contributions from A.D.S., Y.Y., S.B., L.C.S., R.S.H., T.M.M., D.V.C., K. Offit, W.C. and L.L.R.; T.B. performed the experiments and undertook the analysis; D.L., A.D.S., T.K., and Y.Y. performed data analysis; S.A.J., S.M.D., K.L.N., O.I.O., W.C. and L.L.R. provided clinical samples and performed analysis of subject data; K. Onel directed the project. All authors contributed to the final manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Kenan Onel Author Details * Timothy Best Search for this author in: * NPG journals * PubMed * Google Scholar * Dalin Li Search for this author in: * NPG journals * PubMed * Google Scholar * Andrew D Skol Search for this author in: * NPG journals * PubMed * Google Scholar * Tomas Kirchhoff Search for this author in: * NPG journals * PubMed * Google Scholar * Sarah A Jackson Search for this author in: * NPG journals * PubMed * Google Scholar * Yutaka Yasui Search for this author in: * NPG journals * PubMed * Google Scholar * Smita Bhatia Search for this author in: * NPG journals * PubMed * Google Scholar * Louise C Strong Search for this author in: * NPG journals * PubMed * Google Scholar * Susan M Domchek Search for this author in: * NPG journals * PubMed * Google Scholar * Katherine L Nathanson Search for this author in: * NPG journals * PubMed * Google Scholar * Olufunmilayo I Olopade Search for this author in: * NPG journals * PubMed * Google Scholar * R Stephanie Huang Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas M Mack Search for this author in: * NPG journals * PubMed * Google Scholar * David V Conti Search for this author in: * NPG journals * PubMed * Google Scholar * Kenneth Offit Search for this author in: * NPG journals * PubMed * Google Scholar * Wendy Cozen Search for this author in: * NPG journals * PubMed * Google Scholar * Leslie L Robison Search for this author in: * NPG journals * PubMed * Google Scholar * Kenan Onel Contact Kenan Onel Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (610K) Supplementary Figures 1–6, Supplementary Tables 1–8 and Supplementary Methods Additional data
• A suPAR circulating factor causes kidney disease
  - Nat Med 17(8):926-927 (2011)
  Article preview View full access options Nature Medicine | Article Circulating urokinase receptor as a cause of focal segmental glomerulosclerosis * Changli Wei1 * Shafic El Hindi1, 18 * Jing Li1, 18 * Alessia Fornoni1, 2, 18 * Nelson Goes3 * Junichiro Sageshima4 * Dony Maiguel1 * S Ananth Karumanchi5 * Hui-Kim Yap6 * Moin Saleem7 * Qingyin Zhang8 * Boris Nikolic3 * Abanti Chaudhuri9 * Pirouz Daftarian10, 11 * Eduardo Salido12 * Armando Torres12 * Moro Salifu13 * Minnie M Sarwal9 * Franz Schaefer14 * Christian Morath15 * Vedat Schwenger15 * Martin Zeier15 * Vineet Gupta1 * David Roth1 * Maria Pia Rastaldi16 * George Burke4 * Phillip Ruiz4, 17 * Jochen Reiser1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:952–960Year published:(2011)DOI:doi:10.1038/nm.2411Received05 January 2011Accepted31 May 2011Published online31 July 2011 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * 日本語要約 * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Focal segmental glomerulosclerosis (FSGS) is a cause of proteinuric kidney disease, compromising both native and transplanted kidneys. Treatment is limited because of a complex pathogenesis, including unknown serum factors. Here we report that serum soluble urokinase receptor (suPAR) is elevated in two-thirds of subjects with primary FSGS, but not in people with other glomerular diseases. We further find that a higher concentration of suPAR before transplantation underlies an increased risk for recurrence of FSGS after transplantation. Using three mouse models, we explore the effects of suPAR on kidney function and morphology. We show that circulating suPAR activates podocyte β3 integrin in both native and grafted kidneys, causing foot process effacement, proteinuria and FSGS-like glomerulopathy. Our findings suggest that the renal disease only develops when suPAR sufficiently activates podocyte β3 integrin. Thus, the disease can be abrogated by lowering serum suPAR concen! trations through plasmapheresis, or by interfering with the suPAR–β3 integrin interaction through antibodies and small molecules targeting either uPAR or β3 integrin. Our study identifies serum suPAR as a circulating factor that may cause FSGS. Figures at a glance * Figure 1: suPAR measurement in the serum of subjects with glomerular disease. For transplant subjects, the suPAR values were measured from pretransplantation serum unless otherwise indicated. Data is presented as means ± s.e.m. () Serum suPAR concentration in subjects with glomerular disease and healthy human subjects. MN, membranous nephropathy. *P < 0.05 for FSGS versus MN and preeclampsia; #P < 0.001 for FSGS versus healthy, MCD relapse, and MCD remission. Note that the values highlighted with red or green dots in the healthy subject and FSGS columns are identical twin pairs; in each case, one is healthy and has a twin brother with FSGS. () Serum suPAR in different population of subjects with primary FSGS. **P < 0.01 for recurrent FSGS versus nonrecurrent FSGS and nontransplant primary FSGS, respectively. () Serum suPAR concentrations after transplantation. #P < 0.001. () Correlation analysis of pretransplantation suPAR with proteinuria after transplantation. Pearson r = 0.16, P = 0.50. () Correlation analysis of pretransplantation suPAR with eGFR! . Pearson r = 0.36, P = 0.16. () Correlation analysis of suPAR after transplantation with eGFR. Pearson r = 0.10, P = 0.58. * Figure 2: suPAR binds to and activates β3 integrin on podocytes. () Western blot showing that suPAR binds β3 integrin (representative of three experiments). EIF1B-GFP, encoding a translation initiation factor, and Raver-Flag encoding a ribonucleoprotein served as negative binding controls. β3 integrin is encoded by Itgb3. S, sPlaurWT (encoding suPAR); M, PlaurWT (encoding membrane-bound uPAR); IP, immunoprecipitation. () AP5 immunostaining of differentiated human podocytes incubated with suPAR-rich recurrent FSGS serum (rec-FSGS serum), co-treated with the monoclonal antibody to human uPAR (uPAR mAb), and with cycloRGDfv, a small molecule that blocks β3 integrin activity. AP5-specific antibody detects the active form of β3 integrin. Bovine serum, negative control; suPAR, recombinant human suPAR protein. () Immunohistochemistry of AP5 on kidney biopsies from patients with glomerular disease. Top, representative AP5 staining in the glomerulus of subjects with FSGS. Bottom, the percentage (mean ± s.e.m.) of AP5-positive glomeruli. *P < ! 0.05 for primary FSGS versus control; **P < 0.01 for recurrent FSGS versus control. () Double immunofluorescent staining in glomeruli of kidney grafts for AP5 (green) and the podocyte marker synaptopodin (red). Top and bottom left, AP5 in the graft glomerulus 2 h after reperfusion in recurrent and nonrecurrent transplant biopsies (n = 2 per group). Top right, AP5 signal in recurrent transplant biopsies (n = 3) and nonrecurrent grafts (n = 5). Bottom right, normal kidney sections (n = 2) and biopsies from acute T cell–mediated rejections (n = 3) served as controls. Scale bars, 30 μm. * Figure 3: suPAR serum concentrations and podocyte β3 integrin activity determine treatment response to plasmapheresis in recurrent FSGS. () Human podocytes incubated with different pooled serum samples and assayed for β3 integrin activity. MFI, mean fluorescence intensity. *P < 0.05 for nonrecurrent FSGS versus normal subjects, ***P < 0.001 for recurrent versus nonrecurrent FSGS or versus healthy subjects. The respective suPAR concentration of the pooled sera is marked in red. NS, normal (healthy) subject; NR, nonrecurrent FSGS; REC, recurrent FSGS (representative of three experiments). () Pharmacological modulation of β3 integrin activity in podocytes. **P < 0.01 for cylcoRGDfv co-treated cells versus recurrent FSGS serum alone; ***P < 0.001 for uPAR-specific mAb co-treated cells versus recurrent FSGS serum alone. () suPAR in serum from subjects with recurrent FSGS (n = 4) before and after a course of plasmapheresis. **P < 0.01. () Effect of plasmapheresis on β3 integrin activity in podocytes incubated with recurrent FSGS serum (n = 6), collected before and after serial treatment with plasmapheresis. ***P! < 0.001. (–) Clinical cases of recurrent FSGS. Top graphs show serum suPAR, urine protein/creatinine ratio (g/g) and individual plasmapheresis treatment as indicated by arrows and plotted over time () from before (−1) to after transplantation. Bottom graphs and images show podocyte β3 integrin activity measured by FACS (left) and immunofluorescence (right) as a result of incubation with pretransplantation serum, or with the after-transplantation serum collected after repetitive plasmapheresis treatments. As a reference, the mean concentration of AP5 from is marked as a dashed line. (,) Patients who obtained full remission after pheresis. (,) Patients who did not achieve remission after pheresis. Scale bars, 30 μm. Whiskers in plots of AP5 activity and serum suPAR show minimum to maximum. * Figure 4: suPAR activates β3 integrin and causes foot process effacement in Plaur−/− mouse kidneys and albuminuria in Plaur−/− mice. () Injection (i.v.) of high doses of recombinant mouse suPAR into Plaur−/− mice (n = 4 per group) induces proteinuria. **P < 0.01 for mice injected with 20 μg of suPAR at 24 h versus mice injected with other doses or versus other time points. () Injection (i.v.) of high doses of recombinant suPAR deposits into podocytes. Green, uPAR; red, synaptopodin (Synpo). () AP5 activity induced in the podocytes of high-dosage suPAR-injected Plaur−/− mice (n = 4). Green, AP5; red, Synpo. (,) LPS induced endogenous suPAR in wild-type mice (n = 6). () Serum suPAR concentrations in LPS-treated mice. ***P < 0.001 for LPS-injected mice at 24 h versus PBS control, and versus LPS-injected mice at 0 h. **P < 0.01 for LPS-injected mice at 48 h versus at 0 h. () Urinary suPAR concentrations. ***P < 0.001 for LPS-injected mice at 48 h versus 0 h, and versus PBS control at any time point. **P < 0.01 for LPS-injected mice at 24 h versus 0 h. () Generation of a hybrid-kidney mouse model. () ! Electron microscope analysis of the PBS (n = 3) or LPS (n = 5) treated hybrid kidney. () uPAR expression in the native or Plaur−/− kidneys from the hybrid-kidney mice with or without LPS treatment. Scale bars, 30 μm in , and ; 250 nm in . Error bars, means ± s.e.m. in ; means ± s.d. in ,. * Figure 5: Sustained overexpression of suPAR in the blood of wild-type mice leads to an FSGS-like glomerulopathy. () Generation of β3 integrin binding–deficient suPAR mutants. () Serum suPAR concentrations in the sPlaurWT engineered mice. *P < 0.05 at day 7 versus day 0 (before initial electroporation) () Urinary suPAR in sPlaurWT engineered mice. ***P < 0.001 for days 7, 14 and 28 versus day 0; *P < 0.05 for day 28 versus day 7. (n = 4 in each group). () Albuminuria in sPlaurWT and sPlaurE134A mice. *P < 0.05 for sPlaurWT mice at day 7 versus before treatment or versus sPlaurE134A mice at day 7. **P < 0.01 for sPlaurWT engineered mice at day 14 versus before treatment or versus sPlaurE134A treated mice at day 7 or 14. () Kidney EM analysis of sPlaur engineered mice. Podocyte damage is reflected by relating the length of effaced foot process (FP) to the total length of the glomerular basement membrane (GBM) analyzed. Scale bars, 1 μm for upper image, 250 nm for lower image. **P < 0.01. () Histochemistry and light microscopy of the kidney from sPlaur engineered mice. PAS, periodic ac! id–Schiff. Scale bars, 30 μm. () Histopathological alteration of the kidneys was semiquantitatively scored. *P < 0.05. Error bars, means ± s.e.m. in ; means ± s.d. in ,, and . * Figure 6: Administration of blocking antibody to uPAR ameliorates suPAR-caused kidney damage. (n = 4 in each group). () Proteinuria in the antibody treated sPlaurWT mice. *P < 0.05 for sPlaurWT mice receiving isotype control at day 7 versus before initial electroporation at day 0 or versus mice treated with antibody to uPAR at day 7; ***P < 0.01 for sPlaurWT mice receiving isotype control at day 21 versus at day 0 or versus antibody to uPAR-treated mice at day 21. () Morphological examination of the antibody treated sPlaurWT kidney. Scale bars, 30 μm. () Pathology score. *P < 0.05. () Electron microscopic analysis of the antibody treated kidney from sPlaurWT engineered mice. **P < 0.01 for IgG isotype control versus uPAR-specific antibody–treated sPlaurWT engineered mice with respect to the ratio of effaced foot process (FP) to total GBM length measured. Scale bar, 360 nm. Error bars, means ± s.e.m. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions GenBank * BC010309 Author information * Abstract * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Shafic El Hindi, * Jing Li & * Alessia Fornoni Affiliations * Department of Medicine, Miller School of Medicine, University of Miami, Miami, Florida, USA. * Changli Wei, * Shafic El Hindi, * Jing Li, * Alessia Fornoni, * Dony Maiguel, * Vineet Gupta, * David Roth & * Jochen Reiser * Diabetes Research Institute, Miller School of Medicine, University of Miami, Miami, Florida, USA. * Alessia Fornoni * Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. * Nelson Goes & * Boris Nikolic * Department of Surgery, Miller School of Medicine, University of Miami, Miami, Florida, USA. * Junichiro Sageshima, * George Burke & * Phillip Ruiz * Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA. * S Ananth Karumanchi * Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. * Hui-Kim Yap * University of Bristol, Children's Renal Unit, Bristol Royal Hospital for Children, Bristol, UK. * Moin Saleem * Department of Surgery, Columbia University, New York, New York, USA. * Qingyin Zhang * Department of Pediatrics, Stanford University, Stanford, California, USA. * Abanti Chaudhuri & * Minnie M Sarwal * The Wallace H. Coulter Center for Translational Research, Miller School of Medicine, University of Miami, Miami, Florida, USA. * Pirouz Daftarian * Department of Ophthalmology, Miller School of Medicine, University of Miami, Miami, Florida, USA. * Pirouz Daftarian * Servicio de Nefrologia and Centre for Biomedical Research on Rare Diseases (CIBERER), Hospital Universitario de Canarias, Canary Islands, Spain. * Eduardo Salido & * Armando Torres * Division of Nephrology, SUNY Downstate Medical Center, Brooklyn, New York, USA. * Moro Salifu * Center for Pediatric and Adolescent Medicine, University of Heidelberg, Heidelberg, Germany. * Franz Schaefer * Department of Nephrology and Endocrinology, University of Heidelberg, Heidelberg, Germany. * Christian Morath, * Vedat Schwenger & * Martin Zeier * Renal Research Laboratory, Fondazione IRCCS Ospedale Maggiore Policlinico & Fondazione D'Amico per la Ricerca sulle Malattie Renali, Milan, Italy. * Maria Pia Rastaldi * Department of Pathology, Miller School of Medicine, University of Miami, Miami, Florida, USA. * Phillip Ruiz Contributions J.R. conceived the study. J.R. and C.W. designed the experiments, coordinated the study, analyzed the data and wrote the manuscript. C.W., S.E.H., J.L., D.M., Q.Z., B.N., P.D., V.G. performed the experiments. A.F., N.G., G.B., J.S., S.A.K., H.-K.Y., M.Saleem, A.C., E.S., A.T., M.Salifu, M.M.S., F.S., C.M., V.S., M.Z., D.R., M.P.R., P.R., J.R. contributed to clinical samples and clinical information. M.P.R. and P.R. provided pathology service. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Jochen Reiser Author Details * Changli Wei Search for this author in: * NPG journals * PubMed * Google Scholar * Shafic El Hindi Search for this author in: * NPG journals * PubMed * Google Scholar * Jing Li Search for this author in: * NPG journals * PubMed * Google Scholar * Alessia Fornoni Search for this author in: * NPG journals * PubMed * Google Scholar * Nelson Goes Search for this author in: * NPG journals * PubMed * Google Scholar * Junichiro Sageshima Search for this author in: * NPG journals * PubMed * Google Scholar * Dony Maiguel Search for this author in: * NPG journals * PubMed * Google Scholar * S Ananth Karumanchi Search for this author in: * NPG journals * PubMed * Google Scholar * Hui-Kim Yap Search for this author in: * NPG journals * PubMed * Google Scholar * Moin Saleem Search for this author in: * NPG journals * PubMed * Google Scholar * Qingyin Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Boris Nikolic Search for this author in: * NPG journals * PubMed * Google Scholar * Abanti Chaudhuri Search for this author in: * NPG journals * PubMed * Google Scholar * Pirouz Daftarian Search for this author in: * NPG journals * PubMed * Google Scholar * Eduardo Salido Search for this author in: * NPG journals * PubMed * Google Scholar * Armando Torres Search for this author in: * NPG journals * PubMed * Google Scholar * Moro Salifu Search for this author in: * NPG journals * PubMed * Google Scholar * Minnie M Sarwal Search for this author in: * NPG journals * PubMed * Google Scholar * Franz Schaefer Search for this author in: * NPG journals * PubMed * Google Scholar * Christian Morath Search for this author in: * NPG journals * PubMed * Google Scholar * Vedat Schwenger Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Zeier Search for this author in: * NPG journals * PubMed * Google Scholar * Vineet Gupta Search for this author in: * NPG journals * PubMed * Google Scholar * David Roth Search for this author in: * NPG journals * PubMed * Google Scholar * Maria Pia Rastaldi Search for this author in: * NPG journals * PubMed * Google Scholar * George Burke Search for this author in: * NPG journals * PubMed * Google Scholar * Phillip Ruiz Search for this author in: * NPG journals * PubMed * Google Scholar * Jochen Reiser Contact Jochen Reiser Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (688K) Supplementary Figures 1–3, Supplementary Tables 1–3 and Supplementary Methods Additional data
• Killing the messenger to maintain control of HIV
  - Nat Med 17(8):927-928 (2011)
  Article preview View full access options Nature Medicine | Article Protective HIV-specific CD8+ T cells evade Treg cell suppression * Shokrollah Elahi1 * Warren L Dinges1, 2 * Nicholas Lejarcegui1 * Kerry J Laing3 * Ann C Collier4 * David M Koelle3, 4, 5, 6, 7 * M Juliana McElrath3, 4, 5, 6 * Helen Horton1, 4, 5 * Affiliations * Contributions * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:989–995Year published:(2011)DOI:doi:10.1038/nm.2422Received09 March 2011Accepted15 June 2011Published online17 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * 日本語要約 * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Specific human leukocyte antigens (HLAs), notably HLA-B*27 and HLA-B*57 allele groups, have long been associated with control of HIV-1. Although the majority of HIV-specific CD8+ T cells lose proliferative capacity during chronic infection, T cells restricted by HLA-B*27 or HLA-B*57 allele groups do not. Here we show that CD8+ T cells restricted by 'protective' HLA allele groups are not suppressed by Treg cells, whereas, within the same individual, T cells restricted by 'nonprotective' alleles are highly suppressed ex vivo. This differential sensitivity of HIV-specific CD8+ T cells to Treg cell–mediated suppression correlates with their expression of the inhibitory receptor T cell immunoglobulin domain and mucin domain 3 (Tim-3) after stimulation with their cognate epitopes. Furthermore, we show that HLA-B*27– and HLA-B*57–restricted effectors also evade Treg cell–mediated suppression by directly killing Treg cells they encounter in a granzyme B (GzmB)-dependent mann! er. This study uncovers a previously unknown explanation for why HLA-B*27 and HLA-B*57 allele groups are associated with delayed HIV-1 disease progression. Figures at a glance * Figure 1: Treg cell suppression of in vitro proliferative ability or cytokine secretion of CD8+ T cells restricted by HLA-B*57, HLA-B*27, HLA-A*03 and control HLAs (HLA-A*02, HLA-A*24 and HLA-B*08). () Background-subtracted percentage CFSEloCD8+ T cells in PBMCs with or without Treg cells when cultured in the presence of HIV-1 epitopes recognized by CD8+ T cells restricted by various HLA alleles. () Background-subtracted HIV-specific IFN-γ ELISPOT responses in the presence and absence of Treg cells. HLA-B*27 or HLA-B*57–restricted and non–HLA-B*27– and HLA-B*57–restricted responses are shown after stimulation with their cognate epitopes. SFC, spot-forming cell. In and , Wilcoxon signed-rank (WSR) test was used. () Percentage suppression of proliferation grouped according to HLA restricting allele. () Percentage suppression of cytokine secretion grouped according to HLA restricting allele. In and , Kruskal-Wallis (KW) test was used for grouped comparisons with a post hoc Dunn's test showing significant subgroup comparisons with horizontal lines. () Differential suppression of proliferation of HLA-B*27– and HLA-B*57– versus HLA-A*03– and control HLA–restr! icted HIV-specific CD8+ CTLs within the same person. NP02 and NP41 are two LTNPs. () Percentage suppression of proliferation by Treg cells of HLA-B*57–restricted CD8+ CTLs in HLA-B*57+ LTNP versus HLA-B*57+ delayed progressors (DP). () Longitudinal analyses of percentage suppression of proliferation by Treg cells of HLA-B*57–restricted CD8+ CTLs before and after progression in HLA-B*57++ individuals. * Figure 2: Frequency of CD8+Tim-3+ T cells following stimulation with their cognate epitopes. () Percentage of Tim-3+ CD8+ T cells using allophycocyanin-labeled HLA-A*03–RLRPGGKKK tetramer or phycoerythrin-labeled HLA-B*57-TSTLQEQIGW tetramer staining of PBMCs before and after stimulation with their cognate epitopes. Top right quadrant shows percentage of Tim-3+ tetramer+ CD8+ CTLs. () Percentage of Tim-3+ on CD8+ T cells using CD137 to identify antigen-specific T cells after stimulation with their cognate epitopes. () Percentage of CD137+Tim-3+ T cells after stimulation of PBMCs from different individuals with their corresponding epitopes. * Figure 3: CFSE dilution data showing inhibition of Gal-9–Tim-3 interactions by lactose and siRNA. () Examples of proliferation of PBMCs stimulated with their corresponding epitopes, showing percentage CFSEloCD8+ T cells in the absence or presence of lactose. () Examples of proliferation of CFSE-labeled, Treg cell–depleted PBMCs stimulated with their cognate epitopes in the presence of Treg cells treated with either LGALS9 siRNA or siControl (at 1:0.25 ratio). The measures of coculture suppression by Treg cells in the presence or absence of lactose or siRNA are shown for a representative experiment from three repeat experiments for each approach. () Percentage of Treg cell suppression calculated after stimulation of CD8+ T cells with their corresponding epitopes in the presence of lactose. () Percentage of Treg cell suppression calculated after stimulation of CD8+ T cells with their cognate epitopes in the presence of LGALS9 siRNA–treated Treg cells (at 1:0.25 ratio). * Figure 4: CFSE dilution data showing CD8+ T cells restricted by HLA-B*57 and HLA-B*27 resist Treg cell-mediated suppression in a GzmB dependent manner. () Percentage CFSEloCD8+ T cells after CFSE-labeled isolated CD8+ T cells were stimulated with their corresponding epitopes alone or together with Treg cells (at 1:0.25 ratio), and also in the presence or absence of a GzmB peptide inhibitor (z-AAD-CMK). Examples of flow data are shown in Supplementary Figure 3a. () Percentage CFSEloCD8+ T cells after electroporation with GZMB siRNA or nonhybridizing negative control (siControl) siRNA oligonucleotides and stimulation with their cognate epitopes alone or with Treg cells (at 1:0.25 ratio). Examples of flow data are shown in Supplementary Figure 3b. * Figure 5: CD8+ T cells restricted by HLA-B*27 and HLA-B*57 induce Treg apoptosis in a GzmB-dependent manner. (–) Percentage annexin V+ Treg cells (CD3+CD4+CD25hiCD127lo) in PBMCs stimulated for 4 d (), 24 h () or 24–72 h () with HLA-B*27–, HLA-B*57–, HLA-B*39– or HLA-A*03–restricted epitopes in the presence or absence of GzmB peptide inhibitor. These data are representative of three separate experiments from different LTNPs. () Percentage annexin V+ Treg cells in PBMCs stimulated with HLA-B*57–restricted epitopes from HLA-B*57+ LTNP versus HLA-B*57+ DPs. (,) Percentage annexin V+ Treg cells in PBMCs stimulated with HLA-B*57–restricted epitopes before and after progression to disease. () Treg cell frequencies in HIV-1–seronegative individuals versus HIV-1 infected HLA-B*27++ or HLA-B*57+ and HLA-B*27−− or HLA-B*57− LTNPs. Percentages of CD4+CD25hiFOXP3+ Treg cells are shown in PBMCs from 12 HIV-seronegative HLA-B*27+ or HLA-B*57+ individuals, 12 HLA-B*27− or HLA-B*-57− individuals, 13 HLA-B*27++ or HLA-B*57+ LTNPs and 8 HLA-B*27− or HLA-B*57− LTNPs. * Figure 6: Model depicting how HLA-B*27– or HLA-B*57–restricted HIV-specific CD8+ T cells evade Treg cell suppression and subsequently control HIV replication. HIV-specific, HLA-B*27–restricted CD8+ T cells do not upregulate surface expression of Tim-3 upon recognition of their cognate epitopes on HIV-infected CD4+ T cells, whereas HIV-specific, HLA-A*03–restricted CD8+ T cells upregulate high surface expression of Tim-3. Treg cells suppress HLA-A*03–restricted CD8+ T cells owing to their high expression of Tim-3 but cannot suppress proliferation of HLA-B*27–restricted CD8+ T cells. Highly proliferating HLA-B*27–restricted CD8+ T cells upregulate high levels of GzmB and kill not only infected CD4+ T cells but also infected Treg cells that they encounter. Thus, HLA-B*27–restricted CD8+ T cells can control HIV replication during chronic infection, whereas HLA-A*03–restricted CD8+ T cells cannot. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information * Abstract * Author information * Supplementary information Affiliations * Viral Vaccine Program, Seattle Biomedical Research Institute (Seattle Biomed), Seattle, Washington, USA. * Shokrollah Elahi, * Warren L Dinges, * Nicholas Lejarcegui & * Helen Horton * Polyclinic Infectious Disease, Seattle, Washington, USA. * Warren L Dinges * Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. * Kerry J Laing, * David M Koelle & * M Juliana McElrath * Department of Medicine, University of Washington, Seattle, Washington, USA. * Ann C Collier, * David M Koelle, * M Juliana McElrath & * Helen Horton * Department of Global Health Medicine, University of Washington, Seattle, Washington, USA. * David M Koelle, * M Juliana McElrath & * Helen Horton * Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA. * David M Koelle & * M Juliana McElrath * Benaroya Research Institute, Seattle, Washington, USA. * David M Koelle Contributions S.E. designed and performed all the experiments and wrote part of the manuscript. N.L. assisted S.E. to perform some of the experiments. W.L.D. performed statistical analysis and graphing design. K.J.L. performed epitope mapping for individuals infected with HSV. D.M.K. advised on the HSV experiment. D.M.K., K.J.L., M.J.M. and A.C.C. supplied samples from subjects. H.H. designed and supervised all of the research and wrote the manuscript. All authors revised and edited the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Helen Horton Author Details * Shokrollah Elahi Search for this author in: * NPG journals * PubMed * Google Scholar * Warren L Dinges Search for this author in: * NPG journals * PubMed * Google Scholar * Nicholas Lejarcegui Search for this author in: * NPG journals * PubMed * Google Scholar * Kerry J Laing Search for this author in: * NPG journals * PubMed * Google Scholar * Ann C Collier Search for this author in: * NPG journals * PubMed * Google Scholar * David M Koelle Search for this author in: * NPG journals * PubMed * Google Scholar * M Juliana McElrath Search for this author in: * NPG journals * PubMed * Google Scholar * Helen Horton Contact Helen Horton Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (4M) Supplementary Figures 1–6 and Supplementary Tables 1 and 2 Additional data
• Treg cells: patrolling a dangerous neighborhood
  - Nat Med 17(8):929-930 (2011)
  Article preview View full access options Nature Medicine | Article Foxp3+ follicular regulatory T cells control the germinal center response * Michelle A Linterman1, 2 * Wim Pierson3 * Sau K Lee2 * Axel Kallies4 * Shimpei Kawamoto5 * Tim F Rayner1 * Monika Srivastava2 * Devina P Divekar1 * Laura Beaton2 * Jennifer J Hogan2 * Sidonia Fagarasan5 * Adrian Liston3 * Kenneth G C Smith1, 6 * Carola G Vinuesa2, 6 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MedicineVolume: 17,Pages:975–982Year published:(2011)DOI:doi:10.1038/nm.2425Received12 January 2011Accepted27 June 2011Published online24 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * 日本語要約 * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Follicular helper (TFH) cells provide crucial signals to germinal center B cells undergoing somatic hypermutation and selection that results in affinity maturation. Tight control of TFH numbers maintains self tolerance. We describe a population of Foxp3+Blimp-1+CD4+ T cells constituting 10–25% of the CXCR5highPD-1highCD4+ T cells found in the germinal center after immunization with protein antigens. These follicular regulatory T (TFR) cells share phenotypic characteristics with TFH and conventional Foxp3+ regulatory T (Treg) cells yet are distinct from both. Similar to TFH cells, TFR cell development depends on Bcl-6, SLAM-associated protein (SAP), CD28 and B cells; however, TFR cells originate from thymic-derived Foxp3+ precursors, not naive or TFH cells. TFR cells are suppressive in vitro and limit TFH cell and germinal center B cell numbers in vivo. In the absence of TFR cells, an outgrowth of non–antigen-specific B cells in germinal centers leads to fewer antigen-spe! cific cells. Thus, the TFH differentiation pathway is co-opted by Treg cells to control the germinal center response. Figures at a glance * Figure 1: A proportion of CXCR5highPD-1highCD4+ cells express the transcription factor Foxp3. (,) After SRBC immunization, we identified Foxp3+ cells in the CXCR5highPD-1highCD4+ TFH compartment, and these cells follow the same kinetics as classic TFH cells. () Foxp3+ cells (red) are present within the Bcl6+ germinal center area (green) following SRBC immunization. Scale bar: left 100 μm; inset scale bar, 10 μm. () Heat map comparing the gene expression profiles of different CD4+ T-cell subsets from Foxp3gfp mice 7 d after immunization. Red, high gene expression; blue, low gene expression. We sorted the cells using the following markers, which, for simplicity, will be referred by the abbreviations in parentheses throughout: CD4+CD44lowFoxp3− naive (TN) cells, CD4+CD44highCXCR5int/lowPD-1int/lowFoxp3− effector/memory (TEM) cells, CD4+CD44intCXCR5int/lowPD-1int/lowFoxp3+ regulatory T cells (Treg), CD4+CXCR5highPD-1highFoxp3− T follicular helper (TFH) cells and CD4+CXCR5highPD-1highFoxp3+ follicular regulatory (TFR) cells. () Il21 and Il4 mRNA measured by quanti! tative PCR from sorted cells using the strategy described in normalized to Gapdh. The heights of the bars represent the mean, and the error bars represent the range of expression from three biological replicates. ND, gene expression was not detected; NS, not significant. () At left, the intracellular expression of CD40L as determined by flow cytometry in Treg (blue), TFH (green) and TFR (red) cell populations; the gray histogram represents a staining control from an immunized CD40L-deficient mouse. At right, Cxcl13 mRNA measured by quantitative RT-PCR as described in . () Cell surface expression of GITR, intracellular CTLA4 and CD25 in Treg (blue), TFH (green) and TFR (red) cell populations; gray histograms represent the isotype control. () Relative Gzmb and Gzma mRNA determined by quantitative RT-PCR as described in . () Percentage of CD103+ cells within the Treg, TFH and TFR populations; each symbol represents one mouse. () At left, cell surface expression of ICOS as dete! rmined by flow cytometry in Treg (blue), TFH (green) and TFR (! red) cell populations; the gray histogram represents the staining level of an isotype control. At right, Il10 mRNA detected by quantitative RT-PCR as described in . Flow cytometric and RT-PCR data are representative of at least three independent experiments. In –, we determined statistical significance using a one-way analysis of variance (ANOVA) analysis with Bonferroni's multiple testing correction. *P < 0.05, **P < 0.01, ***P < 0.001. Error bars represent the range of expression from three biological replicates. Rel, relative. * Figure 2: TFR cells require the same differentiation cues as TFH cells for their development. (–) Flow cytometric contour plots (,,) and dot plots of TFH (,,) and TFR (,,) cells in the groups of mice described below 7 d after SRBC immunization. (–) Mixed bone marrow chimeras generated by sub-lethally irradiating Rag2−/− mice and reconstituting their immune system with a 1:1 ratio of bone marrow cells from CD45.1 Cd28+/+ and CD45.2 Cd28−/− embryos or control CD45.1 Cd28+/+ and CD45.2 Cd28+/+ mice. (–) C57BL/6 (BL/6) and B cell–deficient μMT mice. (–) Sh2d1a+/+ and Sh2d1a−/− mice. Each symbol represents one mouse, and the horizontal bars represent the median values. All contour plots are gated on CD4+ cells; percentages shown are of total CD4+ cells. Figures represent one of three independent experiments with similar results. We determined statistical significance using a Mann-Whitney U test. *P < 0.05, **P < 0.01. * Figure 3: TFR cells express Bcl-6 and Blimp-1. () Bcl6 and Prdm1 mRNA normalized to Gapdh determined by quantitative RT-PCR from sorted cells using the strategy described in Figure 1d and Supplementary Figure 1. The heights of the bars represent the mean, and the error bars represent the range of expression from three biological replicates. We determined statistical significance using a one-way ANOVA analysis with Bonferroni's multiple testing correction. *P < 0.05, **P < 0.01, ***P < 0.001. The bar graphs are representative of three experiments. () Immunofluorescence of frozen spleen sections from mice immunized 7 d previously with SRBC. The germinal center is demarcated by the white dotted line in the three consecutive sections. Upper panel, AID (red) and CD3 (green); middle panel, Foxp3 (red) and Bcl-6 (green); lower panel, Foxp3 (red) and Blimp1 (green). Scale bars, 100 μm. Inset scale bars, 10 μm. () Flow cytometric contour plots of TFH (upper panels) and TFR (lower panels) cell formation in the draining (mediasti! nal) lymph node 10 d after intranasal influenza infection of mixed fetal liver chimeras reconstituted with a 1:1 ratio of fetal liver cells from embryonic day (E) 14.5 CD45.2 Prdm1gfp/gfp:CD45.1 Prdm1+/+ embryos, E14.5 CD45.2 Bcl6−/−:CD45.1 Bcl6+/+ embryos or control E14.5 CD45.2 Prdm1gfp/+:CD45.1 Prdm1+/+ embryos. Top graphs gated on CD4+CD45.2+CD44highFoxP3−; bottom graphs gated on CD4+CD45.2+CD44highFoxP3+. * Figure 4: TFR cells derive from Foxp3+ precursors. (–) Flow cytometric contour plots of splenic CD4+CXCR5highPD-1high cells () or CD4+ cells () 7 d after 1 × 105 transferred transgenic TCR3A9 HEL-specific CD45.1 T cells were adoptively transferred into congenically distinct CD45.2 B10.Br mice and immunized with HEL in alum. Flow cytometric contour plots of splenic CD4+CXCR5highPD-1high cells () or CD4+ cells () 7 d after adoptive transfer of 1 × 105 OT-II OVA-specific Thy1.2 T cells into congenically distinct Thy1.1 C57BL6 mice and immunization with OVA in alum. () Flow cytometric contour plots of splenic CD4+ T cells from CD45.1 C57BL/6 mice 7 d after adoptive transfer of 1 × 106 sorted naive CD4+CD44intFoxp3+ Treg (top) or CD4+CD44lowFoxp3− naive T cells (bottom) from unimmunized CD45.2 Foxp3gfp mice and KLH in Ribi immunization. Transferred CD45.2 cells are shown in red, and the endogenous CD45.1 cells are represented by the gray contour plots. Histograms show Foxp3-GFP expression in transferred CD45.2+CD4+CXCR5hig! hPD-1high cells. () Contour plots of splenic CD4+ T cells and quantification of TFR cells () from Foxp3DTR mice 6 d after SRBC immunization and administration of either 0.9% saline (top) or diphtheria toxin (DT) (lower panel). Histograms show Foxp3+ cells within the CD4+CXCR5highPD-1high compartment. () Flow cytometric contour plots of splenic CD4+ cells from Foxp3-Cre × ROSA-Stop-flox-YFP mice immunized 7 d previously with SRBC (left). Shown is an enumeration of the proportion of CD4+CXCR5highPD-1high cells that expressed YFP and/or Foxp3 (right). Each symbol represents one mouse, and the horizontal bars represent the median values. Figures are representative of two to four independent experiments. * Figure 5: TFR cells regulate the size of the TFH cell population. (,) Flow cytometric contour plots of splenic CD4+ cells () and splenic B220+ cells () and graphs of TFH cells () and germinal center B cells () from the spleens of Foxp3DTR mice immunized 8 d previously (d0) with SRBC. Five days after immunization, the mice were treated with either diphtheria toxin or saline. (–) Analysis of mixed bone marrow chimeras generated by sub-lethally irradiating Rag2−/− mice and reconstituting their immune system with either a 1:1 ratio of Sh2d1a−/− CD45.2:Foxp3DTR CD45.1 bone marrow or control Sh2d1a+/+ CD45.2:Foxp3DTR CD45.1 bone marrow. Eight weeks after reconstitution, we immunized chimeric mice with SRBC and treated them with 50 μg per kg of diphtheria toxin 1 d before immunization and 2 and 5 d after immunization. We analyzed splenocytes on day 8 for the proportion and total number of CD4+CXCR5highPD-1highFoxp3+ TFR cells (), CD4+Foxp3+ Treg cells (), CD4+CXCR5highPD-1high TFH cells () and B220+GL-7highCD95high germinal center B ce! lls (). Each symbol represents one mouse, and the horizontal bars represent the median values. We determined statistical significance using a Mann-Whitney U test. *P < 0.05, **P < 0.01. D, day; WT, wild type; KO, knockout. * Figure 6: TFR cells restrict the outgrowth of non–antigen-specific clones in the germinal center. (–) Flow cytometric contour plots of splenic B220+ cells () and graphs () of total GL-7+CD95+ germinal center B cells and () NP+ germinal center B cells 10 d after immunization of Foxp3WT and Foxp3DTR mice that were treated with diphtheria toxin 6 d after NP-KLH immunization. We performed statistical analyses using a Mann-Whitney U test. The experimental outline () of the immunization and diphtheria toxin or saline treatment scheme of Foxp3DTR mice (n = 8 per group) to examine the antigen-specific immunoglobulin response over time; we bled mice before immunization and 10, 15, 20 and 28 d after the primary immunization. We gave the mice a booster immunization 24 d after the primary immunization. () ELISA analysis of NP12 and NP2 antibodies in the experiment outlined in . Error bars, s.e.m. from eight individual mice from one experiment, representative of two experiments. We performed the statistical analyses in using a two-way ANOVA with a Bonferroni post-hoc test to compar! e differences at each time point. (–) Graphs and flow cytometric contour plots gated on splenic B220+ cells () and CD11c−Gr1− bone marrow cells () of NP+ germinal center B cells (), total GL-7+CD95+ germinal center B cells () and NP+ bone marrow plasma and memory cells (,) 21 d after NP-CGG immunization of chimeric mice generated by reconstituting Rag2−/− mice with a 1:1 mix of Sh2d1a−/−:Foxp3−/−, Sh2d1a+/+:Foxp3+/+, Sh2d1a+/+:Foxp3−/− and Sh2d1a−/−:Foxp3+/+ fetal liver. We performed the statistical analyses in – using a one-way ANOVA with Bonferroni post-hoc test correction. Each symbol represents one mouse, and the horizontal bars represent the median values. *P < 0.05, **P < 0.01. Unim, unimmunized; NS, not significant. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Kenneth G C Smith & * Carola G Vinuesa Affiliations * Cambridge Institute for Medical Research and the Department of Medicine, University of Cambridge School of Clinical Medicine, Addenbrooke's Hospital, Cambridge, UK. * Michelle A Linterman, * Tim F Rayner, * Devina P Divekar & * Kenneth G C Smith * John Curtin School of Medical Research, Australian National University, Canberra, Australian Capital Territory, Australia. * Michelle A Linterman, * Sau K Lee, * Monika Srivastava, * Laura Beaton, * Jennifer J Hogan & * Carola G Vinuesa * Vlaams Instituut voor Biotechnologie and Department of Experimental Medicine, Catholic University of Leuven, Leuven, Belgium. * Wim Pierson & * Adrian Liston * Department of Immunology, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia. * Axel Kallies * Laboratory for Mucosal Immunity, RIKEN Research Center for Allergy and Immunology, Tsurumi, Yokohama, Japan. * Shimpei Kawamoto & * Sidonia Fagarasan Contributions M.A.L. designed and performed experiments, analyzed the data and wrote the manuscript. W.P. performed experiments. S.K.L. performed experiments. A.K. contributed Blimp-1 chimera experiments and reviewed the manuscript. S.K. contributed confocal microscopy images. T.F.R. performed bioinformatic analyses. M.S. performed qRT-PCR experiments. D.P.D., L.B. and J.J.H. performed experiments. S.F. contributed confocal microscopy images and reviewed the manuscript. A.L. designed experiments and reviewed the manuscript. K.G.C.S. designed experiments, wrote the manuscript and supervised the study. C.G.V. designed experiments, wrote the manuscript and supervised the study. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Carola G Vinuesa or * Adrian Liston or * Kenneth G C Smith Author Details * Michelle A Linterman Search for this author in: * NPG journals * PubMed * Google Scholar * Wim Pierson Search for this author in: * NPG journals * PubMed * Google Scholar * Sau K Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Axel Kallies Search for this author in: * NPG journals * PubMed * Google Scholar * Shimpei Kawamoto Search for this author in: * NPG journals * PubMed * Google Scholar * Tim F Rayner Search for this author in: * NPG journals * PubMed * Google Scholar * Monika Srivastava Search for this author in: * NPG journals * PubMed * Google Scholar * Devina P Divekar Search for this author in: * NPG journals * PubMed * Google Scholar * Laura Beaton Search for this author in: * NPG journals * PubMed * Google Scholar * Jennifer J Hogan Search for this author in: * NPG journals * PubMed * Google Scholar * Sidonia Fagarasan Search for this author in: * NPG journals * PubMed * Google Scholar * Adrian Liston Contact Adrian Liston Search for this author in: * NPG journals * PubMed * Google Scholar * Kenneth G C Smith Contact Kenneth G C Smith Search for this author in: * NPG journals * PubMed * Google Scholar * Carola G Vinuesa Contact Carola G Vinuesa Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information Excel files * Supplementary Table 1 (373K) Differentially expressed genes in TFR cells PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–11, Supplementary Table 2 and Supplementary Methods. Additional data
• A ribosomal tactic to halt cancer
  - Nat Med 17(8):930-931 (2011)
  Article preview View full access options Nature Medicine | Article Regulation of the MDM2-P53 pathway and tumor growth by PICT1 via nucleolar RPL11 * Masato Sasaki1, 14 * Kohichi Kawahara2, 14 * Miki Nishio2 * Koshi Mimori3 * Ryunosuke Kogo3 * Koichi Hamada2 * Bunsho Itoh2 * Jia Wang2 * Yukako Komatsu2 * Yong Ryoul Yang2 * Hiroki Hikasa2 * Yasuo Horie4 * Takayuki Yamashita5 * Takehiko Kamijo6 * Yanping Zhang7 * Yan Zhu8 * Carol Prives8 * Toru Nakano9 * Tak Wah Mak10 * Takehiko Sasaki1, 11 * Tomohiko Maehama12 * Masaki Mori3, 13 * Akira Suzuki1, 2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MedicineVolume: 17,Pages:944–951Year published:(2011)DOI:doi:10.1038/nm.2392Received25 May 2010Accepted03 May 2011Published online31 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * 日本語要約 * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg PICT1 (also known as GLTSCR2) is considered a tumor suppressor because it stabilizes phosphatase and tensin homolog (PTEN), but individuals with oligodendrogliomas lacking chromosome 19q13, where PICT1 is located, have better prognoses than other oligodendroglioma patients. To clarify the function of PICT1, we generated Pict1-deficient mice and embryonic stem (ES) cells. Pict1 is a nucleolar protein essential for embryogenesis and ES cell survival. Even without DNA damage, Pict1 loss led to p53-dependent arrest of cell cycle phase G1 and apoptosis. Pict1-deficient cells accumulated p53, owing to impaired Mdm2 function. Pict1 binds Rpl11, and Rpl11 is released from nucleoli in the absence of Pict1. In Pict1-deficient cells, increased binding of Rpl11 to Mdm2 blocks Mdm2-mediated ubiquitination of p53. In human cancer, individuals whose tumors express less PICT1 have better prognoses. When PICT1 is depleted in tumor cells with intact P53 signaling, the cells grow more slowly a! nd accumulate P53. Thus, PICT1 is a potent regulator of the MDM2-P53 pathway and promotes tumor progression by retaining RPL11 in the nucleolus. Figures at a glance * Figure 1: Pict1 loss impairs survival of mouse embryos and ES cells. () Top, morphologies of representative Pict1+/+, Pict1+/− and Pict1−/− embryos at the E3.5 blastocyst stage and the E2.75 morula stage (after compaction). Bottom, TUNEL staining of Pict1+/+, Pict1+/− and Pict1−/− embryos at E3.5. +/+DNase, DNase-treated E3.5 Pict1+/+ embryos (positive control). DAPI, nuclear staining. Scale bar, 50 μm. () Top, semiquantitative RT-PCR of Pict1 mRNA in Pict1 ES cells treated for 24 h with doxycycline (Dox) as indicated. Actb, loading control. Bottom, MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt) assay of proliferation of Pict1 ES cells treated with Dox as indicated. Results are mean cell growth (A490) of three cultures per dose per time point. () Left, representative FACS profiles of Pict1 ES cells treated with or without Dox (5 ng ml−1) for 1, 2 or 3 d, stained with propidium iodide (PI), and analyzed by flow cytometry. Numbers indicate percentage of cells in G0/G1, S! or G2/M phase. Right, mean ± s.e.m. percentage of ES cells in G0/G1 phase (n = 5). *P < 0.01. () Left, representative FACS profile of Pict1 ES cells treated with or without Dox (5 ng ml−1) for 2, 3 or 4 d, stained with TUNEL and analyzed by FACS. Right, mean ± s.e.m. percentage of TUNEL+ ES cells (n = 5). *P < 0.01. Results represent four trials. * Figure 2: Effects of Pict1 deficiency are p53 dependent. () Immunoblot detecting the indicated proteins in Pict1 ES cells treated with or without 5 ng ml−1 doxycycline (Dox). () Immunoblot detecting p53 and Pict1 proteins in Pict1 ES cells treated with Dox. Actin, loading control. () Left, immunoblot detecting p53 protein and DNA damage (pγH2ax) in Pict1 ES cells treated with or without Dox (5 ng ml−1) or UV irradiation (80 J m−2). Right, immunoblot of Pict1 ES cells treated with Dox (5 ng ml−1, 48 h), UV irradiation (80 J m−2, 6 h) or both (final 6 h for UV). () Pict1 ES cells were transfected with scramble siRNA, Trp53 siRNA A or Trp53 siRNA B for 24 h and cultured with or without 5 ng ml−1 Dox for 2 d () or 4 d (). Left, FACS profiles of percentage of cells in each cell cycle phase () and TUNEL+ cells (). Right, mean ± s.e.m. (n = 5) percentage of G0–G1 phase () and TUNEL+ () ES cells. *P < 0.01. () Top, gross appearance of thymi from mice of the indicated genotypes (5 weeks old). Bottom, mean total thymocytes �! � s.e.m. from these thymi (n = 5). *P < 0.01. Scale bar, 5 mm. Results represent three trials. * Figure 3: Pict1 deficiency inhibits Mdm2 function. () Northern blot detecting indicated mRNAs in Pict1 ES cells treated for 48 h with Dox. () Immunoblot detecting p53 and Pict1 in Pict1 ES cells treated for 48 h with or without 5 ng ml−1 Dox and with or without cycloheximide (CHX; 100 μg ml−1). () Immunoblot detecting p53 in Pict1 ES cells treated for 36 h with or without 5 ng ml−1 Dox, with or without MG132 (20 μM). () Immunoblot of H1299 cells transfected with the indicated plasmids and treated with MG132 (20 μM). Lysates were immunoprecipitated and immunoblotted with antibodies to HA (ubiquitin, Ub) and Myc (ubiquitinated p53). () Immunoblot of Pict1 ES cells transfected with scramble siRNA or Mdm2 siRNA (siMdm2) and treated with or without 5 ng ml−1 Dox for 48 h. MG132 (20 μM) was added for 3 h before lysis. The p53 protein level in each sample was adjusted to equality before immunoprecipitation with antibody to p53 or to ubiquitin. () Pict1 ES cells were transfected with scramble siRNA or the indicated siRNA! s and treated with or without 5 ng ml−1 Dox for 24 h. Top, immunoblot detecting indicated proteins. Bottom, quantification of ratio of p53 to actin using LAS Image Analyzer with Multi Gauge Software. () Immunoblot detecting indicated proteins in Pict1 ES cells treated with or without 5 ng ml−1 Dox for 48 h. Results represent three trials. * Figure 4: Pict1 regulates Mdm2 by binding to nucleolar Rpl11. () Immunoblot detecting indicated proteins in cytoplasmic, nuclear and nucleolar fractions (30 μg) of Pict1 ES cells treated for 1 or 2 d with or without 5 ng ml−1 Dox. Nucleostemin (Nsm), lamin and tubulin, localization controls. () Immunoblot detecting the indicated proteins in Pict1 ES cells transfected with vehicle (No), scramble siRNA, Trp53 siRNA (positive control) or siRNAs against the indicated ribosomal proteins and treated with or without 5 ng ml−1 Dox for 24 h. () Immunoblot of untreated Dox− ES cells immunoprecipitated and immunoblotted with antibodies to Pict1 and Rpl11, respectively. () Confocal microscopy of Pict1 ES cells transfected with plasmid encoding RPL11-DsRed and treated with or without 5 ng ml−1 Dox for 24 h or 48 h. Endogenous nucleophosmin (Npm) was detected using antibody to Npm (green). Cell fluorescence at 24 h is in , and percentages of cells retaining RPL11 in the nucleolus at 24 h and 48 h is graphed in (). Scale bars, 5 μm. () Conf! ocal microscopy of Pict1 ES cells transfected with plasmid encoding RPL11-DsRed and treated with or without 5 ng ml−1 Dox for 48 h. Endogenous Mdm2 was detected with antibody to Mdm2 (green). Scale bars, 5 μm. () Immunoblot of cytoplasmic and nuclear fractions of Pict1 ES cells treated with or without 5 ng ml−1 Dox for 2 d. Rpl11 was quantified by immunoblotting and the Rpl11 protein level in each sample was adjusted to equality before immunoprecipitation with antibody to Rpl11. Lysates were immnoprecipitated with control IgG or antibody to Rpl11 followed by immunoblotting to detect Mdm2. Results represent three trials. * Figure 5: Reduced cancer growth and better survival with low PICT1. () Pict1+/+ and Pict1+/− mice treated with DMBA plus TPA were monitored for papillomagenesis for 22 weeks. Left, gross tumor appearance. Scale bars, 2 mm. Middle, number of papillomas per mouse at 22 weeks (mean ± s.e.m., *P < 0.05). Right, incidence and diameter of papillomas at the indicated number of weeks after TPA. () Human glioma cell lines DBTRG-05MG and D247, colorectal cancer cell lines Lovo and RKO, and ovarian cancer cell line RMG-1 (all WT TP53) were treated with scramble shRNA or shRNA against PICT1 (PICT1-1 and PICT1-2). Top, MTS assay of growth inhibition. Bottom, immunoblot detecting indicated proteins. Results represent three trials. () Left, Kaplan-Meier survival curves for 181 individuals with colorectal cancer and 81 individuals with esophageal cancer whose tumors showed low PICT1 mRNA (blue) or high PICT1 mRNA (orange). Middle, Kaplan-Meier curves for 67 individuals with colorectal cancer and 45 individuals with esophageal cancer whose tumors showed W! T TP53 and high or low PICT1 mRNA. Right, Kaplan-Meier curves for 45 individuals with colorectal cancer and 34 individuals with esophageal cancer whose tumors showed mutated TP53 and high or low PICT1 mRNA. * Figure 6: PICT1 binding to nucleolar RPL11 regulates MDM2-P53 activity. Model of PICT1 function. Left, when PICT1 is present in the nucleolus, RPL11 is retained in the nucleolus and MDM2 is free to ubquitinate P53, promoting its degradation. Right, when PICT1 is absent, nucleolar RPL11 escapes into the nucleoplasm and binds to MDM2, blocking its ubiquitination of P53. As a result, P53 accumulates in PICT1-deficient cells. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Masato Sasaki & * Kohichi Kawahara Affiliations * Global Centers of Excellence Program, Akita University Graduate School of Medicine, Akita, Japan. * Masato Sasaki, * Takehiko Sasaki & * Akira Suzuki * Division of Cancer Genetics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan. * Kohichi Kawahara, * Miki Nishio, * Koichi Hamada, * Bunsho Itoh, * Jia Wang, * Yukako Komatsu, * Yong Ryoul Yang, * Hiroki Hikasa & * Akira Suzuki * Division of Molecular and Surgical Oncology, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan. * Koshi Mimori, * Ryunosuke Kogo & * Masaki Mori * Department of Gastroenterology, Akita University Graduate School of Medicine, Akita, Japan. * Yasuo Horie * Laboratory of Molecular Genetics, Institute for Molecular and Cellular Regulation, Gunma University, Maebashi, Japan. * Takayuki Yamashita * Division of Biochemistry and Molecular Carcinogenesis, Chiba Cancer Center Research Institute, Chiba, Japan. * Takehiko Kamijo * Department of Radiation Oncology and Lineberger Comprehensive Cancer Center, Chapel Hill, North Carolina, USA. * Yanping Zhang * Department of Biological Sciences, Columbia University, New York, New York, USA. * Yan Zhu & * Carol Prives * Department of Pathology, Osaka University, Suita, Japan. * Toru Nakano * The Campbell Family Institute for Cancer Research, University Health Network, Toronto, Ontario, Canada. * Tak Wah Mak * Department of Medical Biology, Akita University Graduate School of Medicine, Akita, Japan. * Takehiko Sasaki * Department of Biochemistry and Cell Biology, Japan National Institute of Infectious Diseases, Tokyo, Japan. * Tomohiko Maehama * Department of Gastroenterological Surgery, Medical School and Graduate School of Frontier Biosciences, Osaka University, Suita, Japan. * Masaki Mori Contributions M.S. carried out the initial generation and analyses of Pict1flox mice and Pict1 ES cells. K.K. carried out subsequent major biochemical and biological experiments, and M.N. carried out mouse work. K.M., R.K. and M.M. carried out the human cancer tissue analyses. K.H. generated Pict1−/− mice. B.I. assisted with confocal microscopy. J.W., Y.K. and Y.R.Y. assisted with the introduction of shRNA into human cancer cell lines. H.H. assisted with the protein binding assays. Y.H. carried out mouse analyses. T.Y., T.K., Y. Zhang, Y. Zhu, C.P. and T.W.M. provided key materials. T.M., K.M. and A.S. conceived of the project, and M.S., K.K., K.M, T.M., M.M. and A.S. designed the experiments. M.S., K.K., M.N., K.M., R.K., T.Y., T.K., Y. Zhang, C.P., T.N., T.W.M., T.S., T.M., M.M. and A.S. discussed the hypothesis and interpreted the data. A.S. coordinated and directed the project and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Akira Suzuki or * Masaki Mori Author Details * Masato Sasaki Search for this author in: * NPG journals * PubMed * Google Scholar * Kohichi Kawahara Search for this author in: * NPG journals * PubMed * Google Scholar * Miki Nishio Search for this author in: * NPG journals * PubMed * Google Scholar * Koshi Mimori Search for this author in: * NPG journals * PubMed * Google Scholar * Ryunosuke Kogo Search for this author in: * NPG journals * PubMed * Google Scholar * Koichi Hamada Search for this author in: * NPG journals * PubMed * Google Scholar * Bunsho Itoh Search for this author in: * NPG journals * PubMed * Google Scholar * Jia Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Yukako Komatsu Search for this author in: * NPG journals * PubMed * Google Scholar * Yong Ryoul Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Hiroki Hikasa Search for this author in: * NPG journals * PubMed * Google Scholar * Yasuo Horie Search for this author in: * NPG journals * PubMed * Google Scholar * Takayuki Yamashita Search for this author in: * NPG journals * PubMed * Google Scholar * Takehiko Kamijo Search for this author in: * NPG journals * PubMed * Google Scholar * Yanping Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Yan Zhu Search for this author in: * NPG journals * PubMed * Google Scholar * Carol Prives Search for this author in: * NPG journals * PubMed * Google Scholar * Toru Nakano Search for this author in: * NPG journals * PubMed * Google Scholar * Tak Wah Mak Search for this author in: * NPG journals * PubMed * Google Scholar * Takehiko Sasaki Search for this author in: * NPG journals * PubMed * Google Scholar * Tomohiko Maehama Search for this author in: * NPG journals * PubMed * Google Scholar * Masaki Mori Contact Masaki Mori Search for this author in: * NPG journals * PubMed * Google Scholar * Akira Suzuki Contact Akira Suzuki Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (709K) Supplementary Figures 1–8 and Supplementary Methods Additional data
• Alzheimer's therapy: a BACE in the hand?
  - Nat Med 17(8):932-933 (2011)
  Article preview View full access options Nature Medicine | Community Corner Alzheimer's therapy: a BACE in the hand? Journal name:Nature MedicineVolume: 17,Pages:932–933Year published:(2011)DOI:doi:10.1038/nm0811-932Published online04 August 2011 Pasieka/Photo Researchers, Inc. With the continued increase in human lifespan, the incidence of Alzheimer's disease is rising, prompting a need for innovative therapies that can slow or stop the progression of this devastating condition. Since the discovery of the β-amyloid precursor protein site cleaving enzyme (BACE), which initiates the production of the Alzheimer's associated peptide Aβ, it has been one of the most intensely investigated Alzheimer's disease targets. Now, Ryan Watts and his colleagues at Genentech have used a bi-specific antibody approach to target this enzyme, which allows transport of the therapeutic antibody across the blood-brain barrier (BBB)1, 2. The bi-specific antibody reduced the levels of brain Aβ more effectively than a monospecific antibody to BACE1, and this targeting approach could potentially even be applied to treat other neurological diseases. We asked three experts to comment on the implications of this study for Alzheimer's therapy. Sam Gandy Recently, in a tour-de-force duo of papers, Ryan Watts and colleagues have delivered advances in the two diverse areas of BACE inhibition and therapeutic delivery of biologicals across the BBB1, 2. First, they described a neutralizing antibody against BACE1 with powerful Aβ-lowering actions1. This is especially welcome, as pharmacological BACE inhibition, long stymied by the challenges presented by its large catalytic site, has not yet survived a phase 1 randomized human clinical trial. In addition, an antibody-based approach typically has the advantage of much greater specificity than that of small molecules. Delivery to the CNS would normally be a potential roadblock, but the authors circumvent this in their second paper by exploiting a transcytosis motif, thus enhancing delivery of BACE1-specific antibody across the BBB2. "The best hope for Aβ-lowering interventions is probably as prophylaxis and not as therapy." This is all good news, but it would be more positive if the experience with Aβ-lowering agents were faring better. Lilly's γ-secretase inhibitor failed in a phase 2 clinical trial last summer because it unexpectedly enhanced cognitive decline7. Bapineuzumab, the Pfizer/Johnson&Johnson monoclonal antibody against Aβ, continues plugging away in phase 2, after an initial 18-month endpoint that failed to establish clinical benefit despite a mild reduction in the burden of fibrillar amyloid8. With the discovery that Aβ accumulation can precede clinical symptoms by 10–20 years, the best hope for Aβ-lowering interventions is probably as prophylaxis and not as therapy for symptomatic patients. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Competing financial interests S.G. is a grantee from Amicus Pharmaceuticals and a data and safety monitoring board member of Pfizer/Johnson&Johnson Alzheimer Immunotherapy Alliance. Additional data
• miRNAs in the spotlight: Making 'silent' mutations speak up
  - Nat Med 17(8):934-935 (2011)
  Nature Medicine | Between Bedside and Bench miRNAs in the spotlight: Making 'silent' mutations speak up * David W Salzman1 * Joanne B Weidhaas1 * Affiliations * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:934–935Year published:(2011)DOI:doi:10.1038/nm0811-934Published online04 August 2011 Genetic mutations can cause numerous diseases. These alterations affect not only protein-coding genes but also regions that were until recently thought to be trivial in disease. In 'Bedside to Bench', David Salzman and Joanne Weidhaas examine a human study showing how a silent mutation impairs the binding of miR-196, increasing the risk for Crohn's disease. Therefore, alterations of miRNA target sites as pathogenic mechanism begs further investigation. miRNAs themselves can also be the root of disease. In 'Bench to Bedside', Carlo Croce peruses a study in vivo showing evidence of tumor addiction to miR-21 in a mouse model of cancer, which highlights the role of miRNAs as initiators of disease. Targeting these drivers will help to develop effective drugs. View full text Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * David W. Salzman and Joanne B. Weidhaas are at the Yale University School of Medicine Department of Therapeutic Radiology, New Haven, Connecticut, USA. Competing financial interests J.B.W. is co-inventor on several patents and is the founder of a company, miraDx. Corresponding author Correspondence to: * Joanne B Weidhaas Author Details * David W Salzman Search for this author in: * NPG journals * PubMed * Google Scholar * Joanne B Weidhaas Contact Joanne B Weidhaas Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• miRNAs in the spotlight: Understanding cancer gene dependency
  - Nat Med 17(8):935-936 (2011)
  Article preview View full access options Nature Medicine | Between Bedside and Bench miRNAs in the spotlight: Understanding cancer gene dependency * Carlo M Croce1Journal name:Nature MedicineVolume: 17,Pages:935–936Year published:(2011)DOI:doi:10.1038/nm0811-935Published online04 August 2011 Bench to bedside Most human cancers are driven by somatic genetic alterations, which often involve oncogenes and tumor suppressor genes1. For example, chromosome translocations involving the MYC oncogene on chromosome 8 and one of three immunoglobulin loci dysregulate the MYC oncogene, leading to the development of Burkitt's lymphoma1. The BCR-ABL fusion gene resulting from the Philadelphia chromosome causes elevation of the activity of the Abl tyrosine kinase and is responsible for chronic myelogenous leukemia (CML)1. Because such driver gene alterations are essential for tumor cell growth, survival or both, their reversion can lead to selective death of cancer cells1. Specific drugs, such as imatinib in the case of CML, can target the consequences of such genetic alterations2. Treatment with imatinib leads to complete remission in more than 95% of patients with CML in the chronic phase with few side effects2, indicating that targeting the activated Abl tyrosine kinase can selectively result in the death of cancer cells with considerable benefit for the patients. Given that the malignancy is caused by the expression of the BCR-ABL fusion gene, the results suggest that reverting cancer 'drivers' can lead to tumor regression and possibly cure. The expression of additional cancer genes can be altered during tumor progression and can contribute to tumor growth and spreading; therefore, targeting these additional alterations may have some effect. But such alterations may not be present in every cell within a tumor. Another possibility is that cooperation of cancer genes may be required for or may speed up tumorigenicity in some tumors. In this case, targeting several of them may be beneficial. Yet, as most tumors initiate from one cell (monoclonal)1, it is quite likely that the initial alteration, which is present in 100% of the cells of a given tumor, is the crucial target. During tumor progression, however, numerous genes can become mutated, making the tumor less dependent on the initial genetic change. For example, CML can progress to an acute leukemia that is more resistant to imatinib treatment2. As recently as the start of this decade, all cancer-associated genes, oncogenes and tumor suppressors were thought to be protein-coding genes. Yet, in 2002, a study showed that alterations in miRNA genes, which regulate gene expression by targeting mRNA and blocking its translation, causing its degradation or both, could also lead to malignancy3. In fact, the loss of miR-15a and miR-16-1 was found as the most common alteration in human chronic lymphocytic leukemia (CLL)3. Further studies indicated that many miRNA genes map precisely to regions of the human genome that are consistently altered, for example, by deletion or gene amplification, in a large variety of human cancers, including lung cancer and lymphoma4. For instance, the members of the let-7 family of miRNAs mapping to chromosome regions involved in deletions in multiple human cancers have been shown to target the oncogene RAS (ref. 5). In addition, miR-15a and miR-16-1, which are lost in CLL, target and downregulate the expression of the BCL2 oncogene, which is overexpressed in CLL6. This evidence indicates that loss of these miRNA results in the constitutive overexpression of the targeted oncogenes and contributes to malignant transformation. Another miRNA, miR-155, was found to be overexpressed and often amplified in the activated B cell (ABC) form of human diffuse large B cell lymphoma7. Transgenic mice in which the overexpression of miR-155 was specifically targeted to B cells developed an acute lymphoblastic leukemia or high-grade lymphoma, suggesting that dysregulation of a single miRNA gene can cause cancer in mice and humans8. Given that the development of the malignancy took a few months, it seems possible that additional genetic or epigenetic changes may be necessary for full malignant transformation. In 2004, profiling of expression of miRNAs in human glioblastoma multiforme indicated that another miRNA, miR-21, is highly overexpressed in this tumor type9. Further investigations showed that miR-21 is the most commonly dysregulated miRNA in a variety of human tumors, including leukemias and solid cancers, suggesting that this miRNA could function as an oncogene in many types of human malignancies10. In a recent study, Medina et al.11 presented in vivo evidence of tumor addiction—dependency—to miR-21 in a mouse model of lymphoma. The authors overexpressed miR-21 in a Cre- and doxycycline-dependent manner using the Rosa26 locus (miR-21LSL-Tetoff). miR-21 was overexpressed in tissues where nestin is expressed, including the hematopoietic component, and its expression could be silenced upon doxycycline treatment. Interestingly, these mice in the absence of doxycycline developed clinical signs of aggressive lymphomas, including spenomegaly and severe lymphadenopathy, and disruption of the normal tissue architecture of the spleen and thymus by invasive malignant B cells11. Tumors from miR-21LSL-Tetoff mice were transplantable into immunodeficient nonobese diabetic, severe combined immunodeficient mice, confirming their fully malignant nature11. These findings indicated that, in the context of B cells, upregulation of miR-21 leads to an aggressive malignancy and that such ! dysregulation is the initial and causal event in cancer development. The tumors in miR-21LSL-Tetoff mice not exposed to doxycycline were found to be monoclonal or oligoclonal, which suggests that additional epigenetic and genetic changes might be required for malignancy1. But the miR-21LSL-Tetoff mice also showed that tumors continued to be dependent on the overexpression of miR-21, the driver. In fact, administering DOX to these mice bearing advanced lymphomas caused silencing of miR-21 overexpression, and, consequently, rapid regression of the B cell tumors. Increasing evidence is showing that dysregulation of a single miRNA, such as miR-21, can cause malignant tumors. Notably, those tumors remained dependent on the overexpression of miR-21—the driver—and when the initiator or driver was shut off, the tumors regressed11. The striking results in the treatment of patients with CML with imatinib, and those obtained in the context of a malignancy driven (initiated) by miRNA dysregulation, such as the case of miR-21, clearly indicate that targeting the initiators of malignant transformation should be a priority (Fig. 1). Targeting other alterations occurring during the progression of malignancy might not be as useful. Figure 1: miRNAs targeting oncogenes and tumor suppressors as cancer drivers. In human malignancies, mRNAs can be overexpressed (miR-155 and miR-21) or lost (for example, miR-15a and miR-16-1). Their role in human cancer as cancer drivers can be validated in mouse models. New cancer therapeutics may include miRNAs and antimiRNAs to target early cancer events. Katie Vicari * Full size image (73 KB) Unfortunately, for most of the pharmaceutical industry a cancer target is a cancer target, independently of its role in tumor development. It is doubtful that targeting players that are involved in one of the multiple steps of tumor progression will have the same efficacy as targeting early events, possibly the initiation events, leading to cancer. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Carlo M. Croce is in the Department of Molecular Virology, Immunology and Medical Genetics, The Ohio State University School of Medicine, Columbus, Ohio, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Carlo M Croce Author Details * Carlo M Croce Contact Carlo M Croce Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Research highlights
  - Nat Med 17(8):938-939 (2011)
  Article preview View full access options Nature Medicine | Research Highlights Research highlights Journal name:Nature MedicineVolume: 17,Pages:938–939Year published:(2011)DOI:doi:10.1038/nm0811-938Published online04 August 2011 Cancer: Breast cancer mans up Breast tumors often rely on hormonal signaling for their growth, and are thought mainly to be driven by estrogen. However, some breast tumors do not express estrogen receptors, and some express the androgen receptor (AR) instead. How androgen signaling can foster breast cancer is starting to be unraveled, and a recent report (Cancer Cell, 119–131) suggests it may be more entwined with classical breast tumor–driving pathways than we thought. Similarly to other hormones, androgens lead to profound reprogramming of gene expression, but the specific effects depend on the cell type. The authors surveyed the gene expression program induced by AR stimulation in breast cancer cells and found that it overlaps with the effects of increased signaling by HER2, a breast cancer oncoprotein. Ni et al. elucidated the molecular pathway that links AR stimulation and HER2 signaling, which includes the intermediary activation of Wnt signaling by AR and the cooperation between downstream effectors of Wnt and AR to increase the expression of the HER2-related receptor HER3. Interestingly, this report further suggests that androgen antagonists, which are frequently used in prostate cancer, could be a feasible treatment option for breast tumors, as they may stop the tumor-fostering cross talk between hormonal and growth receptor signaling. —VA Infection: Bacterial protection Infection with the gastric bacterial pathogen Helicobacter pylori has previously been inversely correlated with asthma incidence in epidemiological studies. A new study provides insight into how this bacterium can protect against asthma and adds support to the hypothesis that loss of the microbiota contributes to the rise of allergic disease in modern societies. Isabelle C. Arnold et al. (J. Clin. Invest. doi:10.1172/JCI45041) found that infecting mice with H. pylori significantly reduced airway hyper-responsiveness, inflammation and inflammatory cell infiltration on subsequent airway allergen challenge. This protection from asthma pathology was most efficient when the mice were infected neonatally with the pathogen, and it could be eliminated by antibiotic treatment. Previously, H. pylori infection has been shown to elicit regulatory T (Treg) cell responses, and Arnold et al. now show that H. pylori infection leads to pulmonary infiltration of Treg cells in their allergic model. Treg depletion abrogated the protective effect and adoptively transferred Treg cells conferred protection to uninfected, allergen-challenged mice. Although the detailed mechanism by which Treg cells mediate this protection remains to be worked out, the authors suggest that the Treg cells may maintain lung-infiltrating dendritic cells in a partially mature state and thus prevent them from activating T cells. —MS Metabolism: Replacing broken parts Promoting the generation of new mitochondria may be therapeutically beneficial in various metabolic disorders, according to Carlo Viscomi et al. (Cell Metab., 80–90). Mitochondrial dysfunction is central to many genetic diseases of metabolism that often affect the heart and brain. Although repairing the affected gene may be beneficial, replacing the whole mitochondrion might also work. Indeed, there is already evidence that promoting mitochondrial biogenesis improves function in cells from metabolic patients and clinical phenotypes in vivo. Now Viscomi et al. extend these observations in three mouse models of metabolic disease characterized by defective cytochrome oxidase activity. They found that overexpressing PGC-1α, a master regulator of mitochondrial biogenesis, improved clinical outcomes in the mice. Mechanistically, the beneficial effect depended on AMPK, a kinase upstream of PGC-1α, as an AMPK agonist also improved disease phenotypes. PGC-1α effects seemed independent of the transcriptional coactivator PPARγ—a remarkable result because previous therapeutic attempts to promote mitochondrial biogenesis have shown that this molecule contributes to improved metabolic phenotypes. Here, a PPARγ agonist actually worsened disease. Although the authors have no definitive explanation for this difference between their results and earlier work, physicians should cautiously proceed with the use of PPARγ agonists to treat mitochondrial diseases, as this strategy is already being tested for some conditions. —JCL Immunology: A miRNA mediator of arthritis Recently, a number of miRNAs, including miR-155, have been identified that are differentially regulated in the autoimmune disease arthritis, but the functional pathways through which these molecules might mediate inflammation have not been studied in depth. Now miR-155 is shown to be an important inflammatory regulator in arthritis, suggesting that it might be a potential therapeutic target for this disease. Synovial inflammation is a characteristic feature of arthritis, and Iain B. McInnes and colleagues (PNAS, 11193–11198) now show that miR-155 expression is increased in synovial membrane and fluid macrophages from people with rheumatoid arthritis. miR-155 overexpression in CD14+ macrophages led to the production of rheumatoid arthritis–associated chemokines and cytokines such as TNF-a and interleukin-6; conversely, the expression of a miR-155 inhibitor in rheumatoid arthritis synovial macrophages inhibited TNF-a production. The authors narrowed in on the enzyme SHIP-1, a miR-155 target in myeloid cells and an inhibitor of several inflammatory pathways, showing that miR-155 overexpression in CD14+ cells reduced SHIP-1 mRNA expression and that SHIP-1 was downregulated in rheumatoid arthritis synovial CD14+ cells. The authors then found that miR-155 deficient mice are resistant to collagen-induced arthritis, consistent with a recent study by Bluml et al. (Arthritis Rheum., 1281–1288), and they suggest that miR-155 is important for the development of arthritis through its effects on inflammatory cytokines. Despite the importance of the miR-155–SHIP-1 axis in arthritis discovered here, further studies will be required to ascertain whether other miR-155–regulated targets have a role in arthritis pathology, as miRNAs can act on several targets to mediate their downstream effects. —MS Therapy: Blue light special The ability to turn on expression of a therapeutic protein in vivo simply by shining a light sounds a bit far-fetched, but a recent report from Haifeng Ye et al. shows how this might be achieved (Science, 1565–1568). The authors exploited the retinal photopigment melanopsin, which when illuminated by blue light, triggers an increase in the concentration of intracellular calcium. Forced expression of melanopsin in cultured human kidney cells also increased calcium levels, which in turn activated the transcription factor NFAT. When the melanopsin-expressing cells were implanted under the skin of mice, a light source in the ceiling of their cages could trigger expression of a gene placed downstream of an NFAT regulatory element. The researchers then engineered the implanted cells to express the insulin-stimulatory protein GLP-1. In a mouse model of diabetes, light-induced expression of GLP-1 increased insulin levels and improved glucose handling, a first step in demonstrating the therapeutic potential of this type of implantable bioreactor. —MB Epigenetics: On the ataxia Spinocerebellar ataxia 7 (SCA7) differs from most other forms of the inherited neurodegenerative disease in that visual problems, rather than loss of motor control, are generally the earliest signs of the disease. But one thing SCA7 might share with other trinucleotide disorders is an intricate epigenetic regulation of bidirectional transcription that may be involved in driving disease pathology. SCA7 is caused by the expansion of an unstable CAG repeat in the third exon of the gene encoding ataxin-7. Previous studies had shown that the repeat region and the start site of translation are flanked by binding sites for a transcription factor called CTCF. But by further probing the gene sequence, Sopher et al. discovered an alternative promoter and antisense noncoding RNA, which they called SCAANT1—short for spinocerebellar ataxia-7 antisense noncoding transcript 1 (Neuron, 1071–1084). The researchers put ataxin-7–encoding minigenes into mice, and showed that CTCF binding promotes the production of SCAANT1, which in turn represses transcription at the newly discovered promoter. In mice lacking SCAANT1, however, the alternate ataxin-7 gene was expressed, leading to the mouse equivalent of SCA7. By showing that fibroblasts and white blood cells taken from people with SCA7 lack SCAANT1 expression, the scientists further implicated loss of regulation by this antisense RNA in the disease process. —ED Immunology: Choking off T cells Steve Gschmeissner / Photo Researchers, Inc. The transcription factor hypoxia-inducible factor 1-α (HIF1-α) is now shown to influence T cell differentiation and recruitment. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Medicine for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data
• Variants at 6q21 implicate PRDM1 in the etiology of therapy-induced second malignancies after Hodgkin's lymphoma
  - Nat Med 17(8):941-943 (2011)
  Nature Medicine | Brief Communication Variants at 6q21 implicate PRDM1 in the etiology of therapy-induced second malignancies after Hodgkin's lymphoma * Timothy Best1 * Dalin Li2 * Andrew D Skol3 * Tomas Kirchhoff4 * Sarah A Jackson3 * Yutaka Yasui5 * Smita Bhatia6 * Louise C Strong7 * Susan M Domchek8 * Katherine L Nathanson8 * Olufunmilayo I Olopade3 * R Stephanie Huang3 * Thomas M Mack2, 9 * David V Conti2 * Kenneth Offit4 * Wendy Cozen2, 9 * Leslie L Robison10 * Kenan Onel1, 11 * Affiliations * Contributions * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:941–943Year published:(2011)DOI:doi:10.1038/nm.2407Received11 January 2011Accepted24 May 2011Published online24 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Survivors of pediatric Hodgkin's lymphoma are at risk for radiation therapy–induced second malignant neoplasms (SMNs). We identified two variants at chromosome 6q21 associated with SMNs in survivors of Hodgkin's lymphoma treated with radiation therapy as children but not as adults. The variants comprise a risk locus associated with decreased basal expression of PRDM1 (encoding PR domain containing 1, with ZNF domain) and impaired induction of the PRDM1 protein after radiation exposure. These data suggest a new gene-exposure interaction that may implicate PRDM1 in the etiology of radiation therapy-induced SMNs. View full text Author information * Abstract * Author information * Supplementary information Affiliations * Committee on Cancer Biology, University of Chicago, Chicago, Illinois, USA. * Timothy Best & * Kenan Onel * Department of Preventive Medicine, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA. * Dalin Li, * Thomas M Mack, * David V Conti & * Wendy Cozen * Department of Medicine, University of Chicago, Chicago, Illinois, USA. * Andrew D Skol, * Sarah A Jackson, * Olufunmilayo I Olopade & * R Stephanie Huang * Department of Medicine, Clinical Genetics Service, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. * Tomas Kirchhoff & * Kenneth Offit * Department of Public Health Sciences, University of Alberta, Edmonton, Alberta, Canada. * Yutaka Yasui * Department of Population Sciences, City of Hope, Duarte, California, USA. * Smita Bhatia * Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA. * Louise C Strong * Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA. * Susan M Domchek & * Katherine L Nathanson * Department of Pathology, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA. * Thomas M Mack & * Wendy Cozen * Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee, USA. * Leslie L Robison * Department of Pediatrics, University of Chicago, Chicago, Illinois, USA. * Kenan Onel Contributions T.B. and K. Onel designed the study and wrote the manuscript with substantial contributions from A.D.S., Y.Y., S.B., L.C.S., R.S.H., T.M.M., D.V.C., K. Offit, W.C. and L.L.R.; T.B. performed the experiments and undertook the analysis; D.L., A.D.S., T.K., and Y.Y. performed data analysis; S.A.J., S.M.D., K.L.N., O.I.O., W.C. and L.L.R. provided clinical samples and performed analysis of subject data; K. Onel directed the project. All authors contributed to the final manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Kenan Onel Author Details * Timothy Best Search for this author in: * NPG journals * PubMed * Google Scholar * Dalin Li Search for this author in: * NPG journals * PubMed * Google Scholar * Andrew D Skol Search for this author in: * NPG journals * PubMed * Google Scholar * Tomas Kirchhoff Search for this author in: * NPG journals * PubMed * Google Scholar * Sarah A Jackson Search for this author in: * NPG journals * PubMed * Google Scholar * Yutaka Yasui Search for this author in: * NPG journals * PubMed * Google Scholar * Smita Bhatia Search for this author in: * NPG journals * PubMed * Google Scholar * Louise C Strong Search for this author in: * NPG journals * PubMed * Google Scholar * Susan M Domchek Search for this author in: * NPG journals * PubMed * Google Scholar * Katherine L Nathanson Search for this author in: * NPG journals * PubMed * Google Scholar * Olufunmilayo I Olopade Search for this author in: * NPG journals * PubMed * Google Scholar * R Stephanie Huang Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas M Mack Search for this author in: * NPG journals * PubMed * Google Scholar * David V Conti Search for this author in: * NPG journals * PubMed * Google Scholar * Kenneth Offit Search for this author in: * NPG journals * PubMed * Google Scholar * Wendy Cozen Search for this author in: * NPG journals * PubMed * Google Scholar * Leslie L Robison Search for this author in: * NPG journals * PubMed * Google Scholar * Kenan Onel Contact Kenan Onel Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (610K) Supplementary Figures 1–6, Supplementary Tables 1–8 and Supplementary Methods Additional data
• Regulation of the MDM2-P53 pathway and tumor growth by PICT1 via nucleolar RPL11
  - Nat Med 17(8):944-951 (2011)
  Nature Medicine | Article Regulation of the MDM2-P53 pathway and tumor growth by PICT1 via nucleolar RPL11 * Masato Sasaki1, 14 * Kohichi Kawahara2, 14 * Miki Nishio2 * Koshi Mimori3 * Ryunosuke Kogo3 * Koichi Hamada2 * Bunsho Itoh2 * Jia Wang2 * Yukako Komatsu2 * Yong Ryoul Yang2 * Hiroki Hikasa2 * Yasuo Horie4 * Takayuki Yamashita5 * Takehiko Kamijo6 * Yanping Zhang7 * Yan Zhu8 * Carol Prives8 * Toru Nakano9 * Tak Wah Mak10 * Takehiko Sasaki1, 11 * Tomohiko Maehama12 * Masaki Mori3, 13 * Akira Suzuki1, 2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MedicineVolume: 17,Pages:944–951Year published:(2011)DOI:doi:10.1038/nm.2392Received25 May 2010Accepted03 May 2011Published online31 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg PICT1 (also known as GLTSCR2) is considered a tumor suppressor because it stabilizes phosphatase and tensin homolog (PTEN), but individuals with oligodendrogliomas lacking chromosome 19q13, where PICT1 is located, have better prognoses than other oligodendroglioma patients. To clarify the function of PICT1, we generated Pict1-deficient mice and embryonic stem (ES) cells. Pict1 is a nucleolar protein essential for embryogenesis and ES cell survival. Even without DNA damage, Pict1 loss led to p53-dependent arrest of cell cycle phase G1 and apoptosis. Pict1-deficient cells accumulated p53, owing to impaired Mdm2 function. Pict1 binds Rpl11, and Rpl11 is released from nucleoli in the absence of Pict1. In Pict1-deficient cells, increased binding of Rpl11 to Mdm2 blocks Mdm2-mediated ubiquitination of p53. In human cancer, individuals whose tumors express less PICT1 have better prognoses. When PICT1 is depleted in tumor cells with intact P53 signaling, the cells grow more slowly a! nd accumulate P53. Thus, PICT1 is a potent regulator of the MDM2-P53 pathway and promotes tumor progression by retaining RPL11 in the nucleolus. View full text Figures at a glance * Figure 1: Pict1 loss impairs survival of mouse embryos and ES cells. () Top, morphologies of representative Pict1+/+, Pict1+/− and Pict1−/− embryos at the E3.5 blastocyst stage and the E2.75 morula stage (after compaction). Bottom, TUNEL staining of Pict1+/+, Pict1+/− and Pict1−/− embryos at E3.5. +/+DNase, DNase-treated E3.5 Pict1+/+ embryos (positive control). DAPI, nuclear staining. Scale bar, 50 μm. () Top, semiquantitative RT-PCR of Pict1 mRNA in Pict1 ES cells treated for 24 h with doxycycline (Dox) as indicated. Actb, loading control. Bottom, MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt) assay of proliferation of Pict1 ES cells treated with Dox as indicated. Results are mean cell growth (A490) of three cultures per dose per time point. () Left, representative FACS profiles of Pict1 ES cells treated with or without Dox (5 ng ml−1) for 1, 2 or 3 d, stained with propidium iodide (PI), and analyzed by flow cytometry. Numbers indicate percentage of cells in G0/G1, S! or G2/M phase. Right, mean ± s.e.m. percentage of ES cells in G0/G1 phase (n = 5). *P < 0.01. () Left, representative FACS profile of Pict1 ES cells treated with or without Dox (5 ng ml−1) for 2, 3 or 4 d, stained with TUNEL and analyzed by FACS. Right, mean ± s.e.m. percentage of TUNEL+ ES cells (n = 5). *P < 0.01. Results represent four trials. * Figure 2: Effects of Pict1 deficiency are p53 dependent. () Immunoblot detecting the indicated proteins in Pict1 ES cells treated with or without 5 ng ml−1 doxycycline (Dox). () Immunoblot detecting p53 and Pict1 proteins in Pict1 ES cells treated with Dox. Actin, loading control. () Left, immunoblot detecting p53 protein and DNA damage (pγH2ax) in Pict1 ES cells treated with or without Dox (5 ng ml−1) or UV irradiation (80 J m−2). Right, immunoblot of Pict1 ES cells treated with Dox (5 ng ml−1, 48 h), UV irradiation (80 J m−2, 6 h) or both (final 6 h for UV). () Pict1 ES cells were transfected with scramble siRNA, Trp53 siRNA A or Trp53 siRNA B for 24 h and cultured with or without 5 ng ml−1 Dox for 2 d () or 4 d (). Left, FACS profiles of percentage of cells in each cell cycle phase () and TUNEL+ cells (). Right, mean ± s.e.m. (n = 5) percentage of G0–G1 phase () and TUNEL+ () ES cells. *P < 0.01. () Top, gross appearance of thymi from mice of the indicated genotypes (5 weeks old). Bottom, mean total thymocytes �! � s.e.m. from these thymi (n = 5). *P < 0.01. Scale bar, 5 mm. Results represent three trials. * Figure 3: Pict1 deficiency inhibits Mdm2 function. () Northern blot detecting indicated mRNAs in Pict1 ES cells treated for 48 h with Dox. () Immunoblot detecting p53 and Pict1 in Pict1 ES cells treated for 48 h with or without 5 ng ml−1 Dox and with or without cycloheximide (CHX; 100 μg ml−1). () Immunoblot detecting p53 in Pict1 ES cells treated for 36 h with or without 5 ng ml−1 Dox, with or without MG132 (20 μM). () Immunoblot of H1299 cells transfected with the indicated plasmids and treated with MG132 (20 μM). Lysates were immunoprecipitated and immunoblotted with antibodies to HA (ubiquitin, Ub) and Myc (ubiquitinated p53). () Immunoblot of Pict1 ES cells transfected with scramble siRNA or Mdm2 siRNA (siMdm2) and treated with or without 5 ng ml−1 Dox for 48 h. MG132 (20 μM) was added for 3 h before lysis. The p53 protein level in each sample was adjusted to equality before immunoprecipitation with antibody to p53 or to ubiquitin. () Pict1 ES cells were transfected with scramble siRNA or the indicated siRNA! s and treated with or without 5 ng ml−1 Dox for 24 h. Top, immunoblot detecting indicated proteins. Bottom, quantification of ratio of p53 to actin using LAS Image Analyzer with Multi Gauge Software. () Immunoblot detecting indicated proteins in Pict1 ES cells treated with or without 5 ng ml−1 Dox for 48 h. Results represent three trials. * Figure 4: Pict1 regulates Mdm2 by binding to nucleolar Rpl11. () Immunoblot detecting indicated proteins in cytoplasmic, nuclear and nucleolar fractions (30 μg) of Pict1 ES cells treated for 1 or 2 d with or without 5 ng ml−1 Dox. Nucleostemin (Nsm), lamin and tubulin, localization controls. () Immunoblot detecting the indicated proteins in Pict1 ES cells transfected with vehicle (No), scramble siRNA, Trp53 siRNA (positive control) or siRNAs against the indicated ribosomal proteins and treated with or without 5 ng ml−1 Dox for 24 h. () Immunoblot of untreated Dox− ES cells immunoprecipitated and immunoblotted with antibodies to Pict1 and Rpl11, respectively. () Confocal microscopy of Pict1 ES cells transfected with plasmid encoding RPL11-DsRed and treated with or without 5 ng ml−1 Dox for 24 h or 48 h. Endogenous nucleophosmin (Npm) was detected using antibody to Npm (green). Cell fluorescence at 24 h is in , and percentages of cells retaining RPL11 in the nucleolus at 24 h and 48 h is graphed in (). Scale bars, 5 μm. () Conf! ocal microscopy of Pict1 ES cells transfected with plasmid encoding RPL11-DsRed and treated with or without 5 ng ml−1 Dox for 48 h. Endogenous Mdm2 was detected with antibody to Mdm2 (green). Scale bars, 5 μm. () Immunoblot of cytoplasmic and nuclear fractions of Pict1 ES cells treated with or without 5 ng ml−1 Dox for 2 d. Rpl11 was quantified by immunoblotting and the Rpl11 protein level in each sample was adjusted to equality before immunoprecipitation with antibody to Rpl11. Lysates were immnoprecipitated with control IgG or antibody to Rpl11 followed by immunoblotting to detect Mdm2. Results represent three trials. * Figure 5: Reduced cancer growth and better survival with low PICT1. () Pict1+/+ and Pict1+/− mice treated with DMBA plus TPA were monitored for papillomagenesis for 22 weeks. Left, gross tumor appearance. Scale bars, 2 mm. Middle, number of papillomas per mouse at 22 weeks (mean ± s.e.m., *P < 0.05). Right, incidence and diameter of papillomas at the indicated number of weeks after TPA. () Human glioma cell lines DBTRG-05MG and D247, colorectal cancer cell lines Lovo and RKO, and ovarian cancer cell line RMG-1 (all WT TP53) were treated with scramble shRNA or shRNA against PICT1 (PICT1-1 and PICT1-2). Top, MTS assay of growth inhibition. Bottom, immunoblot detecting indicated proteins. Results represent three trials. () Left, Kaplan-Meier survival curves for 181 individuals with colorectal cancer and 81 individuals with esophageal cancer whose tumors showed low PICT1 mRNA (blue) or high PICT1 mRNA (orange). Middle, Kaplan-Meier curves for 67 individuals with colorectal cancer and 45 individuals with esophageal cancer whose tumors showed W! T TP53 and high or low PICT1 mRNA. Right, Kaplan-Meier curves for 45 individuals with colorectal cancer and 34 individuals with esophageal cancer whose tumors showed mutated TP53 and high or low PICT1 mRNA. * Figure 6: PICT1 binding to nucleolar RPL11 regulates MDM2-P53 activity. Model of PICT1 function. Left, when PICT1 is present in the nucleolus, RPL11 is retained in the nucleolus and MDM2 is free to ubquitinate P53, promoting its degradation. Right, when PICT1 is absent, nucleolar RPL11 escapes into the nucleoplasm and binds to MDM2, blocking its ubiquitination of P53. As a result, P53 accumulates in PICT1-deficient cells. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Masato Sasaki & * Kohichi Kawahara Affiliations * Global Centers of Excellence Program, Akita University Graduate School of Medicine, Akita, Japan. * Masato Sasaki, * Takehiko Sasaki & * Akira Suzuki * Division of Cancer Genetics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan. * Kohichi Kawahara, * Miki Nishio, * Koichi Hamada, * Bunsho Itoh, * Jia Wang, * Yukako Komatsu, * Yong Ryoul Yang, * Hiroki Hikasa & * Akira Suzuki * Division of Molecular and Surgical Oncology, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan. * Koshi Mimori, * Ryunosuke Kogo & * Masaki Mori * Department of Gastroenterology, Akita University Graduate School of Medicine, Akita, Japan. * Yasuo Horie * Laboratory of Molecular Genetics, Institute for Molecular and Cellular Regulation, Gunma University, Maebashi, Japan. * Takayuki Yamashita * Division of Biochemistry and Molecular Carcinogenesis, Chiba Cancer Center Research Institute, Chiba, Japan. * Takehiko Kamijo * Department of Radiation Oncology and Lineberger Comprehensive Cancer Center, Chapel Hill, North Carolina, USA. * Yanping Zhang * Department of Biological Sciences, Columbia University, New York, New York, USA. * Yan Zhu & * Carol Prives * Department of Pathology, Osaka University, Suita, Japan. * Toru Nakano * The Campbell Family Institute for Cancer Research, University Health Network, Toronto, Ontario, Canada. * Tak Wah Mak * Department of Medical Biology, Akita University Graduate School of Medicine, Akita, Japan. * Takehiko Sasaki * Department of Biochemistry and Cell Biology, Japan National Institute of Infectious Diseases, Tokyo, Japan. * Tomohiko Maehama * Department of Gastroenterological Surgery, Medical School and Graduate School of Frontier Biosciences, Osaka University, Suita, Japan. * Masaki Mori Contributions M.S. carried out the initial generation and analyses of Pict1flox mice and Pict1 ES cells. K.K. carried out subsequent major biochemical and biological experiments, and M.N. carried out mouse work. K.M., R.K. and M.M. carried out the human cancer tissue analyses. K.H. generated Pict1−/− mice. B.I. assisted with confocal microscopy. J.W., Y.K. and Y.R.Y. assisted with the introduction of shRNA into human cancer cell lines. H.H. assisted with the protein binding assays. Y.H. carried out mouse analyses. T.Y., T.K., Y. Zhang, Y. Zhu, C.P. and T.W.M. provided key materials. T.M., K.M. and A.S. conceived of the project, and M.S., K.K., K.M, T.M., M.M. and A.S. designed the experiments. M.S., K.K., M.N., K.M., R.K., T.Y., T.K., Y. Zhang, C.P., T.N., T.W.M., T.S., T.M., M.M. and A.S. discussed the hypothesis and interpreted the data. A.S. coordinated and directed the project and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Akira Suzuki or * Masaki Mori Author Details * Masato Sasaki Search for this author in: * NPG journals * PubMed * Google Scholar * Kohichi Kawahara Search for this author in: * NPG journals * PubMed * Google Scholar * Miki Nishio Search for this author in: * NPG journals * PubMed * Google Scholar * Koshi Mimori Search for this author in: * NPG journals * PubMed * Google Scholar * Ryunosuke Kogo Search for this author in: * NPG journals * PubMed * Google Scholar * Koichi Hamada Search for this author in: * NPG journals * PubMed * Google Scholar * Bunsho Itoh Search for this author in: * NPG journals * PubMed * Google Scholar * Jia Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Yukako Komatsu Search for this author in: * NPG journals * PubMed * Google Scholar * Yong Ryoul Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Hiroki Hikasa Search for this author in: * NPG journals * PubMed * Google Scholar * Yasuo Horie Search for this author in: * NPG journals * PubMed * Google Scholar * Takayuki Yamashita Search for this author in: * NPG journals * PubMed * Google Scholar * Takehiko Kamijo Search for this author in: * NPG journals * PubMed * Google Scholar * Yanping Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Yan Zhu Search for this author in: * NPG journals * PubMed * Google Scholar * Carol Prives Search for this author in: * NPG journals * PubMed * Google Scholar * Toru Nakano Search for this author in: * NPG journals * PubMed * Google Scholar * Tak Wah Mak Search for this author in: * NPG journals * PubMed * Google Scholar * Takehiko Sasaki Search for this author in: * NPG journals * PubMed * Google Scholar * Tomohiko Maehama Search for this author in: * NPG journals * PubMed * Google Scholar * Masaki Mori Contact Masaki Mori Search for this author in: * NPG journals * PubMed * Google Scholar * Akira Suzuki Contact Akira Suzuki Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (709K) Supplementary Figures 1–8 and Supplementary Methods Additional data
• Circulating urokinase receptor as a cause of focal segmental glomerulosclerosis
  - Nat Med 17(8):952-960 (2011)
  Nature Medicine | Article Circulating urokinase receptor as a cause of focal segmental glomerulosclerosis * Changli Wei1 * Shafic El Hindi1, 18 * Jing Li1, 18 * Alessia Fornoni1, 2, 18 * Nelson Goes3 * Junichiro Sageshima4 * Dony Maiguel1 * S Ananth Karumanchi5 * Hui-Kim Yap6 * Moin Saleem7 * Qingyin Zhang8 * Boris Nikolic3 * Abanti Chaudhuri9 * Pirouz Daftarian10, 11 * Eduardo Salido12 * Armando Torres12 * Moro Salifu13 * Minnie M Sarwal9 * Franz Schaefer14 * Christian Morath15 * Vedat Schwenger15 * Martin Zeier15 * Vineet Gupta1 * David Roth1 * Maria Pia Rastaldi16 * George Burke4 * Phillip Ruiz4, 17 * Jochen Reiser1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:952–960Year published:(2011)DOI:doi:10.1038/nm.2411Received05 January 2011Accepted31 May 2011Published online31 July 2011 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Focal segmental glomerulosclerosis (FSGS) is a cause of proteinuric kidney disease, compromising both native and transplanted kidneys. Treatment is limited because of a complex pathogenesis, including unknown serum factors. Here we report that serum soluble urokinase receptor (suPAR) is elevated in two-thirds of subjects with primary FSGS, but not in people with other glomerular diseases. We further find that a higher concentration of suPAR before transplantation underlies an increased risk for recurrence of FSGS after transplantation. Using three mouse models, we explore the effects of suPAR on kidney function and morphology. We show that circulating suPAR activates podocyte β3 integrin in both native and grafted kidneys, causing foot process effacement, proteinuria and FSGS-like glomerulopathy. Our findings suggest that the renal disease only develops when suPAR sufficiently activates podocyte β3 integrin. Thus, the disease can be abrogated by lowering serum suPAR concen! trations through plasmapheresis, or by interfering with the suPAR–β3 integrin interaction through antibodies and small molecules targeting either uPAR or β3 integrin. Our study identifies serum suPAR as a circulating factor that may cause FSGS. View full text Figures at a glance * Figure 1: suPAR measurement in the serum of subjects with glomerular disease. For transplant subjects, the suPAR values were measured from pretransplantation serum unless otherwise indicated. Data is presented as means ± s.e.m. () Serum suPAR concentration in subjects with glomerular disease and healthy human subjects. MN, membranous nephropathy. *P < 0.05 for FSGS versus MN and preeclampsia; #P < 0.001 for FSGS versus healthy, MCD relapse, and MCD remission. Note that the values highlighted with red or green dots in the healthy subject and FSGS columns are identical twin pairs; in each case, one is healthy and has a twin brother with FSGS. () Serum suPAR in different population of subjects with primary FSGS. **P < 0.01 for recurrent FSGS versus nonrecurrent FSGS and nontransplant primary FSGS, respectively. () Serum suPAR concentrations after transplantation. #P < 0.001. () Correlation analysis of pretransplantation suPAR with proteinuria after transplantation. Pearson r = 0.16, P = 0.50. () Correlation analysis of pretransplantation suPAR with eGFR! . Pearson r = 0.36, P = 0.16. () Correlation analysis of suPAR after transplantation with eGFR. Pearson r = 0.10, P = 0.58. * Figure 2: suPAR binds to and activates β3 integrin on podocytes. () Western blot showing that suPAR binds β3 integrin (representative of three experiments). EIF1B-GFP, encoding a translation initiation factor, and Raver-Flag encoding a ribonucleoprotein served as negative binding controls. β3 integrin is encoded by Itgb3. S, sPlaurWT (encoding suPAR); M, PlaurWT (encoding membrane-bound uPAR); IP, immunoprecipitation. () AP5 immunostaining of differentiated human podocytes incubated with suPAR-rich recurrent FSGS serum (rec-FSGS serum), co-treated with the monoclonal antibody to human uPAR (uPAR mAb), and with cycloRGDfv, a small molecule that blocks β3 integrin activity. AP5-specific antibody detects the active form of β3 integrin. Bovine serum, negative control; suPAR, recombinant human suPAR protein. () Immunohistochemistry of AP5 on kidney biopsies from patients with glomerular disease. Top, representative AP5 staining in the glomerulus of subjects with FSGS. Bottom, the percentage (mean ± s.e.m.) of AP5-positive glomeruli. *P < ! 0.05 for primary FSGS versus control; **P < 0.01 for recurrent FSGS versus control. () Double immunofluorescent staining in glomeruli of kidney grafts for AP5 (green) and the podocyte marker synaptopodin (red). Top and bottom left, AP5 in the graft glomerulus 2 h after reperfusion in recurrent and nonrecurrent transplant biopsies (n = 2 per group). Top right, AP5 signal in recurrent transplant biopsies (n = 3) and nonrecurrent grafts (n = 5). Bottom right, normal kidney sections (n = 2) and biopsies from acute T cell–mediated rejections (n = 3) served as controls. Scale bars, 30 μm. * Figure 3: suPAR serum concentrations and podocyte β3 integrin activity determine treatment response to plasmapheresis in recurrent FSGS. () Human podocytes incubated with different pooled serum samples and assayed for β3 integrin activity. MFI, mean fluorescence intensity. *P < 0.05 for nonrecurrent FSGS versus normal subjects, ***P < 0.001 for recurrent versus nonrecurrent FSGS or versus healthy subjects. The respective suPAR concentration of the pooled sera is marked in red. NS, normal (healthy) subject; NR, nonrecurrent FSGS; REC, recurrent FSGS (representative of three experiments). () Pharmacological modulation of β3 integrin activity in podocytes. **P < 0.01 for cylcoRGDfv co-treated cells versus recurrent FSGS serum alone; ***P < 0.001 for uPAR-specific mAb co-treated cells versus recurrent FSGS serum alone. () suPAR in serum from subjects with recurrent FSGS (n = 4) before and after a course of plasmapheresis. **P < 0.01. () Effect of plasmapheresis on β3 integrin activity in podocytes incubated with recurrent FSGS serum (n = 6), collected before and after serial treatment with plasmapheresis. ***P! < 0.001. (–) Clinical cases of recurrent FSGS. Top graphs show serum suPAR, urine protein/creatinine ratio (g/g) and individual plasmapheresis treatment as indicated by arrows and plotted over time () from before (−1) to after transplantation. Bottom graphs and images show podocyte β3 integrin activity measured by FACS (left) and immunofluorescence (right) as a result of incubation with pretransplantation serum, or with the after-transplantation serum collected after repetitive plasmapheresis treatments. As a reference, the mean concentration of AP5 from is marked as a dashed line. (,) Patients who obtained full remission after pheresis. (,) Patients who did not achieve remission after pheresis. Scale bars, 30 μm. Whiskers in plots of AP5 activity and serum suPAR show minimum to maximum. * Figure 4: suPAR activates β3 integrin and causes foot process effacement in Plaur−/− mouse kidneys and albuminuria in Plaur−/− mice. () Injection (i.v.) of high doses of recombinant mouse suPAR into Plaur−/− mice (n = 4 per group) induces proteinuria. **P < 0.01 for mice injected with 20 μg of suPAR at 24 h versus mice injected with other doses or versus other time points. () Injection (i.v.) of high doses of recombinant suPAR deposits into podocytes. Green, uPAR; red, synaptopodin (Synpo). () AP5 activity induced in the podocytes of high-dosage suPAR-injected Plaur−/− mice (n = 4). Green, AP5; red, Synpo. (,) LPS induced endogenous suPAR in wild-type mice (n = 6). () Serum suPAR concentrations in LPS-treated mice. ***P < 0.001 for LPS-injected mice at 24 h versus PBS control, and versus LPS-injected mice at 0 h. **P < 0.01 for LPS-injected mice at 48 h versus at 0 h. () Urinary suPAR concentrations. ***P < 0.001 for LPS-injected mice at 48 h versus 0 h, and versus PBS control at any time point. **P < 0.01 for LPS-injected mice at 24 h versus 0 h. () Generation of a hybrid-kidney mouse model. () ! Electron microscope analysis of the PBS (n = 3) or LPS (n = 5) treated hybrid kidney. () uPAR expression in the native or Plaur−/− kidneys from the hybrid-kidney mice with or without LPS treatment. Scale bars, 30 μm in , and ; 250 nm in . Error bars, means ± s.e.m. in ; means ± s.d. in ,. * Figure 5: Sustained overexpression of suPAR in the blood of wild-type mice leads to an FSGS-like glomerulopathy. () Generation of β3 integrin binding–deficient suPAR mutants. () Serum suPAR concentrations in the sPlaurWT engineered mice. *P < 0.05 at day 7 versus day 0 (before initial electroporation) () Urinary suPAR in sPlaurWT engineered mice. ***P < 0.001 for days 7, 14 and 28 versus day 0; *P < 0.05 for day 28 versus day 7. (n = 4 in each group). () Albuminuria in sPlaurWT and sPlaurE134A mice. *P < 0.05 for sPlaurWT mice at day 7 versus before treatment or versus sPlaurE134A mice at day 7. **P < 0.01 for sPlaurWT engineered mice at day 14 versus before treatment or versus sPlaurE134A treated mice at day 7 or 14. () Kidney EM analysis of sPlaur engineered mice. Podocyte damage is reflected by relating the length of effaced foot process (FP) to the total length of the glomerular basement membrane (GBM) analyzed. Scale bars, 1 μm for upper image, 250 nm for lower image. **P < 0.01. () Histochemistry and light microscopy of the kidney from sPlaur engineered mice. PAS, periodic ac! id–Schiff. Scale bars, 30 μm. () Histopathological alteration of the kidneys was semiquantitatively scored. *P < 0.05. Error bars, means ± s.e.m. in ; means ± s.d. in ,, and . * Figure 6: Administration of blocking antibody to uPAR ameliorates suPAR-caused kidney damage. (n = 4 in each group). () Proteinuria in the antibody treated sPlaurWT mice. *P < 0.05 for sPlaurWT mice receiving isotype control at day 7 versus before initial electroporation at day 0 or versus mice treated with antibody to uPAR at day 7; ***P < 0.01 for sPlaurWT mice receiving isotype control at day 21 versus at day 0 or versus antibody to uPAR-treated mice at day 21. () Morphological examination of the antibody treated sPlaurWT kidney. Scale bars, 30 μm. () Pathology score. *P < 0.05. () Electron microscopic analysis of the antibody treated kidney from sPlaurWT engineered mice. **P < 0.01 for IgG isotype control versus uPAR-specific antibody–treated sPlaurWT engineered mice with respect to the ratio of effaced foot process (FP) to total GBM length measured. Scale bar, 360 nm. Error bars, means ± s.e.m. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions GenBank * BC010309 Author information * Abstract * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Shafic El Hindi, * Jing Li & * Alessia Fornoni Affiliations * Department of Medicine, Miller School of Medicine, University of Miami, Miami, Florida, USA. * Changli Wei, * Shafic El Hindi, * Jing Li, * Alessia Fornoni, * Dony Maiguel, * Vineet Gupta, * David Roth & * Jochen Reiser * Diabetes Research Institute, Miller School of Medicine, University of Miami, Miami, Florida, USA. * Alessia Fornoni * Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. * Nelson Goes & * Boris Nikolic * Department of Surgery, Miller School of Medicine, University of Miami, Miami, Florida, USA. * Junichiro Sageshima, * George Burke & * Phillip Ruiz * Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA. * S Ananth Karumanchi * Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. * Hui-Kim Yap * University of Bristol, Children's Renal Unit, Bristol Royal Hospital for Children, Bristol, UK. * Moin Saleem * Department of Surgery, Columbia University, New York, New York, USA. * Qingyin Zhang * Department of Pediatrics, Stanford University, Stanford, California, USA. * Abanti Chaudhuri & * Minnie M Sarwal * The Wallace H. Coulter Center for Translational Research, Miller School of Medicine, University of Miami, Miami, Florida, USA. * Pirouz Daftarian * Department of Ophthalmology, Miller School of Medicine, University of Miami, Miami, Florida, USA. * Pirouz Daftarian * Servicio de Nefrologia and Centre for Biomedical Research on Rare Diseases (CIBERER), Hospital Universitario de Canarias, Canary Islands, Spain. * Eduardo Salido & * Armando Torres * Division of Nephrology, SUNY Downstate Medical Center, Brooklyn, New York, USA. * Moro Salifu * Center for Pediatric and Adolescent Medicine, University of Heidelberg, Heidelberg, Germany. * Franz Schaefer * Department of Nephrology and Endocrinology, University of Heidelberg, Heidelberg, Germany. * Christian Morath, * Vedat Schwenger & * Martin Zeier * Renal Research Laboratory, Fondazione IRCCS Ospedale Maggiore Policlinico & Fondazione D'Amico per la Ricerca sulle Malattie Renali, Milan, Italy. * Maria Pia Rastaldi * Department of Pathology, Miller School of Medicine, University of Miami, Miami, Florida, USA. * Phillip Ruiz Contributions J.R. conceived the study. J.R. and C.W. designed the experiments, coordinated the study, analyzed the data and wrote the manuscript. C.W., S.E.H., J.L., D.M., Q.Z., B.N., P.D., V.G. performed the experiments. A.F., N.G., G.B., J.S., S.A.K., H.-K.Y., M.Saleem, A.C., E.S., A.T., M.Salifu, M.M.S., F.S., C.M., V.S., M.Z., D.R., M.P.R., P.R., J.R. contributed to clinical samples and clinical information. M.P.R. and P.R. provided pathology service. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Jochen Reiser Author Details * Changli Wei Search for this author in: * NPG journals * PubMed * Google Scholar * Shafic El Hindi Search for this author in: * NPG journals * PubMed * Google Scholar * Jing Li Search for this author in: * NPG journals * PubMed * Google Scholar * Alessia Fornoni Search for this author in: * NPG journals * PubMed * Google Scholar * Nelson Goes Search for this author in: * NPG journals * PubMed * Google Scholar * Junichiro Sageshima Search for this author in: * NPG journals * PubMed * Google Scholar * Dony Maiguel Search for this author in: * NPG journals * PubMed * Google Scholar * S Ananth Karumanchi Search for this author in: * NPG journals * PubMed * Google Scholar * Hui-Kim Yap Search for this author in: * NPG journals * PubMed * Google Scholar * Moin Saleem Search for this author in: * NPG journals * PubMed * Google Scholar * Qingyin Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Boris Nikolic Search for this author in: * NPG journals * PubMed * Google Scholar * Abanti Chaudhuri Search for this author in: * NPG journals * PubMed * Google Scholar * Pirouz Daftarian Search for this author in: * NPG journals * PubMed * Google Scholar * Eduardo Salido Search for this author in: * NPG journals * PubMed * Google Scholar * Armando Torres Search for this author in: * NPG journals * PubMed * Google Scholar * Moro Salifu Search for this author in: * NPG journals * PubMed * Google Scholar * Minnie M Sarwal Search for this author in: * NPG journals * PubMed * Google Scholar * Franz Schaefer Search for this author in: * NPG journals * PubMed * Google Scholar * Christian Morath Search for this author in: * NPG journals * PubMed * Google Scholar * Vedat Schwenger Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Zeier Search for this author in: * NPG journals * PubMed * Google Scholar * Vineet Gupta Search for this author in: * NPG journals * PubMed * Google Scholar * David Roth Search for this author in: * NPG journals * PubMed * Google Scholar * Maria Pia Rastaldi Search for this author in: * NPG journals * PubMed * Google Scholar * George Burke Search for this author in: * NPG journals * PubMed * Google Scholar * Phillip Ruiz Search for this author in: * NPG journals * PubMed * Google Scholar * Jochen Reiser Contact Jochen Reiser Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (688K) Supplementary Figures 1–3, Supplementary Tables 1–3 and Supplementary Methods Additional data
• Inhibition of Notch signaling ameliorates insulin resistance in a FoxO1-dependent manner
  - Nat Med 17(8):961-967 (2011)
  Nature Medicine | Article Inhibition of Notch signaling ameliorates insulin resistance in a FoxO1-dependent manner * Utpal B Pajvani1 * Carrie J Shawber2, 3 * Varman T Samuel4 * Andreas L Birkenfeld4 * Gerald I Shulman4 * Jan Kitajewski2, 3 * Domenico Accili1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:961–967Year published:(2011)DOI:doi:10.1038/nm.2378Received09 November 2010Accepted15 April 2011Published online31 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Transcription factor FoxO1 promotes hepatic glucose production. Genetic inhibition of FoxO1 function prevents diabetes in experimental animal models, providing impetus to identify pharmacological approaches to modulate this function. Altered Notch signaling is evident in tumorigenesis, and Notch antagonists are in clinical testing for application in cancer. Here we report that FoxO1 and Notch coordinately regulate hepatic glucose metabolism. Combined haploinsufficiency of FoxO1 and Notch1 markedly raises insulin sensitivity in diet-induced insulin resistance, as does liver-specific knockout of the Notch transcriptional effector Rbp-Jκ. Conversely, Notch1 gain-of-function promotes insulin resistance in a FoxO1-dependent manner and induces glucose-6-phosphatase expression. Pharmacological blockade of Notch signaling with γ-secretase inhibitors raises insulin sensitivity after in vivo administration in lean mice and in obese, insulin-resistant mice. The data identify a hereto! fore unknown metabolic function of Notch and suggest that Notch inhibition is beneficial in diabetes treatment, in part by helping to offset excessive FoxO1-driven hepatic glucose production. View full text Figures at a glance * Figure 1: Metabolic characterization of Foxo1+/− and Foxo1+/−; Notch1+/− mice. (,) Notch1 cleavage () and Notch target gene expression (mRNA levels, ) in livers from 8-week-old male WT mice after fasting for indicated periods or refeeding after 24-h fast. *P < 0.05, **P < 0.01. (,) Glucose () and insulin levels () in mice fed either HFD or standard chow and fasted for 16 h without refeeding (fasted) or fasted for 16 h and then refed for 2 h (refed). () Intraperitoneal glucose tolerance tests in HFD-fed mice after 16-h fast. () Insulin tolerance tests in HFD-fed mice after 4-h fast. () Pyruvate tolerance test in HFD-fed mice after 16-h fast. () Glucose production in primary hepatocytes from WT, FoxO1+/− and Foxo1+/−; Notch1+/− mice in the presence (HGP) or absence of pyruvate and lactate (glycogenolysis, Gly). The difference between these two values was assumed to reflect gluconeogenesis (Gng). () Western blots of insulin signaling proteins in livers from HFD-fed WT, FoxO1+/− and Foxo1+/−; Notch1+/− mice. All animals were 16 weeks old. *P < ! 0.05 vs. WT, &P < 0.05 vs. Foxo1+/− (n = 7 or 8 of each genotype). Error bars indicate s.e.m. * Figure 2: Hyperinsulinemic-euglycemic clamps and gene expression studies in Foxo1+/−; Notch1+/− mice. (,) Glucose infusion rate (GIR, ) or HGP rate and glucose disposal rate (Rd) () from clamp studies in 12-week-old, HFD-fed WT, Foxo1+/− and Foxo1+/−; Notch1+/− male mice. () 14C-2-deoxy-glucose (2-DOG) uptake in gastrocnemius muscle (Gastroc) and white adipose tissue (WAT) during the final 5 min of the clamp. () Hepatic glycogen content in clamped livers. (,) mRNA levels in 16-week-old chow-fed () or HFD-fed () WT, Foxo1+/− and Foxo1+/−; Notch1+/− male mice killed after a 16-h fast. *P < 0.05, **P < 0.01, ***P < 0.001 vs. WT; &P < 0.05 vs. Foxo1+/− (n = 7 or 8 of each genotype). Error bars indicate s.e.m. * Figure 3: Metabolic characteristics of L-Rbpj mice. (–) Growth curves (), body composition (), ad libitum insulin () and glucose levels () of HFD-fed L-Rbpj mice and Cre-negative controls (Cre−) measured every 2–4 weeks. () Intraperitoneal glucose tolerance tests in 16-h-fasted, HFD-fed Cre− and L-Rbpj mice. () Western blots for hepatic p-Akt, total Akt and G6pc from fasted, HFD-fed, 16-week-old Cre− and L-Rbpj (Cre+) mice. *P < 0.05 vs. Cre− (n = 8 of each genotype). Error bars indicate s.e.m. * Figure 4: Notch1 regulation of G6pc transcription in hepatocytes, and hepatic insulin sensitivity in vivo. () mRNA levels in primary hepatocytes from 12-week-old WT male mice transduced with adenoviruses expressing FoxO1-ADA (FoxO1), Notch1-IC (N1-IC) and/or GFP (MOI = 5). (,) Luciferase reporter assays of the G6pc promoter after transduction with GFP or N1-IC (), or after incubation with rDLL4 (). Luciferase activity was induced in constructs containing both Rbp-Jκ (R) and FoxO1 binding sites (−1227bp) but not constructs lacking the sites (−499bp) or containing mutated FoxO1 sites (−1227mut). Numbers refer to nucleotides upstream of transcription start site. No tx, control with no treatment. *P < 0.05, ***P < 0.001 vs. GFP or no tx; *&P < 0.05 vs. FoxO1 or FoxO1 + GFP. () ChIP at the G6pc promoter using anti–Rbp-Jκ or control antibody in livers from fasted control (Cre−), L-Foxo1 and L-Rbpj mice. () G6pc ChIP assays from liver of WT mice fasted for 16 h or refed for 2 h after a 16-h fast. In ,, *P < 0.05 compared with control (Neg) IgG (n = 4). (,) Glucose () and ins! ulin levels () 7 d after N1-IC delivery in mice fasted for 16 h or refed for 2 h after a 16-h fast. () mRNA levels in livers of mice transduced with either N1-IC or GFP adenoviruses. (,) Sixteen-hour-fasted and 2-h-refed Insulin levels () and hepatic gene expression (mRNA levels, ) in 16-h-fasted L-Rbpj male mice and Cre− controls transduced with either N1-IC or GFP adenoviruses. *P < 0.05, **P < 0.01, ***P < 0.001 vs. GFP; &P < 0.05 vs. Cre− (n = 5–8 of each genotype). Error bars indicate s.e.m. * Figure 5: Effects of GSI in primary hepatocytes. () Western blot analysis of Notch1 cleavage at Val1744 after incubation with increasing doses of EDTA in the presence or absence of GSI. () mRNA levels of Notch targets in vehicle-treated (No tx) or EDTA-treated hepatocytes in the presence or absence of GSI. (,) mRNA levels () and glucose production () in the absence (No tx) or presence of GSI. Hepatocytes were treated with cAMP and dexamethasone (cAMP/dex) for 3 h to stimulate gluconeogenic gene expression and glucose output. () Dose-response curve for insulin inhibition of glucose production from primary hepatocytes incubated with or without GSI. () Glucose production in the absence or presence of GSI in primary hepatocytes from control (Cre−), FoxO1-deficient (L-Foxo1) and Rbp-Jκ–deficient mice (L-Rbpj). () mRNA levels in the absence or presence of GSI in hepatocytes transduced with FoxO1 shRNA adenovirus. *P < 0.05 vs. No tx; &P < 0.05 vs. cAMP/dex (n = 4). Error bars indicate s.e.m. Data from one experiment represe! ntative of three individual experiments are shown. * Figure 6: Insulin-sensitizing effects of dibenzazepine (GSI) treatment. (,) Intraperitoneal glucose tolerance tests (IPGTT) () and hepatic gene expression (mRNA levels, ) in 16-h-fasted, chow-fed lean mice after a single dose of GSI (GSI 1 d) or 5 consecutive days of GSI treatment (GSI 5 d). (–) Ad libitum glucose () and insulin levels () in DIO and ob/ob mice or IPGTT in ob/ob mice (), after a 5-d course of either vehicle or GSI. (–) IPGTT () or ad libitum glucose () or insulin () levels in DIO mice treated with either vehicle or GSI every third day (arrows). () Glucose levels in DIO mice treated with vehicle or GSI every second day. () Western blots of Akt and IRS1 phosphorylation in livers isolated after 5-d treatment with vehicle or GSI. *P < 0.05, **P < 0.01, ***P < 0.001 vs. vehicle; &P < 0.05 vs. GSI 1 d (n = 6 in each group). Error bars indicate s.e.m. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Medicine, Columbia University, New York, New York, USA. * Utpal B Pajvani & * Domenico Accili * Department of Pathology, Columbia University, New York, New York, USA. * Carrie J Shawber & * Jan Kitajewski * Department of Obstetrics and Gynecology, Columbia University, New York, New York, USA. * Carrie J Shawber & * Jan Kitajewski * Department of Internal Medicine, Yale University, New Haven, Connecticut. * Varman T Samuel, * Andreas L Birkenfeld & * Gerald I Shulman Contributions U.B.P. designed and performed experiments, analyzed data and wrote the manuscript. C.J.S., A.L.B. and V.T.S. performed experiments and analyzed data. G.I.S., J.K. and D.A. designed the studies, analyzed the data and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Domenico Accili Author Details * Utpal B Pajvani Search for this author in: * NPG journals * PubMed * Google Scholar * Carrie J Shawber Search for this author in: * NPG journals * PubMed * Google Scholar * Varman T Samuel Search for this author in: * NPG journals * PubMed * Google Scholar * Andreas L Birkenfeld Search for this author in: * NPG journals * PubMed * Google Scholar * Gerald I Shulman Search for this author in: * NPG journals * PubMed * Google Scholar * Jan Kitajewski Search for this author in: * NPG journals * PubMed * Google Scholar * Domenico Accili Contact Domenico Accili Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (799K) Supplementary Figures 1–6 and Supplementary Tables 1–5 Additional data
• HDAC6 inhibitors reverse axonal loss in a mouse model of mutant HSPB1–induced Charcot-Marie-Tooth disease
  - Nat Med 17(8):968-974 (2011)
  Nature Medicine | Article HDAC6 inhibitors reverse axonal loss in a mouse model of mutant HSPB1–induced Charcot-Marie-Tooth disease * Constantin d'Ydewalle1, 2 * Jyothsna Krishnan1, 2 * Driss M Chiheb1, 2 * Philip Van Damme1, 2, 3 * Joy Irobi4, 5 * Alan P Kozikowski6 * Pieter Vanden Berghe7 * Vincent Timmerman4, 5 * Wim Robberecht1, 2, 3 * Ludo Van Den Bosch1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:968–974Year published:(2011)DOI:doi:10.1038/nm.2396Received01 February 2011Accepted10 May 2011Published online24 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Charcot-Marie-Tooth disease (CMT) is the most common inherited disorder of the peripheral nervous system. Mutations in the 27-kDa small heat-shock protein gene (HSPB1) cause axonal CMT or distal hereditary motor neuropathy (distal HMN). We developed and characterized transgenic mice expressing two different HSPB1 mutations (S135F and P182L) in neurons only. These mice showed all features of CMT or distal HMN dependent on the mutation. Expression of mutant HSPB1 decreased acetylated α-tubulin abundance and induced severe axonal transport deficits. An increase of α-tubulin acetylation induced by pharmacological inhibition of histone deacetylase 6 (HDAC6) corrected the axonal transport defects caused by HSPB1 mutations and rescued the CMT phenotype of symptomatic mutant HSPB1 mice. Our findings demonstrate the pathogenic role of α-tubulin deacetylation in mutant HSPB1–induced neuropathies and offer perspectives for using HDAC6 inhibitors as a therapeutic strategy for hered! itary axonopathies. View full text Figures at a glance * Figure 1: Neuronal expression of human mutant HSPB1 in mice leads to progressive motor defects and decreased muscle strength. () Western blots of sciatic nerve, DRG, spinal cord and brain homogenates isolated from 2-month-old nontransgenic (Nontg) mice or mice expressing WT or mutant (S135F or P182L) HSPB1 probed with an antibody to the HA tag of the 27-kDa human HSPB1. Glyceraldehyde-3-phosphate dehydrogenase (Gapdh) staining confirmed equal loading. MW, molecular weight. () Six-month-old mice expressing WT or mutant HSPB1 lifted by the tail showing normal spreading of the limbs (WT) or limb-clasping behavior (S135F and P182L). () Monthly testing of the general motor performance of the different HSPB1-transgenic mice using an accelerating rotarod. n = 25 mice per genotype. Two-way analysis of variance (ANOVA) for repeated measures. ***P < 0.0001. (,) Age-dependent measurements of grip strength normalized to body weight of all paws combined () or forepaws only () using a dynamometer with a grid or a triangular bar, respectively. AU, arbitrary units. n = 25 mice per genotype. Two-way ANOVA for repea! ted measures. Blue asterisks indicate differences between P182L and WT; red asterisks indicate differences between S135F and WT. The line represents the span in which data points are significantly different compared to WT. Tukey's HSD test was used for post hoc analysis. *P < 0.05; ***P < 0.0001. Data are presented as means ± s.e.m. * Figure 2: Mice expressing mutant HSPB1 show steppage gait and clawed hindpaws. () Typical gait patterns of 8-month-old transgenic mice monitored with the semiautomated Catwalk system. Colored bars represent the time a paw makes contact with the floor plate. LH, left hindpaw; LF, left forepaw; RH, right hindpaw; RF, right forepaw. Asterisks mark hesitations in the gait pattern observed for both mutant HSPB1 mouse lines. Scale bar, 10 cm. (–) Quantification of various parameters obtained from the gait analysis with the Catwalk. Stride length (), forepaw angle (), hindpaw angle (), forepaw print area () and hindpaw print area () were measured as a function of age in mice expressing HSPB1WT, HSPB1S135F or HSPB1P182L. n = 15 mice per genotype. Two-way ANOVA for repeated measures. **P < 0.001; ***P < 0.0001. Blue asterisks indicate differences between P182L and WT. Red asterisks indicate differences between S135F and WT. The lines represent the span in which the data points are significantly different. Tukey's HSD test was used for post hoc analysis. Data ! are presented as means ± s.e.m. () Typical example of a mutant HSPB1P182L-expressing mouse showing clawed hindpaws. * Figure 3: Mutation-dependent pure motor or sensorimotor axonal loss and denervation of neuromuscular junctions in mice expressing mutant HSPB1. () Relative difference in response latencies on a hot plate between mice expressing HSPB1WT, HSPB1S135F and HSPB1P182L. () Determination of the amplitude and the latency of the CMAPs in mice expressing HSPB1WT, HSPB1S135F or HSPB1P182L. () CMAP amplitudes as a function of age. () Linear curve fitting of the CMAP data points (R2S135F: 0.99 and R2P182L: 0.94). () CMAP latencies as a function of age. (,) Age-dependent measurements of amplitudes () and latencies () of SNAPs. Blue asterisks indicate difference between P182L and WT. Red asterisks indicate difference between S135F and WT. Line represents the span in which the data points are significantly different compared to WT. Tukey's HSD test was used to analyze post hoc. () Toluidine blue staining of semithin distal sciatic nerve sections of 10-month-old HSPB1WT-expressing (left) and mutant HSPB1–expressing (middle and right) mice, showing axonal loss in the mutant lines. No signs of demyelination were observed. Scale bars,! 40 μm. () Correlation between myelin thickness and axonal diameter confirming the absence of demyelination in HSPB1WT-expressing (left) and mutant HSPB1–expressing (middle and right) mice. () Quantification of the number of axons in distal parts of the sciatic nerve. () Left, example of a completely denervated neuromuscular junction stained with α-bungarotoxin (red) and negative for neurofilament heavy chain. Scale bar, 20 μm. Right, quantification of these denervated neuromuscular junctions in 10-month-old transgenic HSPB1 mice. In –, n = 15 mice per genotype. Two-way ANOVA for repeated measures was used in . One-way ANOVA was used in . In –, n = 3 mice per genotype. *P < 0.05; **P < 0.001; ***P < 0.0001. Data are presented as means ± s.e.m. * Figure 4: Mutant HSPB1 mice show axonal transport defects and decreased acetylated tubulin levels. () Representative fluorescent micrograph of a cultured DRG neuron loaded with a selective mitochondrial marker (MitoTracker-Red; left) and typical kymographs obtained from DRG neurons isolated from 10-month-old mice (top right, HSPB1WT; bottom right, HSPB1S135F). Stationary mitochondria are visible as straight vertical lines, whereas moving mitochondria are deflected either to the left (retrograde) or to the right (anterograde). Left scale bar, 40 μm. In right images, time (t) scale bar: 50 s; distance (d) scale bar: 25 μm. (–) Quantification of total and moving (per 200 s and per 100 μm) mitochondria in DRG neurons isolated from different transgenic lines and at different ages. Total number (,) and number of moving (,) mitochondria were determined in DRG neurons from 10-month-old (,) or 2-month-old (,) transgenic mice. n = 25–35 cells isolated from three different mice per genotype. *P < 0.05; ***P < 0.0001. () Western blots from sciatic nerves of 10-month-old mice e! xpressing HSPB1WT or mutant HSPB1 probed with antibodies to acetylated tubulin. We confirmed equal loading by staining for α-tubulin. n = 3. (,) Quantification of the optical densities of acetylated tubulin bands on western blots of sciatic nerve () and spinal cord () extracts. Signals are normalized to total α-tubulin levels. n = 3. () Acetylated α-tubulin in sciatic nerve and spinal cord of 10-month-old transgenic mice, as determined by ELISA. Signals are normalized to total α-tubulin levels. n = 3. One-way ANOVA. ***P < 0.0001. () Immunostaining of longitudinal sections of the sciatic nerve from 10-month-old mice expressing HSPB1WT (top) or HSPB1S135F (bottom) using an antibody to acetylated tubulin (green) and to peripheral myelin protein 22 (Pmp22, red). Scale bar, 40 μm. Statistical analysis of , , and was done with one-way ANOVA. Statistical analysis of and was done with Student's t test. Statistical analysis of was done with Fisher's exact test. Data are presen! ted as means ± s.e.m. * Figure 5: HDAC6 inhibition rescues axonal transport defects and restores the CMT2 phenotype. (,) Axonal transport of mitochondria measured in DRG neurons isolated from 10-month-old HSPB1S135F-expressing mice after 12 h of treatment with TSA (0.4 μM), tubacin (2 μM), tubastatin A (1 μM) or an equivalent amount of DMSO. Total number of () and number of moving () mitochondria (per 200 s and per 100 μm) were quantified. n = 20–30 cells isolated from three different mice for each condition. *P < 0.05; **P < 0.01; ***P < 0.0001. (,) Western blots of sciatic nerve and spinal cord extracts from symptomatic 8-month-old HSPB1S135F-expressing mice treated daily for 3 weeks with TSA (10 mg per kg body weight; ) or tubastatin A (25 mg per kg body weight; ) probed against acetylated tubulin. Equal loading was confirmed with α-tubulin staining. n = 3. (,) Quantifications of optical density (OD) of acetylated tubulin on western blots of sciatic nerve () and spinal cord () extracts of symptomatic HSPB1S135F-expressing mice treated with TSA or tubastatin A. n = 3. () Motor per! formance on an accelerating rotarod of HSPB1S135F-expressing mice treated for 3 weeks with TSA or tubastatin A. () Effect of the TSA or tubastatin A treatments of HSPB1S135F-expressing mice on the amplitudes of CMAPs () or SNAPs (). n = 3–6 mice per group. *P < 0.05; **P < 0.001; ***P < 0.0001. One-way ANOVA was used to analyze the data in ,. Data are presented as means ± s.e.m. * Figure 6: TSA or tubastatin A treatment leads to muscle reinnervation and rescues axonal transport defects. (,) Effect of vehicle (DMSO), TSA or tubastatin A treatment on the innervation level of the gastrocnemius muscle in symptomatic, 8-month-old HSPB1S135F-expressing mice. The number of visible neuromuscular junctions (NMJs) per axon in each field of view () and the relative quantity of denervated NMJs () were determined after staining gastrocnemius muscle with antibodies against α-bungarotoxin and neurofilament heavy chain. n = 2 or 3 mice per condition. ***P < 0.0001. (,) Axonal transport of mitochondria measured in cultured DRG neurons isolated from symptomatic HSPB1S135F-expressing mice after 3 weeks of treatment with TSA or tubastatin A. Total number () and number of moving mitochondria () were quantified (per 200 s and 100 μm). n = 20–25 cells isolated from three different mice in each condition. *P < 0.05; ***P < 0.0001. One-way ANOVA was used to analyze the data. Tukey's HSD test was used for post hoc analysis in –. Data are presented as means ± s.e.m. Author information * Abstract * Author information * Supplementary information Affiliations * Vesalius Research Center, VIB and K.U. Leuven, Campus Gasthuisberg, Leuven, Belgium. * Constantin d'Ydewalle, * Jyothsna Krishnan, * Driss M Chiheb, * Philip Van Damme, * Wim Robberecht & * Ludo Van Den Bosch * Laboratory for Neurobiology, K.U. Leuven, Leuven, Belgium. * Constantin d'Ydewalle, * Jyothsna Krishnan, * Driss M Chiheb, * Philip Van Damme, * Wim Robberecht & * Ludo Van Den Bosch * Department of Neurology, University Hospital Leuven, Leuven, Belgium. * Philip Van Damme & * Wim Robberecht * Peripheral Neuropathy Group, Department of Molecular Genetics, VIB and University of Antwerp, Antwerp, Belgium. * Joy Irobi & * Vincent Timmerman * Neurogenetics Laboratory, Institute Born Bunge, Antwerp, Belgium. * Joy Irobi & * Vincent Timmerman * Drug Discovery Program, Department of Medicinal Chemistry and Pharmacognosy, University of Illinois at Chicago, Chicago, Illinois, USA. * Alan P Kozikowski * Laboratory for Enteric Neuroscience, Translational Research Center for Gastrointestinal Disorders, K.U. Leuven, Leuven, Belgium. * Pieter Vanden Berghe Contributions C.d.Y. planned and performed all the experiments. J.K. developed the transgenic mice and did the initial characterization of the phenotype. D.M.C. provided technical support. P.V.D. assisted with the electrophysiological experiments, J.I. provided the original HSPB1 constructs, A.P.K. provided tubastatin A and P.V.B. helped with the axonal transport measurements. P.V.B., P.V.D., J.I., A.P.K., V.T. and W.R. provided ideas for the project and participated in writing the paper. L.V.D.B. planned and supervised the experiments. C.d.Y. and L.V.D.B. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Ludo Van Den Bosch Author Details * Constantin d'Ydewalle Search for this author in: * NPG journals * PubMed * Google Scholar * Jyothsna Krishnan Search for this author in: * NPG journals * PubMed * Google Scholar * Driss M Chiheb Search for this author in: * NPG journals * PubMed * Google Scholar * Philip Van Damme Search for this author in: * NPG journals * PubMed * Google Scholar * Joy Irobi Search for this author in: * NPG journals * PubMed * Google Scholar * Alan P Kozikowski Search for this author in: * NPG journals * PubMed * Google Scholar * Pieter Vanden Berghe Search for this author in: * NPG journals * PubMed * Google Scholar * Vincent Timmerman Search for this author in: * NPG journals * PubMed * Google Scholar * Wim Robberecht Search for this author in: * NPG journals * PubMed * Google Scholar * Ludo Van Den Bosch Contact Ludo Van Den Bosch Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–6 and Supplementary Methods Additional data
• Foxp3+ follicular regulatory T cells control the germinal center response
  - Nat Med 17(8):975-982 (2011)
  Nature Medicine | Article Foxp3+ follicular regulatory T cells control the germinal center response * Michelle A Linterman1, 2 * Wim Pierson3 * Sau K Lee2 * Axel Kallies4 * Shimpei Kawamoto5 * Tim F Rayner1 * Monika Srivastava2 * Devina P Divekar1 * Laura Beaton2 * Jennifer J Hogan2 * Sidonia Fagarasan5 * Adrian Liston3 * Kenneth G C Smith1, 6 * Carola G Vinuesa2, 6 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MedicineVolume: 17,Pages:975–982Year published:(2011)DOI:doi:10.1038/nm.2425Received12 January 2011Accepted27 June 2011Published online24 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Follicular helper (TFH) cells provide crucial signals to germinal center B cells undergoing somatic hypermutation and selection that results in affinity maturation. Tight control of TFH numbers maintains self tolerance. We describe a population of Foxp3+Blimp-1+CD4+ T cells constituting 10–25% of the CXCR5highPD-1highCD4+ T cells found in the germinal center after immunization with protein antigens. These follicular regulatory T (TFR) cells share phenotypic characteristics with TFH and conventional Foxp3+ regulatory T (Treg) cells yet are distinct from both. Similar to TFH cells, TFR cell development depends on Bcl-6, SLAM-associated protein (SAP), CD28 and B cells; however, TFR cells originate from thymic-derived Foxp3+ precursors, not naive or TFH cells. TFR cells are suppressive in vitro and limit TFH cell and germinal center B cell numbers in vivo. In the absence of TFR cells, an outgrowth of non–antigen-specific B cells in germinal centers leads to fewer antigen-spe! cific cells. Thus, the TFH differentiation pathway is co-opted by Treg cells to control the germinal center response. View full text Figures at a glance * Figure 1: A proportion of CXCR5highPD-1highCD4+ cells express the transcription factor Foxp3. (,) After SRBC immunization, we identified Foxp3+ cells in the CXCR5highPD-1highCD4+ TFH compartment, and these cells follow the same kinetics as classic TFH cells. () Foxp3+ cells (red) are present within the Bcl6+ germinal center area (green) following SRBC immunization. Scale bar: left 100 μm; inset scale bar, 10 μm. () Heat map comparing the gene expression profiles of different CD4+ T-cell subsets from Foxp3gfp mice 7 d after immunization. Red, high gene expression; blue, low gene expression. We sorted the cells using the following markers, which, for simplicity, will be referred by the abbreviations in parentheses throughout: CD4+CD44lowFoxp3− naive (TN) cells, CD4+CD44highCXCR5int/lowPD-1int/lowFoxp3− effector/memory (TEM) cells, CD4+CD44intCXCR5int/lowPD-1int/lowFoxp3+ regulatory T cells (Treg), CD4+CXCR5highPD-1highFoxp3− T follicular helper (TFH) cells and CD4+CXCR5highPD-1highFoxp3+ follicular regulatory (TFR) cells. () Il21 and Il4 mRNA measured by quanti! tative PCR from sorted cells using the strategy described in normalized to Gapdh. The heights of the bars represent the mean, and the error bars represent the range of expression from three biological replicates. ND, gene expression was not detected; NS, not significant. () At left, the intracellular expression of CD40L as determined by flow cytometry in Treg (blue), TFH (green) and TFR (red) cell populations; the gray histogram represents a staining control from an immunized CD40L-deficient mouse. At right, Cxcl13 mRNA measured by quantitative RT-PCR as described in . () Cell surface expression of GITR, intracellular CTLA4 and CD25 in Treg (blue), TFH (green) and TFR (red) cell populations; gray histograms represent the isotype control. () Relative Gzmb and Gzma mRNA determined by quantitative RT-PCR as described in . () Percentage of CD103+ cells within the Treg, TFH and TFR populations; each symbol represents one mouse. () At left, cell surface expression of ICOS as dete! rmined by flow cytometry in Treg (blue), TFH (green) and TFR (! red) cell populations; the gray histogram represents the staining level of an isotype control. At right, Il10 mRNA detected by quantitative RT-PCR as described in . Flow cytometric and RT-PCR data are representative of at least three independent experiments. In –, we determined statistical significance using a one-way analysis of variance (ANOVA) analysis with Bonferroni's multiple testing correction. *P < 0.05, **P < 0.01, ***P < 0.001. Error bars represent the range of expression from three biological replicates. Rel, relative. * Figure 2: TFR cells require the same differentiation cues as TFH cells for their development. (–) Flow cytometric contour plots (,,) and dot plots of TFH (,,) and TFR (,,) cells in the groups of mice described below 7 d after SRBC immunization. (–) Mixed bone marrow chimeras generated by sub-lethally irradiating Rag2−/− mice and reconstituting their immune system with a 1:1 ratio of bone marrow cells from CD45.1 Cd28+/+ and CD45.2 Cd28−/− embryos or control CD45.1 Cd28+/+ and CD45.2 Cd28+/+ mice. (–) C57BL/6 (BL/6) and B cell–deficient μMT mice. (–) Sh2d1a+/+ and Sh2d1a−/− mice. Each symbol represents one mouse, and the horizontal bars represent the median values. All contour plots are gated on CD4+ cells; percentages shown are of total CD4+ cells. Figures represent one of three independent experiments with similar results. We determined statistical significance using a Mann-Whitney U test. *P < 0.05, **P < 0.01. * Figure 3: TFR cells express Bcl-6 and Blimp-1. () Bcl6 and Prdm1 mRNA normalized to Gapdh determined by quantitative RT-PCR from sorted cells using the strategy described in Figure 1d and Supplementary Figure 1. The heights of the bars represent the mean, and the error bars represent the range of expression from three biological replicates. We determined statistical significance using a one-way ANOVA analysis with Bonferroni's multiple testing correction. *P < 0.05, **P < 0.01, ***P < 0.001. The bar graphs are representative of three experiments. () Immunofluorescence of frozen spleen sections from mice immunized 7 d previously with SRBC. The germinal center is demarcated by the white dotted line in the three consecutive sections. Upper panel, AID (red) and CD3 (green); middle panel, Foxp3 (red) and Bcl-6 (green); lower panel, Foxp3 (red) and Blimp1 (green). Scale bars, 100 μm. Inset scale bars, 10 μm. () Flow cytometric contour plots of TFH (upper panels) and TFR (lower panels) cell formation in the draining (mediasti! nal) lymph node 10 d after intranasal influenza infection of mixed fetal liver chimeras reconstituted with a 1:1 ratio of fetal liver cells from embryonic day (E) 14.5 CD45.2 Prdm1gfp/gfp:CD45.1 Prdm1+/+ embryos, E14.5 CD45.2 Bcl6−/−:CD45.1 Bcl6+/+ embryos or control E14.5 CD45.2 Prdm1gfp/+:CD45.1 Prdm1+/+ embryos. Top graphs gated on CD4+CD45.2+CD44highFoxP3−; bottom graphs gated on CD4+CD45.2+CD44highFoxP3+. * Figure 4: TFR cells derive from Foxp3+ precursors. (–) Flow cytometric contour plots of splenic CD4+CXCR5highPD-1high cells () or CD4+ cells () 7 d after 1 × 105 transferred transgenic TCR3A9 HEL-specific CD45.1 T cells were adoptively transferred into congenically distinct CD45.2 B10.Br mice and immunized with HEL in alum. Flow cytometric contour plots of splenic CD4+CXCR5highPD-1high cells () or CD4+ cells () 7 d after adoptive transfer of 1 × 105 OT-II OVA-specific Thy1.2 T cells into congenically distinct Thy1.1 C57BL6 mice and immunization with OVA in alum. () Flow cytometric contour plots of splenic CD4+ T cells from CD45.1 C57BL/6 mice 7 d after adoptive transfer of 1 × 106 sorted naive CD4+CD44intFoxp3+ Treg (top) or CD4+CD44lowFoxp3− naive T cells (bottom) from unimmunized CD45.2 Foxp3gfp mice and KLH in Ribi immunization. Transferred CD45.2 cells are shown in red, and the endogenous CD45.1 cells are represented by the gray contour plots. Histograms show Foxp3-GFP expression in transferred CD45.2+CD4+CXCR5hig! hPD-1high cells. () Contour plots of splenic CD4+ T cells and quantification of TFR cells () from Foxp3DTR mice 6 d after SRBC immunization and administration of either 0.9% saline (top) or diphtheria toxin (DT) (lower panel). Histograms show Foxp3+ cells within the CD4+CXCR5highPD-1high compartment. () Flow cytometric contour plots of splenic CD4+ cells from Foxp3-Cre × ROSA-Stop-flox-YFP mice immunized 7 d previously with SRBC (left). Shown is an enumeration of the proportion of CD4+CXCR5highPD-1high cells that expressed YFP and/or Foxp3 (right). Each symbol represents one mouse, and the horizontal bars represent the median values. Figures are representative of two to four independent experiments. * Figure 5: TFR cells regulate the size of the TFH cell population. (,) Flow cytometric contour plots of splenic CD4+ cells () and splenic B220+ cells () and graphs of TFH cells () and germinal center B cells () from the spleens of Foxp3DTR mice immunized 8 d previously (d0) with SRBC. Five days after immunization, the mice were treated with either diphtheria toxin or saline. (–) Analysis of mixed bone marrow chimeras generated by sub-lethally irradiating Rag2−/− mice and reconstituting their immune system with either a 1:1 ratio of Sh2d1a−/− CD45.2:Foxp3DTR CD45.1 bone marrow or control Sh2d1a+/+ CD45.2:Foxp3DTR CD45.1 bone marrow. Eight weeks after reconstitution, we immunized chimeric mice with SRBC and treated them with 50 μg per kg of diphtheria toxin 1 d before immunization and 2 and 5 d after immunization. We analyzed splenocytes on day 8 for the proportion and total number of CD4+CXCR5highPD-1highFoxp3+ TFR cells (), CD4+Foxp3+ Treg cells (), CD4+CXCR5highPD-1high TFH cells () and B220+GL-7highCD95high germinal center B ce! lls (). Each symbol represents one mouse, and the horizontal bars represent the median values. We determined statistical significance using a Mann-Whitney U test. *P < 0.05, **P < 0.01. D, day; WT, wild type; KO, knockout. * Figure 6: TFR cells restrict the outgrowth of non–antigen-specific clones in the germinal center. (–) Flow cytometric contour plots of splenic B220+ cells () and graphs () of total GL-7+CD95+ germinal center B cells and () NP+ germinal center B cells 10 d after immunization of Foxp3WT and Foxp3DTR mice that were treated with diphtheria toxin 6 d after NP-KLH immunization. We performed statistical analyses using a Mann-Whitney U test. The experimental outline () of the immunization and diphtheria toxin or saline treatment scheme of Foxp3DTR mice (n = 8 per group) to examine the antigen-specific immunoglobulin response over time; we bled mice before immunization and 10, 15, 20 and 28 d after the primary immunization. We gave the mice a booster immunization 24 d after the primary immunization. () ELISA analysis of NP12 and NP2 antibodies in the experiment outlined in . Error bars, s.e.m. from eight individual mice from one experiment, representative of two experiments. We performed the statistical analyses in using a two-way ANOVA with a Bonferroni post-hoc test to compar! e differences at each time point. (–) Graphs and flow cytometric contour plots gated on splenic B220+ cells () and CD11c−Gr1− bone marrow cells () of NP+ germinal center B cells (), total GL-7+CD95+ germinal center B cells () and NP+ bone marrow plasma and memory cells (,) 21 d after NP-CGG immunization of chimeric mice generated by reconstituting Rag2−/− mice with a 1:1 mix of Sh2d1a−/−:Foxp3−/−, Sh2d1a+/+:Foxp3+/+, Sh2d1a+/+:Foxp3−/− and Sh2d1a−/−:Foxp3+/+ fetal liver. We performed the statistical analyses in – using a one-way ANOVA with Bonferroni post-hoc test correction. Each symbol represents one mouse, and the horizontal bars represent the median values. *P < 0.05, **P < 0.01. Unim, unimmunized; NS, not significant. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Kenneth G C Smith & * Carola G Vinuesa Affiliations * Cambridge Institute for Medical Research and the Department of Medicine, University of Cambridge School of Clinical Medicine, Addenbrooke's Hospital, Cambridge, UK. * Michelle A Linterman, * Tim F Rayner, * Devina P Divekar & * Kenneth G C Smith * John Curtin School of Medical Research, Australian National University, Canberra, Australian Capital Territory, Australia. * Michelle A Linterman, * Sau K Lee, * Monika Srivastava, * Laura Beaton, * Jennifer J Hogan & * Carola G Vinuesa * Vlaams Instituut voor Biotechnologie and Department of Experimental Medicine, Catholic University of Leuven, Leuven, Belgium. * Wim Pierson & * Adrian Liston * Department of Immunology, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia. * Axel Kallies * Laboratory for Mucosal Immunity, RIKEN Research Center for Allergy and Immunology, Tsurumi, Yokohama, Japan. * Shimpei Kawamoto & * Sidonia Fagarasan Contributions M.A.L. designed and performed experiments, analyzed the data and wrote the manuscript. W.P. performed experiments. S.K.L. performed experiments. A.K. contributed Blimp-1 chimera experiments and reviewed the manuscript. S.K. contributed confocal microscopy images. T.F.R. performed bioinformatic analyses. M.S. performed qRT-PCR experiments. D.P.D., L.B. and J.J.H. performed experiments. S.F. contributed confocal microscopy images and reviewed the manuscript. A.L. designed experiments and reviewed the manuscript. K.G.C.S. designed experiments, wrote the manuscript and supervised the study. C.G.V. designed experiments, wrote the manuscript and supervised the study. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Carola G Vinuesa or * Adrian Liston or * Kenneth G C Smith Author Details * Michelle A Linterman Search for this author in: * NPG journals * PubMed * Google Scholar * Wim Pierson Search for this author in: * NPG journals * PubMed * Google Scholar * Sau K Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Axel Kallies Search for this author in: * NPG journals * PubMed * Google Scholar * Shimpei Kawamoto Search for this author in: * NPG journals * PubMed * Google Scholar * Tim F Rayner Search for this author in: * NPG journals * PubMed * Google Scholar * Monika Srivastava Search for this author in: * NPG journals * PubMed * Google Scholar * Devina P Divekar Search for this author in: * NPG journals * PubMed * Google Scholar * Laura Beaton Search for this author in: * NPG journals * PubMed * Google Scholar * Jennifer J Hogan Search for this author in: * NPG journals * PubMed * Google Scholar * Sidonia Fagarasan Search for this author in: * NPG journals * PubMed * Google Scholar * Adrian Liston Contact Adrian Liston Search for this author in: * NPG journals * PubMed * Google Scholar * Kenneth G C Smith Contact Kenneth G C Smith Search for this author in: * NPG journals * PubMed * Google Scholar * Carola G Vinuesa Contact Carola G Vinuesa Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information Excel files * Supplementary Table 1 (373K) Differentially expressed genes in TFR cells PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–11, Supplementary Table 2 and Supplementary Methods. Additional data
• Follicular regulatory T cells expressing Foxp3 and Bcl-6 suppress germinal center reactions
  - Nat Med 17(8):983-988 (2011)
  Nature Medicine | Article Follicular regulatory T cells expressing Foxp3 and Bcl-6 suppress germinal center reactions * Yeonseok Chung1, 2 * Shinya Tanaka1 * Fuliang Chu3 * Roza I Nurieva1 * Gustavo J Martinez1 * Seema Rawal3 * Yi-Hong Wang1 * Hoyong Lim2 * Joseph M Reynolds1 * Xiao-hui Zhou4 * Hui-min Fan4 * Zhong-ming Liu4 * Sattva S Neelapu3 * Chen Dong1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MedicineVolume: 17,Pages:983–988Year published:(2011)DOI:doi:10.1038/nm.2426Received25 December 2010Accepted27 June 2011Published online24 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Foxp3+ regulatory T (Treg) cells suppress different types of immune responses to help maintain homeostasis in the body. How Treg cells regulate humoral immunity, including germinal center reactions, is unclear. Here we identify a subset of Treg cells expressing CXCR5 and Bcl-6 that localize to the germinal centers in mice and humans. The expression of CXCR5 on Treg cells depends on Bcl-6. These CXCR5+Bcl-6+ Treg cells are absent in the thymus but can be generated de novo from CXCR5−Foxp3+ natural Treg precursors. A lack of CXCR5+ Treg cells leads to greater germinal center reactions including germinal center B cells, affinity maturation of antibodies and the differentiation of plasma cells. These results unveil a Bcl-6-CXCR5 axis in Treg cells that drives the development of follicular regulatory T (TFR) cells that function to inhibit the germinal center reactions. View full text Figures at a glance * Figure 1: CXCR5+ Treg cells co-express Bcl-6 and expand upon immunization. () Immunofluorescence imaging of Foxp3+ cells (green) in the PNA+ (red) germinal center of the draining lymph nodes from mice immunized with KLH in CFA. White arrowheads indicate Foxp3+ cells in the PNA+ area. Scale bar, 50 μm. () Flow cytometry analysis of the expression of CXCR5, BTLA and Foxp3 in CD4+ T cells among lymphoid cells from the indicated secondary lymphoid tissues of naive mice. ILN, inguinal lymph nodes; MLN, mesenteric lymph nodes; PP, Peyer's patches. (,) Expression of Bcl-6 and CXCR5 in Foxp3+ and Foxp3− CD4+ T cells analyzed in draining lymph node cells obtained 7 d after s.c. immunization with KLH in CFA (Immunized) or without immunization (Nil). Values in are means ± s.e.m. *P < 0.05; **P < 0.01 in comparison with Nil group. Numbers above outlined areas indicate the percentages of cells expressing BTLA and CXCR5 () or CXCR5 and Bcl-6 (,). In –, data represent two or three independent experiments. () Expression of CXCR5, Foxp3 and Bcl-6 in human ton! sillar CD4+ T cells. The dot plots represent the T cell staining from three donors. * Figure 2: Generation of CXCR5+Foxp3+ T cells requires Bcl-6. (,) Expression of CXCR5 and BTLA in Foxp3− () and Foxp3+ () CD4+ T cells analyzed with lymphoid cells from the draining lymph nodes (DLN) or spleen of wild-type littermate or Bcl-6−/− mice at 7 d after s.c. immunization with KLH in CFA. Numbers above outlined areas indicate the percentages of cells expressing BTLA and CXCR5. Data represent two independent experiments. * Figure 3: Characterization of CXCR5+Foxp3+ T cells. () Surface expression of the indicated molecules on CXCR5+Foxp3+ T cells. Data are gated on CD4+Foxp3+ cells and represent two independent experiments. () The relative expression levels of the indicated genes in FACS-sorted CD25hiCD4+ T cells from Bcl-6−/− mice or wild-type littermates. Data were normalized with expression amounts of Actb. Tgfb1, transforming growth factor-β1. *P < 0.05; **P < 0.01 in comparison with wild-type Treg cells. () Suppressive activity of CD25hiCD4+ T cells from Bcl-6−/− mice or wild-type littermates measured by the proliferation of T cells. Data shown are means ± s.e.m. **P < 0.01 in comparison with the naive T cell alone condition. Data represent two independent experiments. * Figure 4: Bcl-6+CXCR5+ Treg cells are generated from CXCR5− natural Treg cells in the periphery. () Expression of CXCR5, BTLA and Foxp3 in CD4+ T cells from spleen or thymus (CD4+CD8−). Numbers above outlined areas indicate the percentages of cells expressing BTLA and CXCR5. () Left, analysis of Foxp3+ and Foxp3− CD4+ T cells in the draining lymph nodes of Tcrb−/− recipients given a mixture of CD25−GITR−CD44loCD62Lhi naive CD4+ T cells (CD45.1+) and CXCR5-negative Foxp3+ T cells (CD45.2+; CXCR5− GFP+ cells from Foxp3GFP mice) after immunization with KLH in CFA. Middle, the expression of CXCR5 and Bcl-6 in Foxp3+ or Foxp3− CD4+ T cells. Right, CD45.1/CD45.2 expression in CXCR5+Bcl-6+ or CXCR5− Bcl-6− population among Foxp3+ Treg cells. Numbers next to circled areas indicate the percentages of Bcl-6+CXCR5+ or Bcl-6−CXCR5− cells. () Helios expression in CXCR5+ Treg cells. Data shown are gated on CD4+Foxp3+ cells. Data represent two independent experiments. * Figure 5: Uncontrolled germinal center reactions in scurfy mice. (,) Expression of Bcl-6 and CXCR5 on CD4+ T cells () or GL7 and CD95 on B cells () from the indicated secondary lymphoid tissues of scurfy mice and wild-type littermates (4–5 weeks old). Data are shown on the CD4 gate () or B220 gate (). Numbers above outlined areas indicate the percentages of cells expressing Bcl-6 and CXCR5 () or CD95 and GL7 (). Data represent two independent experiments. * Figure 6: Both Cxcr5−/− Treg and Bcl-6−/− Treg were inefficient in controlling germinal center reactions. (–) Expression of CD25 and Foxp3 among CD4+ T cells (), the proportion of GL7+CD95+ cells among B220+ B cells (,) and CXCR5+BTLA+ cells among the CD45.1+ population () in the draining lymph nodes of Tcrb−/− recipients given the mixture of naive CD4+ T cells (CD45.1+) and regulatory T cells (CD25hi; CD45.2+) from wild-type or Cxcr5−/− mice, followed by s.c. immunization with KLH in CFA. Numbers above outlined areas are the percentages of B220+ cells expressing CD95 and GL7 (). () Immunofluorescence imaging of Foxp3+ cells (green) in a PNA+ (red) germinal center in the draining lymph node of the recipient mice. Scale bars, 25 μm. Data were obtained 9 d after immunization and represent three independent experiments. Data in and are pooled from two independent experiments. () Levels of immunoglobulin specific for NP4 or NP26 in the sera obtained from Tcrb−/− recipients given a mixture of naive CD4+ T cells (CD45.1+) and regulatory T cells (CD25hi; CD45.2+) from wi! ld-type or Bcl-6−/− mice, followed by s.c. immunization with KLH-NP15 in CFA. () Population of NP-specific B220+ cells or B220− CD138+ plasma cells in the spleens of the Tcrb−/− recipients. Data are means ± s.e.m. (n = 5). *P < 0.05 in comparison with wild-type Treg recipients. P values in were analyzed by two-way analysis of variance. Data represent two independent experiments. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Immunology, Center for Cancer Immunology Research, The University of Texas-MD Anderson Cancer Center, Houston, Texas, USA. * Yeonseok Chung, * Shinya Tanaka, * Roza I Nurieva, * Gustavo J Martinez, * Yi-Hong Wang, * Joseph M Reynolds & * Chen Dong * Center for Immunology and Autoimmune Diseases, Institute of Molecular Medicine, The University of Texas–Health Science Center at Houston, Houston, Texas, USA. * Yeonseok Chung & * Hoyong Lim * Department of Lymphoma and Myeloma, Center for Cancer Immunology Research, The University of Texas–MD Anderson Cancer Center, Houston, Texas, USA. * Fuliang Chu, * Seema Rawal & * Sattva S Neelapu * Shanghai Dong Fang Hospital, Shanghai, China. * Xiao-hui Zhou, * Hui-min Fan & * Zhong-ming Liu Contributions Y.C. and C.D. designed the experiments and wrote the manuscript; Y.C., S.T., F.C., R.I.N., G.J.M., S.R., Y.-H.W., H.L., J.M.R., X.Z., H.F. and Z.L. performed experiments and analyzed data; S.S.N. designed and analyzed human sample data. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Chen Dong or * Yeonseok Chung Author Details * Yeonseok Chung Contact Yeonseok Chung Search for this author in: * NPG journals * PubMed * Google Scholar * Shinya Tanaka Search for this author in: * NPG journals * PubMed * Google Scholar * Fuliang Chu Search for this author in: * NPG journals * PubMed * Google Scholar * Roza I Nurieva Search for this author in: * NPG journals * PubMed * Google Scholar * Gustavo J Martinez Search for this author in: * NPG journals * PubMed * Google Scholar * Seema Rawal Search for this author in: * NPG journals * PubMed * Google Scholar * Yi-Hong Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Hoyong Lim Search for this author in: * NPG journals * PubMed * Google Scholar * Joseph M Reynolds Search for this author in: * NPG journals * PubMed * Google Scholar * Xiao-hui Zhou Search for this author in: * NPG journals * PubMed * Google Scholar * Hui-min Fan Search for this author in: * NPG journals * PubMed * Google Scholar * Zhong-ming Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Sattva S Neelapu Search for this author in: * NPG journals * PubMed * Google Scholar * Chen Dong Contact Chen Dong Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (590K) Supplementary Figures 1–8 Additional data
• Protective HIV-specific CD8+ T cells evade Treg cell suppression
  - Nat Med 17(8):989-995 (2011)
  Nature Medicine | Article Protective HIV-specific CD8+ T cells evade Treg cell suppression * Shokrollah Elahi1 * Warren L Dinges1, 2 * Nicholas Lejarcegui1 * Kerry J Laing3 * Ann C Collier4 * David M Koelle3, 4, 5, 6, 7 * M Juliana McElrath3, 4, 5, 6 * Helen Horton1, 4, 5 * Affiliations * Contributions * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:989–995Year published:(2011)DOI:doi:10.1038/nm.2422Received09 March 2011Accepted15 June 2011Published online17 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Specific human leukocyte antigens (HLAs), notably HLA-B*27 and HLA-B*57 allele groups, have long been associated with control of HIV-1. Although the majority of HIV-specific CD8+ T cells lose proliferative capacity during chronic infection, T cells restricted by HLA-B*27 or HLA-B*57 allele groups do not. Here we show that CD8+ T cells restricted by 'protective' HLA allele groups are not suppressed by Treg cells, whereas, within the same individual, T cells restricted by 'nonprotective' alleles are highly suppressed ex vivo. This differential sensitivity of HIV-specific CD8+ T cells to Treg cell–mediated suppression correlates with their expression of the inhibitory receptor T cell immunoglobulin domain and mucin domain 3 (Tim-3) after stimulation with their cognate epitopes. Furthermore, we show that HLA-B*27– and HLA-B*57–restricted effectors also evade Treg cell–mediated suppression by directly killing Treg cells they encounter in a granzyme B (GzmB)-dependent mann! er. This study uncovers a previously unknown explanation for why HLA-B*27 and HLA-B*57 allele groups are associated with delayed HIV-1 disease progression. View full text Figures at a glance * Figure 1: Treg cell suppression of in vitro proliferative ability or cytokine secretion of CD8+ T cells restricted by HLA-B*57, HLA-B*27, HLA-A*03 and control HLAs (HLA-A*02, HLA-A*24 and HLA-B*08). () Background-subtracted percentage CFSEloCD8+ T cells in PBMCs with or without Treg cells when cultured in the presence of HIV-1 epitopes recognized by CD8+ T cells restricted by various HLA alleles. () Background-subtracted HIV-specific IFN-γ ELISPOT responses in the presence and absence of Treg cells. HLA-B*27 or HLA-B*57–restricted and non–HLA-B*27– and HLA-B*57–restricted responses are shown after stimulation with their cognate epitopes. SFC, spot-forming cell. In and , Wilcoxon signed-rank (WSR) test was used. () Percentage suppression of proliferation grouped according to HLA restricting allele. () Percentage suppression of cytokine secretion grouped according to HLA restricting allele. In and , Kruskal-Wallis (KW) test was used for grouped comparisons with a post hoc Dunn's test showing significant subgroup comparisons with horizontal lines. () Differential suppression of proliferation of HLA-B*27– and HLA-B*57– versus HLA-A*03– and control HLA–restr! icted HIV-specific CD8+ CTLs within the same person. NP02 and NP41 are two LTNPs. () Percentage suppression of proliferation by Treg cells of HLA-B*57–restricted CD8+ CTLs in HLA-B*57+ LTNP versus HLA-B*57+ delayed progressors (DP). () Longitudinal analyses of percentage suppression of proliferation by Treg cells of HLA-B*57–restricted CD8+ CTLs before and after progression in HLA-B*57++ individuals. * Figure 2: Frequency of CD8+Tim-3+ T cells following stimulation with their cognate epitopes. () Percentage of Tim-3+ CD8+ T cells using allophycocyanin-labeled HLA-A*03–RLRPGGKKK tetramer or phycoerythrin-labeled HLA-B*57-TSTLQEQIGW tetramer staining of PBMCs before and after stimulation with their cognate epitopes. Top right quadrant shows percentage of Tim-3+ tetramer+ CD8+ CTLs. () Percentage of Tim-3+ on CD8+ T cells using CD137 to identify antigen-specific T cells after stimulation with their cognate epitopes. () Percentage of CD137+Tim-3+ T cells after stimulation of PBMCs from different individuals with their corresponding epitopes. * Figure 3: CFSE dilution data showing inhibition of Gal-9–Tim-3 interactions by lactose and siRNA. () Examples of proliferation of PBMCs stimulated with their corresponding epitopes, showing percentage CFSEloCD8+ T cells in the absence or presence of lactose. () Examples of proliferation of CFSE-labeled, Treg cell–depleted PBMCs stimulated with their cognate epitopes in the presence of Treg cells treated with either LGALS9 siRNA or siControl (at 1:0.25 ratio). The measures of coculture suppression by Treg cells in the presence or absence of lactose or siRNA are shown for a representative experiment from three repeat experiments for each approach. () Percentage of Treg cell suppression calculated after stimulation of CD8+ T cells with their corresponding epitopes in the presence of lactose. () Percentage of Treg cell suppression calculated after stimulation of CD8+ T cells with their cognate epitopes in the presence of LGALS9 siRNA–treated Treg cells (at 1:0.25 ratio). * Figure 4: CFSE dilution data showing CD8+ T cells restricted by HLA-B*57 and HLA-B*27 resist Treg cell-mediated suppression in a GzmB dependent manner. () Percentage CFSEloCD8+ T cells after CFSE-labeled isolated CD8+ T cells were stimulated with their corresponding epitopes alone or together with Treg cells (at 1:0.25 ratio), and also in the presence or absence of a GzmB peptide inhibitor (z-AAD-CMK). Examples of flow data are shown in Supplementary Figure 3a. () Percentage CFSEloCD8+ T cells after electroporation with GZMB siRNA or nonhybridizing negative control (siControl) siRNA oligonucleotides and stimulation with their cognate epitopes alone or with Treg cells (at 1:0.25 ratio). Examples of flow data are shown in Supplementary Figure 3b. * Figure 5: CD8+ T cells restricted by HLA-B*27 and HLA-B*57 induce Treg apoptosis in a GzmB-dependent manner. (–) Percentage annexin V+ Treg cells (CD3+CD4+CD25hiCD127lo) in PBMCs stimulated for 4 d (), 24 h () or 24–72 h () with HLA-B*27–, HLA-B*57–, HLA-B*39– or HLA-A*03–restricted epitopes in the presence or absence of GzmB peptide inhibitor. These data are representative of three separate experiments from different LTNPs. () Percentage annexin V+ Treg cells in PBMCs stimulated with HLA-B*57–restricted epitopes from HLA-B*57+ LTNP versus HLA-B*57+ DPs. (,) Percentage annexin V+ Treg cells in PBMCs stimulated with HLA-B*57–restricted epitopes before and after progression to disease. () Treg cell frequencies in HIV-1–seronegative individuals versus HIV-1 infected HLA-B*27++ or HLA-B*57+ and HLA-B*27−− or HLA-B*57− LTNPs. Percentages of CD4+CD25hiFOXP3+ Treg cells are shown in PBMCs from 12 HIV-seronegative HLA-B*27+ or HLA-B*57+ individuals, 12 HLA-B*27− or HLA-B*-57− individuals, 13 HLA-B*27++ or HLA-B*57+ LTNPs and 8 HLA-B*27− or HLA-B*57− LTNPs. * Figure 6: Model depicting how HLA-B*27– or HLA-B*57–restricted HIV-specific CD8+ T cells evade Treg cell suppression and subsequently control HIV replication. HIV-specific, HLA-B*27–restricted CD8+ T cells do not upregulate surface expression of Tim-3 upon recognition of their cognate epitopes on HIV-infected CD4+ T cells, whereas HIV-specific, HLA-A*03–restricted CD8+ T cells upregulate high surface expression of Tim-3. Treg cells suppress HLA-A*03–restricted CD8+ T cells owing to their high expression of Tim-3 but cannot suppress proliferation of HLA-B*27–restricted CD8+ T cells. Highly proliferating HLA-B*27–restricted CD8+ T cells upregulate high levels of GzmB and kill not only infected CD4+ T cells but also infected Treg cells that they encounter. Thus, HLA-B*27–restricted CD8+ T cells can control HIV replication during chronic infection, whereas HLA-A*03–restricted CD8+ T cells cannot. Author information * Abstract * Author information * Supplementary information Affiliations * Viral Vaccine Program, Seattle Biomedical Research Institute (Seattle Biomed), Seattle, Washington, USA. * Shokrollah Elahi, * Warren L Dinges, * Nicholas Lejarcegui & * Helen Horton * Polyclinic Infectious Disease, Seattle, Washington, USA. * Warren L Dinges * Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. * Kerry J Laing, * David M Koelle & * M Juliana McElrath * Department of Medicine, University of Washington, Seattle, Washington, USA. * Ann C Collier, * David M Koelle, * M Juliana McElrath & * Helen Horton * Department of Global Health Medicine, University of Washington, Seattle, Washington, USA. * David M Koelle, * M Juliana McElrath & * Helen Horton * Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA. * David M Koelle & * M Juliana McElrath * Benaroya Research Institute, Seattle, Washington, USA. * David M Koelle Contributions S.E. designed and performed all the experiments and wrote part of the manuscript. N.L. assisted S.E. to perform some of the experiments. W.L.D. performed statistical analysis and graphing design. K.J.L. performed epitope mapping for individuals infected with HSV. D.M.K. advised on the HSV experiment. D.M.K., K.J.L., M.J.M. and A.C.C. supplied samples from subjects. H.H. designed and supervised all of the research and wrote the manuscript. All authors revised and edited the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Helen Horton Author Details * Shokrollah Elahi Search for this author in: * NPG journals * PubMed * Google Scholar * Warren L Dinges Search for this author in: * NPG journals * PubMed * Google Scholar * Nicholas Lejarcegui Search for this author in: * NPG journals * PubMed * Google Scholar * Kerry J Laing Search for this author in: * NPG journals * PubMed * Google Scholar * Ann C Collier Search for this author in: * NPG journals * PubMed * Google Scholar * David M Koelle Search for this author in: * NPG journals * PubMed * Google Scholar * M Juliana McElrath Search for this author in: * NPG journals * PubMed * Google Scholar * Helen Horton Contact Helen Horton Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (4M) Supplementary Figures 1–6 and Supplementary Tables 1 and 2 Additional data
• DNA released from dying host cells mediates aluminum adjuvant activity
  - Nat Med 17(8):996-1002 (2011)
  Nature Medicine | Article DNA released from dying host cells mediates aluminum adjuvant activity * Thomas Marichal1, 2 * Keiichi Ohata3 * Denis Bedoret1, 2 * Claire Mesnil1, 2 * Catherine Sabatel1, 2 * Kouji Kobiyama3, 4 * Pierre Lekeux1, 2 * Cevayir Coban3 * Shizuo Akira3 * Ken J Ishii3, 4, 5 * Fabrice Bureau1, 2, 5 * Christophe J Desmet1, 2, 5 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MedicineVolume: 17,Pages:996–1002Year published:(2011)DOI:doi:10.1038/nm.2403Received11 February 2011Accepted19 May 2011Published online17 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Aluminum-based adjuvants (aluminum salts or alum) are widely used in human vaccination, although their mechanisms of action are poorly understood. Here we report that, in mice, alum causes cell death and the subsequent release of host cell DNA, which acts as a potent endogenous immunostimulatory signal mediating alum adjuvant activity. Furthermore, we propose that host DNA signaling differentially regulates IgE and IgG1 production after alum-adjuvanted immunization. We suggest that, on the one hand, host DNA induces primary B cell responses, including IgG1 production, through interferon response factor 3 (Irf3)-independent mechanisms. On the other hand, we suggest that host DNA also stimulates 'canonical' T helper type 2 (TH2) responses, associated with IgE isotype switching and peripheral effector responses, through Irf3-dependent mechanisms. The finding that host DNA released from dying cells acts as a damage-associated molecular pattern that mediates alum adjuvant activit! y may increase our understanding of the mechanisms of action of current vaccines and help in the design of new adjuvants. View full text Figures at a glance * Figure 1: Alum induces cell death and release of host DNA at sites of injection. () Quantity of free dsDNA in the acellular fraction of the peritoneal lavage fluid of mice treated i.p. with increasing doses of alum, measured over time using quantitative fluorescent dsDNA stain. () Confocal microscopic imaging of extracellular DNA deposition in alum macroscopic i.p. depots stained with 4′,6-diamidino-2-phenylindole (DAPI). Scale bars, 25 μm. () Cell death rate in the peritoneal lavage fluid of mice treated i.p. with increasing doses of alum, assessed by staining with 7-aminoactinomycin D (7-AAD) and flow cytometry. n = 5 (,). Data are representative of one of three independent experiments. Error bars show means ± s.d. *P < 0.05, **P < 0.01, ***P < 0.001. * Figure 2: Host DNA released by alum cytotoxicity mediates alum adjuvant activity on humoral and TH2 cell responses. (–) Serum titers of OVA-specific IgM (OVA-IgM; ,), IgG1 (OVA-IgG1; ,) and IgE (OVA-IgE; ,). Titers were measured on the indicated days in (–) mice immunized i.p. with OVA alone, OVA and alum, or OVA and DNA on days 0 and 14, and boosted with OVA on d 21; or in (–) mice immunized i.p. with OVA or OVA and alum, treated i.p. with DNase I both 3 and 18 h later, and then boosted with OVA 10 d later. () Proliferation profile (top) and division index (bottom) of adoptively transferred CFSE-labeled OVA-specific CD4+ OT-II cells in the bronchial lymph nodes of mice treated i.p. with OVA, OVA and DNA, OVA and alum, or OVA and alum followed by DNase I treatment. Inserted numbers indicate division index values. n = 5; data are representative of one of two (–) or three (–) independent experiments. Error bars show means ± s.d. *, OVA versus OVA and adjuvant; °, OVA and alum versus OVA and alum followed by DNase I treatment; *,°P < 0.05, **,°°P < 0.01, ***,°°°P < 0.001. a! .u., arbitrary unit. NS, not significant. * Figure 3: Alum and host genomic DNA trigger type I IFN secretion and IgE responses through activation of the Tbk1-Irf3 axis. (,) Quantities of () IFN-β1 and () IL-1β in the peritoneal lavage fluid over time by ELISA in WT mice treated i.p. with OVA, OVA and DNA, or OVA and alum. (–) Serum titers of OVA-specific IgE (,) and IgG1 (,) measured on day 28 in WT and Irf3−/− mice immunized i.p. with OVA, OVA and alum (,), or OVA and DNA (,) on days 0 and 14, and then boosted with OVA on day 21. (,) Serum titers of OVA-specific IgE () and IgG1 () measured on day 28 in Tbk1+/−/Tnf−/− and Tbk1−/−/Tnf−/− mice immunized i.p. with OVA and alum on days 0 and 14, and then boosted with OVA on day 21. n = 5; data are representative of one of three independent experiments. Error bars show means ± s.d. *P < 0.05, **P < 0.01, ***P < 0.001. a.u., arbitrary unit. * Figure 4: Irf3 is essential for the boosting of canonical TH2 cells by alum and genomic DNA. () Proliferation profile (left) and division index (right) of adoptively transferred OVA-specific CD4+ OT-II cells in the BLNs of WT and Irf3−/− mice treated i.p. with OVA, OVA and DNA, or OVA and alum. Inserted numbers indicate division index values. () Cytokine concentrations in the supernatant of OVA-stimulated BLN cells isolated from WT and Irf3−/− mice treated with OVA, OVA and DNA, or OVA and alum. (–) Assessment of allergic airway inflammation in OVA- or OVA and alum–sensitized WT and Irf3−/− mice challenged with aerosolized OVA. () Total and differential immune cell counts in the bronchoalveolar lavage fluid (BALF). () Representative section and inflammatory scores of hematoxylin-eosin staining of lung sections. Scale bar, 50 μm. () Representative staining and percentage of periodic acid Schiff (PAS)-stained goblet cells per total epithelial cells in randomly selected bronchi. Scale bar, 50 μm. n = 5; data are representative of one of two () or thre! e (–) independent experiments. Error bars show means ± s.d. *, OVA versus OVA and adjuvant; °, WT OVA and adjuvant versus Irf3−/− OVA and adjuvant; *,°P < 0.05, **,°°P < 0.01, ***P < 0.001. * Figure 5: Deficient migration of inflammatory monocytes impairs alum-induced TH2 and IgE responses in Irf3−/− mice. () Flow cytometric assessment of the numbers of iDCs, cDCs and pDCs in the BLNs of WT and Irf3−/− mice 24 h after i.p. injection of OVA or OVA and alum. () Recruitment of iDCs to the BLNs of WT and Irf3−/− mice treated i.p. with OVA, OVA and DNA, or OVA and alum. () Correlation between the percentage of cell death (assessed as in Fig. 1c), DNA release (assessed as in Fig. 1a), and the recruitment of iDCs to the BLN (assessed as in , at 24 h) of WT mice treated with alum for 24 h. () Proliferation profile (left) and division index (right) of adoptively transferred OVA-specific CD4+ OT-II cells in the BLNs of Irf3−/− mice that received OVA and alum and an adoptive transfer of WT iMonos obtained from the peritoneal cavity of OVA and alum–treated WT mice. Inserted numbers indicate division index values. () Cytokine concentrations in the supernatant of OVA-stimulated BLN cells isolated from Irf3−/− mice that received OVA and alum and an adoptive transfer of WT i! Monos obtained as in . (,) Serum titers of OVA-specific IgE () and IgG1 () in Irf3−/− mice treated with OVA and alum, transferred with WT iMonos as in on days 0 and 14, and then boosted with OVA on day 21. As controls, we used WT and Irf3−/− mice that received PBS with OVA alone or OVA and alum. () Numbers of CFSE+ iDCs in the BLNs of OVA and alum–treated WT mice that received CFSE-labeled WT or Irf3−/− iMonos 18 h earlier. Control mice received PBS alone. n = 5; data are representative of one of four (,), one of three (–) or one of two (,,) independent experiments. Error bars show means ± s.d. #, WT OVA and adjuvant versus Irf3−/− OVA and adjuvant (,); *,°P < 0.05, **,°°P < 0.01, ***,°°°P < 0.001. a.u., arbitrary unit. * Figure 6: Alum-induced iMono migration depends on IL-12p40 homodimer signaling. () Gating strategy for iMonos and flow cytometric analysis of their surface expression of CCR7 and co-stimulatory molecules in OVA and alum–treated WT and Irf3−/− mice. Bottom right, percentage of CCR7hi iMonos in OVA and alum–treated WT and Irf3−/− mice is indicated. () ELISA measurement of IL-12p70, IL-23 and IL-12p80 in the acellular phase of the peritoneal lavage fluid of WT and Irf3−/− mice treated overnight with OVA or with OVA and alum. #, WT OVA and alum versus Irf3−/− OVA and alum. (,) Recruitment of iDCs to the BLNs of WT and Irf3−/− mice treated with OVA and alum and recombinant IL-12p80 (rIL12p80) () or p40-specific neutralizing antibody (). Control OVA- and OVA and alum–treated mice received PBS only. (,) Serum titers of OVA-specific IgE () and IgG1 () measured on day 17 in WT mice treated i.p. with OVA and alum and p40-specific neutralizing antibody, and then boosted with OVA i.p. 10 d later. n = 5; data are representative of one of th! ree () or two (–) independent experiments. Error bars show means ± s.d. *P < 0.05, **°P < 0.01, ***P < 0.001. a.u., arbitrary unit. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Ken J Ishii, * Fabrice Bureau & * Christophe J Desmet Affiliations * Laboratory of Cellular and Molecular Physiology, Groupe Interdisciplinaire de Génoprotéomique Appliquée, University of Liège, Liège, Belgium. * Thomas Marichal, * Denis Bedoret, * Claire Mesnil, * Catherine Sabatel, * Pierre Lekeux, * Fabrice Bureau & * Christophe J Desmet * Laboratory of Biochemistry, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium. * Thomas Marichal, * Denis Bedoret, * Claire Mesnil, * Catherine Sabatel, * Pierre Lekeux, * Fabrice Bureau & * Christophe J Desmet * World Premier International Immunology Frontier Research Center, Osaka University, Osaka, Japan. * Keiichi Ohata, * Kouji Kobiyama, * Cevayir Coban, * Shizuo Akira & * Ken J Ishii * Laboratory of Adjuvant Innovation, National Institute of Biomedical Innovation, Osaka, Japan. * Kouji Kobiyama & * Ken J Ishii Contributions T.M., K.J.I., F.B. and C.J.D. designed the experiments; C.C., K.J.I., F.B. and C.J.D. supervised the project; T.M. and D.B. made the initial observation; T.M. did most of the experiments and compiled the data; T.M., K.O. and K.K. did the experiments involving Tbk1/Tnf double-knockout mice, Zbp1−/−, Ifnar2−/− and Mavs−/− mice; C.M. and C.S. did the FACS analyses; S.A. provided the Tbk1/Tnf double-knockout mice and Zbp1−/− mice; P.L., S.A., K.J.I. and F.B. secured funding; K.J.I. and F.B. provided feedback on the manuscript; and C.J.D. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Christophe J Desmet or * Ken J Ishii Author Details * Thomas Marichal Search for this author in: * NPG journals * PubMed * Google Scholar * Keiichi Ohata Search for this author in: * NPG journals * PubMed * Google Scholar * Denis Bedoret Search for this author in: * NPG journals * PubMed * Google Scholar * Claire Mesnil Search for this author in: * NPG journals * PubMed * Google Scholar * Catherine Sabatel Search for this author in: * NPG journals * PubMed * Google Scholar * Kouji Kobiyama Search for this author in: * NPG journals * PubMed * Google Scholar * Pierre Lekeux Search for this author in: * NPG journals * PubMed * Google Scholar * Cevayir Coban Search for this author in: * NPG journals * PubMed * Google Scholar * Shizuo Akira Search for this author in: * NPG journals * PubMed * Google Scholar * Ken J Ishii Contact Ken J Ishii Search for this author in: * NPG journals * PubMed * Google Scholar * Fabrice Bureau Search for this author in: * NPG journals * PubMed * Google Scholar * Christophe J Desmet Contact Christophe J Desmet Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–17 and Supplementary Methods Additional data
• Carvedilol and its new analogs suppress arrhythmogenic store overload–induced Ca2+ release
  - Nat Med 17(8):1003-1009 (2011)
  Nature Medicine | Article Carvedilol and its new analogs suppress arrhythmogenic store overload–induced Ca2+ release * Qiang Zhou1, 2, 8 * Jianmin Xiao1, 8 * Dawei Jiang1 * Ruiwu Wang1 * Kannan Vembaiyan3 * Aixia Wang3 * Chris D Smith3 * Cuihong Xie1, 2, 8 * Wenqian Chen1 * Jingqun Zhang2 * Xixi Tian1 * Peter P Jones1, 8 * Xiaowei Zhong1 * Ang Guo4 * Haiyan Chen2 * Lin Zhang1 * Weizhong Zhu5 * Dongmei Yang6 * Xiaodong Li7 * Ju Chen7 * Anne M Gillis1 * Henry J Duff1 * Heping Cheng6, 8 * Arthur M Feldman5 * Long-Sheng Song4 * Michael Fill2 * Thomas G Back3 * S R Wayne Chen1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:1003–1009Year published:(2011)DOI:doi:10.1038/nm.2406Received10 February 2011Accepted23 May 2011Published online10 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Carvedilol is one of the most effective beta blockers for preventing ventricular tachyarrhythmias in heart failure, but the mechanisms underlying its favorable antiarrhythmic benefits remain unclear. Spontaneous Ca2+ waves, also called store overload–induced Ca2+ release (SOICR), evoke ventricular tachyarrhythmias in individuals with heart failure. Here we show that carvedilol is the only beta blocker tested that effectively suppresses SOICR by directly reducing the open duration of the cardiac ryanodine receptor (RyR2). This unique anti-SOICR activity of carvedilol, combined with its beta-blocking activity, probably contributes to its favorable antiarrhythmic effect. To enable optimal titration of carvedilol's actions as a beta blocker and as a suppressor of SOICR separately, we developed a new SOICR-inhibiting, minimally beta-blocking carvedilol analog, VK-II-86. VK-II-86 prevented stress-induced ventricular tachyarrhythmias in RyR2-mutant mice and did so more effectivel! y when combined with either of the selective beta blockers metoprolol or bisoprolol. Combining SOICR inhibition with optimal beta blockade has the potential to provide antiarrhythmic therapy that can be tailored to individual patients. View full text Figures at a glance * Figure 1: Carvedilol inhibits SOICR in HEK293 cells. () The percentage of HEK293 cells (120–370 cells tested) in which SOICR was completely inhibited (n = 3–7). Cells were treated with the indicated beta blockers (30 μM) () or with prazosin (30 μM), phentolamine (30 μM), N-(2-mercaptopropionyl)-glycine (MPG, 1 mM), α-tocopherol (600 μM) or DMSO (control) (). () Fura-2 ratios of representative HEK293 cells treated with carvedilol () or metoprolol () (n = 3–8). () The percentage of cells with SOICR treated with metoprolol (210 cells tested) or carvedilol (1,027 cells tested) at the indicated concentrations. Error bar values are means ± s.e.m. **P < 0.01; versus metoprolol. * Figure 2: Carvedilol modifies the gating of single RyR2 channels. () Open probability (Po), mean open time (OT), mean closed time (CT) and event frequency (s−1) of native RyR2s from rat sarcoplasmic reticulum microsomes () or purified recombinant RyR2 R4496C channels () without (control) or with carvedilol. Tracings show single-channel currents. Openings are downward. Baselines are indicated (short bars). *P < 0.05; **P < 0.01; versus control. Error bar values are means ± s.e.m. * Figure 3: Carvedilol suppresses SOICR in mouse ventricular cardiomyocytes. () Line-scan confocal imaging of R4496C-heterozygous ventricular cardiomyocytes treated with the indicated agents for 30 min in the presence of 6 mM external Ca2+ (the height of each image represents 71.4 μm). (–) In cells treated with the indicated agents, the percentage of cells with SOICR (), the frequency of SOICR () and sarcoplasmic reticulum (SR) Ca2+ content (). () Single-cell epifluorescence imaging of SOICR in the presence of DMSO, metoprolol or carvedilol. (,) In cells (187–202 cells tested) treated with the indicated agents for 30 min (n = 6 separate experiments), the percentage of cells with SOICR () and SOICR frequency (). (,) In cells (147–225 cells tested) treated with the indicated agents for 3 h (n = 4–6 separate experiments), the percentage cells with SOICR () and SOICR frequency (). *P < 0.05; **P < 0.01; versus DMSO. Error bar values are means ± s.e.m. * Figure 4: Effect of VK-II-86 on heart rate, SOICR and single RyR2 channels. () Chemical structures of carvedilol and VK-II-86. () Isoproterenol (Iso)-stimulated heart rate () and unstimulated heart rate () in R4496C-heterozygous mice (n = 7–12 in each group) treated with the indicated agents (mg per kg body weight (BW) or mg per kg (BW) per day for 5 d). () The percentage of HEK293-R4496C cells with SOICR after treatment with DMSO or VK-II-86 (30 μM) (515 cells tested; n = 10 separate experiments. () Line-scan confocal imaging of SOICR in R4496C-heterozygous ventricular cardiomyocytes treated with VK-II-86 for 30 min. The percentage of cells with SOICR, the frequency of SOICR and sarcoplasmic reticulum (SR) Ca2+ content with the indicated agents are shown. (,) Single-cell epifluorescence imaging of SOICR in R4496C-heterozygous cardiomyocytes (177–208 cells tested) treated with VK-II-86 for 30 min (n = 6 separate experiments; ) or for 3 h (n = 6 separate experiments; ). The percentage of cells with SOICR and the frequency of SOICR with the indic! ated agents are shown. () Po, mean OT, mean CT and event frequency (s−1) of single purified RyR2 R4496C channels preincubated (1 h) with VK-II-86 (1 μM) or control (no treatment). *P < 0.05; **P < 0.01; versus DMSO or control. #P < 0.05; ##P < 0.01; versus carvedilol. Error bar values are means ± s.e.m. NS, not significant. * Figure 5: Effects of VK-II-86 on CPVT in R4496C-heterozygous or homozygous mice. () Representative electrocardiogram (ECG) recordings of WT () and R4496C-heterozygous mutant () mice before and after intraperitoneal injection of epinephrine (1.6 mg per kg body weight (BW)) and caffeine (120 mg per kg body weight) (epi/caff). () Ventricular tachyarrhythmia (VT) duration in WT or in R4496C-heterozygous mice (n = 12–33) per 3-min () or 30-min period () of ECG recordings (**P < 0.01 versus WT). () Representative ECG recordings of R4496C-heterozygous mice treated with VK-II-86 before and after the administration of arrhythmic triggers. () VT duration in R4496C-heterozygous mice treated with the indicated agents (mg kg−1 d−1 for 5 d). *P < 0.01 versus DMSO. () VT duration per 3-min period in RyR2 R4496C-homozygous mice post-treated with the indicated agents (*P < 0.05; **P < 0.01; versus DMSO). () VT duration in R4496C-heterozygous mice treated with the indicated agents (mg per kg body weight per day for 5 d). *P < 0.05; **P < 0.01; versus DMSO. ##P < 0.0! 1; versus VK-II-86 plus metoprolol. $P < 0.05; $$P < 0.01; versus VK-II-86 plus bisoprolol. Error bar values are means ± s.e.m. * Figure 6: Effects of CS-I-34 and CS-I-59 on heart rate, SOICR and CPVT. () Chemical structures of CS-I-34 and CS-I-59. () Isoproterenol (Iso)-stimulated heart rate and () unstimulated heart rates in R4496C-heterozygous mice treated with the indicated agents (mg per kg body weight (BW) or mg per kg (BW) per day for 5 d). () Single-cell epifluorescence imaging of SOICR in R4496C-heterozygous ventricular cardiomyocytes (141–144 cells tested) treated with drugs for 30 min (n = 4 separate experiments). The percentage of cells with SOICR and the frequency of SOICR with the indicated agents are shown. () The percentage of HEK293 cells expressing RyR2 R4496C (137–457 cells tested) with SOICR in the presence of the indicated agents (n = 5–9 separate experiments) at the indicated concentrations. () Ventricular tachyarrhythmia duration in R4496C-heterozygous mice treated with drugs (mg kg−1 d−1 for 5 d). *P < 0.05; **P < 0.01; versus DMSO or control. ##P < 0.01; versus carvedilol. Error bar values are means ± s.e.m. Author information * Abstract * Author information * Supplementary information Affiliations * Libin Cardiovascular Institute of Alberta, Department of Physiology and Pharmacology, University of Calgary, Calgary, Alberta, Canada. * Qiang Zhou, * Jianmin Xiao, * Dawei Jiang, * Ruiwu Wang, * Cuihong Xie, * Wenqian Chen, * Xixi Tian, * Peter P Jones, * Xiaowei Zhong, * Lin Zhang, * Anne M Gillis, * Henry J Duff & * S R Wayne Chen * Department of Molecular Biophysics and Physiology, Rush University Medical Center, Chicago, Illinois, USA. * Qiang Zhou, * Cuihong Xie, * Jingqun Zhang, * Haiyan Chen, * Michael Fill & * S R Wayne Chen * Department of Chemistry, University of Calgary, Calgary, Alberta, Canada. * Kannan Vembaiyan, * Aixia Wang, * Chris D Smith & * Thomas G Back * Division of Cardiovascular Medicine, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA. * Ang Guo & * Long-Sheng Song * Department of Medicine, Center for Translational Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, USA. * Weizhong Zhu & * Arthur M Feldman * Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA. * Dongmei Yang & * Heping Cheng * Department of Medicine, University of California at San Diego, La Jolla, California, USA. * Xiaodong Li & * Ju Chen * Present addresses: Department of Cardiology of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (Q.Z.); Department of Cardiology, Taiping People's Hospital of Dongguan, Guangdong, China (J.X.); Department of Emergency of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (C.X.); Department of Physiology, University of Otago, Dunedin, New Zealand (P.P.J.); Institute of Molecular Medicine, Peking University, Beijing, China (H. Cheng). * Qiang Zhou, * Jianmin Xiao, * Cuihong Xie, * Peter P Jones & * Heping Cheng Contributions Q.Z., J.X., D.J., R.W., K.V., A.W., C.D.S., W.Z., D.Y., J.C., A.M.G., H.J.D., H. Cheng, A.M.F., L.-S.S., M.F., T.G.B. and S.R.W.C. designed research; Q.Z., J.X., D.J., R.W., K.V., A.W., C.D.S., C.X., W.C., J.Z., W.Z., X.T., P.P.J., X.Z., A.G., H. Chen, L.Z., D.Y. and X.L. carried out research; Q.Z., J.X., D.J., C.X., W.C., J.Z., W.Z., X.T., P.P.J., X.Z., A.G., H. Chen, L.Z. and D.Y. analyzed data; and Q.Z., R.W., C.D.S., W.Z., M.F., T.G.B. and S.R.W.C. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * S R Wayne Chen Author Details * Qiang Zhou Search for this author in: * NPG journals * PubMed * Google Scholar * Jianmin Xiao Search for this author in: * NPG journals * PubMed * Google Scholar * Dawei Jiang Search for this author in: * NPG journals * PubMed * Google Scholar * Ruiwu Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Kannan Vembaiyan Search for this author in: * NPG journals * PubMed * Google Scholar * Aixia Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Chris D Smith Search for this author in: * NPG journals * PubMed * Google Scholar * Cuihong Xie Search for this author in: * NPG journals * PubMed * Google Scholar * Wenqian Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Jingqun Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Xixi Tian Search for this author in: * NPG journals * PubMed * Google Scholar * Peter P Jones Search for this author in: * NPG journals * PubMed * Google Scholar * Xiaowei Zhong Search for this author in: * NPG journals * PubMed * Google Scholar * Ang Guo Search for this author in: * NPG journals * PubMed * Google Scholar * Haiyan Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Lin Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Weizhong Zhu Search for this author in: * NPG journals * PubMed * Google Scholar * Dongmei Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Xiaodong Li Search for this author in: * NPG journals * PubMed * Google Scholar * Ju Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Anne M Gillis Search for this author in: * NPG journals * PubMed * Google Scholar * Henry J Duff Search for this author in: * NPG journals * PubMed * Google Scholar * Heping Cheng Search for this author in: * NPG journals * PubMed * Google Scholar * Arthur M Feldman Search for this author in: * NPG journals * PubMed * Google Scholar * Long-Sheng Song Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Fill Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas G Back Search for this author in: * NPG journals * PubMed * Google Scholar * S R Wayne Chen Contact S R Wayne Chen Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–10, Supplementary Table 1 and Supplementary Methods Additional data
• Imaging the subcellular structure of human coronary atherosclerosis using micro–optical coherence tomography
  - Nat Med 17(8):1010-1014 (2011)
  Nature Medicine | Technical Report Imaging the subcellular structure of human coronary atherosclerosis using micro–optical coherence tomography * Linbo Liu1, 2 * Joseph A Gardecki1, 2 * Seemantini K Nadkarni1, 2, 3 * Jimmy D Toussaint1, 2 * Yukako Yagi1, 4 * Brett E Bouma1, 2, 3 * Guillermo J Tearney1, 3, 4 * Affiliations * Contributions * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:1010–1014Year published:(2011)DOI:doi:10.1038/nm.2409Received28 June 2010Accepted10 February 2011Published online10 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Progress in understanding, diagnosis, and treatment of coronary artery disease (CAD) has been hindered by our inability to observe cells and extracellular components associated with human coronary atherosclerosis in situ. The current standards for microstructural investigation, histology and electron microscopy are destructive and prone to artifacts. The highest-resolution intracoronary imaging modality, optical coherence tomography (OCT), has a resolution of ~10 μm, which is too coarse for visualizing most cells. Here we report a new form of OCT, termed micro–optical coherence tomography (μOCT), whose resolution is improved by an order of magnitude. We show that μOCT images of cadaver coronary arteries provide clear pictures of cellular and subcellular features associated with atherogenesis, thrombosis and responses to interventional therapy. These results suggest that μOCT can complement existing diagnostic techniques for investigating atherosclerotic specimens, and ! that μOCT may eventually become a useful tool for cellular and subcellular characterization of the human coronary wall in vivo. View full text Figures at a glance * Figure 1: μOCT images of a fibrocalcific human cadaver coronary plaque. (–) Comparison between corresponding OCT (), μOCT () and histology images (, H&E) of a calcium plate (Ca) within the coronary artery wall. Scale bar, 200 μm. * Figure 2: μOCT of superficial arterial morphology. () Three-dimensional rendering of the swine coronary artery ex vivo, showing a pattern of raised cells that are consistent with endothelial "pavementing". (–) Human cadaver specimens. () μOCT image of a coronary plaque showing multiple cells that are likely to be leukocytes (arrows) adhering to the luminal surface. Two different cell morphologies can be observed: one smaller cell with scant cytoplasm, consistent with a lymphocyte (yellow arrow) and another, slightly larger cell with a highly scattering, abundant cytoplasm, suggestive of a monocyte (green arrow). () A cell with an indented, bean-shaped nucleus (green arrow) characteristic of a monocyte. () A cell, possibly a neutrophil (blue arrow), with a multilobed nucleus, is shown attached to the endothelial surface. () Multiple leukocytes tethered to the endothelial surface by linear structures suggestive of pseudopodia (white arrows). () Cells with the morphology of monocytes (red arrows) are shown in this cross-! section and inset to be transmigrating through the endothelium. () Structures consistent with fibrin (magenta arrow) are visible as linear strands bridging a gap in the coronary artery wall. () Thrombus (cyan arrow) that appears to contain fibrin, small (2–3 μm in diameter) highly scattering structures likely to be platelets, and multiple entrapped cells. Scale bars, 30 μm. * Figure 3: μOCT of plaque morphology in human cadaver specimens. () Necrotic core fibroatheroma with highly scattering lipid-laden macrophages or foam cells (white arrows) infiltrating the cap, also seen in the corresponding histology (top left inset). An intracellular region of low μOCT signal, which may represent the nucleus, is shown within the cytoplasm of some foam cells (for example, bottom left inset, blue arrow). () Another lesion, visualized by μOCT and histology, contains highly scattering foam cells that are ellipsoidal (right insets). () Smooth muscle cells imaged by μOCT appear as spindle-shaped cells (green arrow). Smooth muscle cells producing collagen have a high-backscattering interior (top right inset, yellow arrow) and a halo of low backscattering (top right inset, white arrow). Matching histological image (bottom right inset) shows that the high backscattering region represents the cell body, whereas the low-intensity halo corresponds to collagen matrix. () Large necrotic core fibroatheroma, showing cholesterol crys! tals, characterized by reflections from their top and bottom surfaces. () A thin crystal (red arrow) seems to pierce the cap of another necrotic core plaque. Scale bars for all primary images, 100 μm. Scale bars for all insets, 30 μm. CC, cholesterol crystal; NC, necrotic core. * Figure 4: μOCT of stent and neointimal morphology in human cadaver specimens. () μOCT image from a coronary segment with an implanted bare metal stent shows struts devoid of polymer and covered by neointima. () DES struts from another cadaver showing polymer (red dashed box and p, inset) overlying the strut reflections. () Tissue (yellow arrow) is interposed between the polymer and the stent strut and the polymer has fractured (white arrow). () Superficial leukocyte cluster (cyan arrow) and adjacent attached leukocytes overlying the site of the polymer fracture. () Apparent inflammation at the edge of a strut (green arrow). () Uncovered strut, completely devoid of overlying endothelium (red dashed box and inset). Scale bars for primary images, 100 μm. Scale bars for all insets, 30 μm. Author information * Abstract * Author information * Supplementary information Affiliations * Harvard Medical School, Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, Massachusetts, USA. * Linbo Liu, * Joseph A Gardecki, * Seemantini K Nadkarni, * Jimmy D Toussaint, * Yukako Yagi, * Brett E Bouma & * Guillermo J Tearney * Department of Dermatology, Massachusetts General Hospital, Boston, Massachusetts, USA. * Linbo Liu, * Joseph A Gardecki, * Seemantini K Nadkarni, * Jimmy D Toussaint & * Brett E Bouma * Harvard-MIT Health Sciences and Technology, Cambridge, Massachusetts,USA * Seemantini K Nadkarni, * Brett E Bouma & * Guillermo J Tearney * Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts, USA. * Yukako Yagi & * Guillermo J Tearney Contributions L.L. developed the μOCT system and participated in conducting the imaging studies and writing the manuscript. J.A.G. was responsible for procuring and preparing specimens, preparing the specimens for histopathology and organizing all digital histopathology data. S.K.N. and J.D.T. prepared the endothelial cell cultures. Y.Y. digitized the histopathology slides using her full-slide scanning systems. L.L. and G.J.T. analyzed and processed the data. B.E.B. contributed to the study design and participated in the analysis of the data. G.J.T. supervised the overall project and contributed to the design of experiments, interpretation of the μOCT image data and preparation of the manuscript. All authors read and edited the manuscript. Competing financial interests Massachusetts General Hospital has licensed OFDI technology to Terumo Corporation. B.E.B. and G.J.T. receive sponsored research relating to OFDI technology development from Terumo Corporation. B.E.B. and G.J.T. also have the right to receive royalty payments as part of this licensing arrangement. Corresponding author Correspondence to: * Guillermo J Tearney Author Details * Linbo Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Joseph A Gardecki Search for this author in: * NPG journals * PubMed * Google Scholar * Seemantini K Nadkarni Search for this author in: * NPG journals * PubMed * Google Scholar * Jimmy D Toussaint Search for this author in: * NPG journals * PubMed * Google Scholar * Yukako Yagi Search for this author in: * NPG journals * PubMed * Google Scholar * Brett E Bouma Search for this author in: * NPG journals * PubMed * Google Scholar * Guillermo J Tearney Contact Guillermo J Tearney Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–4 and Supplementary Methods Additional data
• Microfluidics-based diagnostics of infectious diseases in the developing world
  - Nat Med 17(8):1015-1019 (2011)
  Nature Medicine | Technical Report Microfluidics-based diagnostics of infectious diseases in the developing world * Curtis D Chin1 * Tassaneewan Laksanasopin1 * Yuk Kee Cheung1 * David Steinmiller2 * Vincent Linder2 * Hesam Parsa1 * Jennifer Wang1 * Hannah Moore1 * Robert Rouse1 * Gisele Umviligihozo3 * Etienne Karita3 * Lambert Mwambarangwe4 * Sarah L Braunstein5 * Janneke van de Wijgert4, 6 * Ruben Sahabo5 * Jessica E Justman5 * Wafaa El-Sadr5 * Samuel K Sia1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MedicineVolume: 17,Pages:1015–1019Year published:(2011)DOI:doi:10.1038/nm.2408Received28 May 2010Accepted03 February 2011Published online31 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg One of the great challenges in science and engineering today is to develop technologies to improve the health of people in the poorest regions of the world. Here we integrated new procedures for manufacturing, fluid handling and signal detection in microfluidics into a single, easy-to-use point-of-care (POC) assay that faithfully replicates all steps of ELISA, at a lower total material cost. We performed this 'mChip' assay in Rwanda on hundreds of locally collected human samples. The chip had excellent performance in the diagnosis of HIV using only 1 μl of unprocessed whole blood and an ability to simultaneously diagnose HIV and syphilis with sensitivities and specificities that rival those of reference benchtop assays. Unlike most current rapid tests, the mChip test does not require user interpretation of the signal. Overall, we demonstrate an integrated strategy for miniaturizing complex laboratory assays using microfluidics and nanoparticles to enable POC diagnostics and! early detection of infectious diseases in remote settings. View full text Figures at a glance * Figure 1: Schematic diagram and pictures of microfluidic device, and data on fluid handling of a POC ELISA-like assay. () Picture of microfluidic chip. Each chip can accommodate seven samples (one per channel), with molded holes for coupling of reagent-loaded tubes. () Scanning electron microscope image of a cross-section of microchannels, made of injection-molded plastic. Scale bar, 500 μm. () Transmitted light micrograph of channel meanders. Scale bar, 1 mm. () Schematic diagram of passive delivery of multiple reagents, which requires no moving parts on-chip. A preloaded sequence of reagents passes over a series of four detection zones, each characterized by dense meanders coated with capture proteins, before exiting the chip to a disposable syringe used to generate a vacuum for fluid actuation. () Illustration of biochemical reactions in detection zones at different immunoassay steps. The reduction of silver ions on gold nanoparticle–conjugated antibodies yields signals that can be read with low-cost optics (for quantification) or examined by eye. () Absorbance traces of a complete HIV! -syphilis duplex test as reagent plugs pass through detection zones. High optical density (OD) is observed when air spacers pass through the detection zones, owing to increased refraction of light compared to in the liquid-filled channels. The train of reagents mimics the pipetting of reagents in and out of multiwell plates. This sample was evaluated (correctly against a reference standard) as HIV negative and syphilis positive. Ag, antigen. * Figure 2: Results of immunoassays performed at Columbia University on commercial specimen panels. () Images of silver-enhanced signals on detection zones coated with HIV antigen (top group, left column), syphilis antigen (bottom group, left column), and antibodies to goat IgG (anti–goat IgG) (both groups, right columns) as a positive reference. Zones were exposed to positive and negative samples as judged by a reference standard (top and bottom rows, respectively). () Test results for HIV (left) and syphilis (right) antibodies. Vertical scatter plots of silver absorbance (normalized by cutoff values) for positive (Pos) and negative (Neg) serum or plasma specimens (each human sample is represented by one filled circle for HIV or cross for syphilis). Signal-to-cutoff values smaller than 0.1 are shown at 0.1 (with arrows). See Supplementary Tables 2–4 for raw data, cutoffs and specimen profiles. () Receiver-operating characteristic (ROC) curves for HIV (left) and syphilis (right), for illustrating changes in sensitivity and specificity depending on cutoff. * Figure 3: Field results of the HIV immunoassay collected in Muhima Hospital in Rwanda using <1 μl of unprocessed whole-blood sample. () Signal-to-cutoff ratios for positive (Pos) and negative (Neg) samples. () ROC curve. * Figure 4: Field results of a HIV and syphilis duplex immunoassay collected in Projet Ubuzima in Rwanda, using 7 μl of plasma or sera. () Signal-to-cutoff ratios of sera or plasma specimens that are positive (Pos) and negative (Neg) for HIV (circles) and syphilis (crosses). Signal-to-cutoff values >10 are shown at 10, and those <0.1 are shown at 0.1 (both with arrows). () ROC curves for HIV and syphilis. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Biomedical Engineering, Columbia University, New York, New York, USA. * Curtis D Chin, * Tassaneewan Laksanasopin, * Yuk Kee Cheung, * Hesam Parsa, * Jennifer Wang, * Hannah Moore, * Robert Rouse & * Samuel K Sia * Claros Diagnostics, Woburn, Massachusetts, USA. * David Steinmiller & * Vincent Linder * Rwanda Zambia HIV Research Group, Projet San Francisco, Kigali, Rwanda. * Gisele Umviligihozo & * Etienne Karita * Projet Ubuzima, Kigali, Rwanda. * Lambert Mwambarangwe & * Janneke van de Wijgert * Mailman School of Public Health, International Center for AIDS Care and Treatment Programs, Columbia University, New York, New York, USA. * Sarah L Braunstein, * Ruben Sahabo, * Jessica E Justman & * Wafaa El-Sadr * Academic Medical Center of the University of Amsterdam, Department of Internal Medicine, Center for Poverty-related Communicable Diseases and Center for Infection and Immunity, Amsterdam, The Netherlands. * Janneke van de Wijgert Contributions S.K.S. initiated the study; C.D.C. and S.K.S. designed and conducted the study; C.D.C., T.L., J.W., H.M. and R.R. performed microfluidic immunoassays at Columbia; Y.K.C. developed the compact reader; D.S. and V.L. advised on assay development and provided materials and reagents; H.P. performed computational analysis; L.M. performed reference testing of clinical samples; S.L.B., J.v.d.W., R.S., J.E.J. and W.E.-S. acquired clinical samples and assisted with field studies; C.D.C. and T.L. performed microfluidic immunoassays in Rwanda; C.D.C., T.L. and S.K.S. analyzed data; C.D.C. and S.K.S. wrote the paper; all co-authors edited the paper. Competing financial interests S.K.S. is a co-founder of Claros Diagnostics. Corresponding author Correspondence to: * Samuel K Sia Author Details * Curtis D Chin Search for this author in: * NPG journals * PubMed * Google Scholar * Tassaneewan Laksanasopin Search for this author in: * NPG journals * PubMed * Google Scholar * Yuk Kee Cheung Search for this author in: * NPG journals * PubMed * Google Scholar * David Steinmiller Search for this author in: * NPG journals * PubMed * Google Scholar * Vincent Linder Search for this author in: * NPG journals * PubMed * Google Scholar * Hesam Parsa Search for this author in: * NPG journals * PubMed * Google Scholar * Jennifer Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Hannah Moore Search for this author in: * NPG journals * PubMed * Google Scholar * Robert Rouse Search for this author in: * NPG journals * PubMed * Google Scholar * Gisele Umviligihozo Search for this author in: * NPG journals * PubMed * Google Scholar * Etienne Karita Search for this author in: * NPG journals * PubMed * Google Scholar * Lambert Mwambarangwe Search for this author in: * NPG journals * PubMed * Google Scholar * Sarah L Braunstein Search for this author in: * NPG journals * PubMed * Google Scholar * Janneke van de Wijgert Search for this author in: * NPG journals * PubMed * Google Scholar * Ruben Sahabo Search for this author in: * NPG journals * PubMed * Google Scholar * Jessica E Justman Search for this author in: * NPG journals * PubMed * Google Scholar * Wafaa El-Sadr Search for this author in: * NPG journals * PubMed * Google Scholar * Samuel K Sia Contact Samuel K Sia Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information Movies * Supplementary Movie 1 (10M) Movie of HIV-syphilis duplex test (complete assay). Time lapse over 20 minutes (1200 s) for two duplex immunoassays, one with a sample which is negative for HIV antibodies and positive for syphilis antibodies (top) and another with a sample which is positive for HIV antibodies and negative for syphilis antibodies (bottom). Meandering zones are functionalized with HIV antigen (left), syphilis antigen (middle), and anti-goat IgG antibody (right, positive control) as described in Supplementary Methods. * Supplementary Movie 2 (2M) Movie of whole blood passing through microchannel. The mChip can test whole blood samples without pre-processing or clogging of microchannels. PDF files * Supplementary Text and Figures (5M) Supplementary Figures 1–7, Supplementary Tables 1–9 and Supplementary Methods Additional data
• Epigenetic modulation of the renal β-adrenergic–WNK4 pathway in salt-sensitive hypertension
  - Nat Med 17(8):1020 (2011)
  Nature Medicine | Corrigendum Epigenetic modulation of the renal β-adrenergic–WNK4 pathway in salt-sensitive hypertension * ShengYu Mu * Tatsuo Shimosawa * Sayoko Ogura * Hong Wang * Yuzaburo Uetake * Fumiko Kawakami-Mori * Takeshi Marumo * Yutaka Yatomi * David S Geller * Hirotoshi Tanaka * Toshiro FujitaJournal name:Nature MedicineVolume: 17,Page:1020Year published:(2011)DOI:doi:10.1038/nm0811-1020Published online04 August 2011 Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Nat. Med.17, 573–580 (2011); published online 17 April 2011; corrected after print 4 August 2011 In the version of this article initially published, the authors made several inadvertent errors during manuscript preparation. In Figure 3f the trace for WT mice was incorrect, and in Figure 4a the bands shown for 'Total GR' were incorrect. These errors did not affect the quantification of band intensities shown in Figure 4a and did not affect any of the conclusions of the article. The errors have been corrected in the HTML and PDF versions of the article. Additional data Author Details * ShengYu Mu Search for this author in: * NPG journals * PubMed * Google Scholar * Tatsuo Shimosawa Search for this author in: * NPG journals * PubMed * Google Scholar * Sayoko Ogura Search for this author in: * NPG journals * PubMed * Google Scholar * Hong Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Yuzaburo Uetake Search for this author in: * NPG journals * PubMed * Google Scholar * Fumiko Kawakami-Mori Search for this author in: * NPG journals * PubMed * Google Scholar * Takeshi Marumo Search for this author in: * NPG journals * PubMed * Google Scholar * Yutaka Yatomi Search for this author in: * NPG journals * PubMed * Google Scholar * David S Geller Search for this author in: * NPG journals * PubMed * Google Scholar * Hirotoshi Tanaka Search for this author in: * NPG journals * PubMed * Google Scholar * Toshiro Fujita Search for this author in: * NPG journals * PubMed * Google Scholar