SALINAS, Calif., Dec. 03, 2020 (GLOBE NEWSWIRE) -- Indus Holdings, Inc. ("Indus” or the “Company”) (CSE:INDS; OTCQX: INDXF), a leading, vertically-integrated, California-focused cannabis company, announces updated guidance for the fourth quarter ending December 31, 2020. All figures stated are in US Dollars.
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BioCryst Announces FDA Approval of ORLADEYO™ (berotralstat), First Oral, Once-daily Therapy to Prevent Attacks in Hereditary Angioedema Patients
CHICO, Calif. -- It's the holiday season, and this Thanksgiving, most people engaged in activities that can lower immunity, like eating a lot of sugar, drinking alcohol in excess, in addition to experiencing increased stress due to the holidays.
Dr. Rand McClain, an expert in restorative and regenerative health and the Chief Medical Officer of LCR Health, shows us how Thanksgiving traditions and habits could be harmful to our immune systems and what we can do to get our immune systems back on track and stay healthy.
Here are a few of his suggestions:
1) Adequate sleep Aim for regular sleep 7 9 hours nightly and during roughly the sameperiod (ex. 11p 7a each night rather than at varying times, especially as occurs with"shift work").
2) Daily exercise Anything is better than nothing but ideally a minimum of 30 minutes, 3times per week of effort that amounts to brisk walking. 5 6 times per week would beeven better, and efforts of an hour each time would be even better. However, morethan that is not necessarily better.
3) Proper nutrition This includes staying hydrated, eating a balanced array of whole, non-processed foods, and spending the time to find what diet works best for you (one dietdoes not fit all). In addition, avoid overeating. Most people eat more than is necessaryfor good immune health. Keep sufficient fiber in the diet to maintain regular bowelmovements and a healthy gut microbiome now considered a major factor inmaintaining healthy immune function.
4) Modulate and avoid excess stress Breathing exercises and other methods (eg,meditation and yoga) of reducing stress (and excess cortisol levels) can help keep theimmune system functioning at its best.
5) Avoid excess alcohol consumption and smoking both known to have negative effectson immune function.
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Recover your immune system through the holidays - Action News Now
In 2021 hundreds of millions of people will be vaccinated against SARS-CoV-2. The success of that COVID-19 vaccination campaign will heavily depend on public trust that the vaccines are not only effective, but also safe. To build that trust, the medical and scientific communities have a responsibility to engage in difficult discussions with the public about the significant fraction of people who will experience temporary side effects from these vaccines.
I am an immunologist who studies the fundamentals of immune responses to vaccination, so part of that responsibility falls on me.
Simply put, receiving these vaccines will likely make a whole lot of people feel crappy for a few days. Thats probably a good thing, and its a far better prospect than long-term illness or death.
In 1989, immunologist Charles Janeway published an article summarizing the state of the field of immunology. Until that point, immunologists had accepted that immune responses were initiated when encountering something foreign bacteria, viruses, and parasites that was non-self.
Janeway suspected that there was more to the story, and famously laid out what he referred to as the immunologists dirty little secret: Your immune system doesnt just respond just to foreign things. It responds to foreign things that it perceives to be dangerous.
Now, 30 years later, immunologists know that your immune system uses a complex set of sensors to understand not only whether or not something is foreign, but also what kind of threat, if any, a microbe might pose. It can tell the difference between viruses like SARS-CoV-2 and parasites, like tapeworms, and activate specialized arms of your immune system to deal with those specific threats accordingly. It can even monitor the level of tissue damage caused by an invader, and ramp up your immune response to match.
Sensing the type of threat posed by a microbe, and the level of intensity of that threat, allows your immune system to select the right set of responses, wield them precisely, and avoid the very real danger of immune overreaction.
Vaccines work by introducing a safe version of a pathogen to a patients immune system. Your immune system remembers its past encounters and responds more efficiently if it sees the same pathogen again. However, it generates memory only if the vaccine packs enough danger signals to kick off a solid immune response.
As a result, your immune systems need to sense danger before responding is at once extremely important (imagine if it started attacking the thousands of species of friendly bacteria in your gut!) and highly problematic. The requirement for danger means that your immune system is programmed not to respond unless a clear threat is identified. It also means that if Im developing a vaccine, I have to convince your immune system that the vaccine itself is a threat worth taking seriously.
This can be accomplished in a number of ways. One is to inject a weakened what immunologists call attenuated or even killed version of a pathogen. This approach has the benefit of looking almost identical to the real pathogen, triggering many of the same danger signals and often resulting in strong, long-term immunity, as is seen in polio vaccination. It can also be risky if you havent weakened the pathogen enough and roll out the vaccine too fast, there is a possibility of unintentionally infecting a large number of vaccine recipients. In addition to this unacceptable human cost, the resulting loss of trust in vaccines could lead to additional suffering as fewer people take other, safer vaccines.
A safer approach is to use individual components of the pathogen, harmless by themselves but capable of training your immune system to recognize the real thing. However, these pieces of the pathogen dont often contain the danger signals necessary to stimulate a strong memory response. As a result, they need to be supplemented with synthetic danger signals, which immunologists refer to as adjuvants.
To make vaccines more effective, whole labs have been dedicated to the testing and development of new adjuvants. All are designed with the same basic purpose to kick the immune system into action in a way that maximizes the effectiveness and longevity of the response. In doing so, we maximize the number of people that will benefit from the vaccine and the length of time those people are protected.
To do this, we take advantage of the same sensors that your immune system uses to sense damage in an active infection. That means that while they will stimulate an effective immune response, they will do so by producing temporary inflammatory effects. At a cellular level, the vaccine triggers inflammation at the injection site. Blood vessels in the area become a little more leaky to help recruit immune cells into the muscle tissue, causing the area to become red and swell. All of this kicks off a full-blown immune response in a lymph node somewhere nearby that will play out over the course of weeks.
In terms of symptoms, this can result in redness and swelling at the injection site, stiffness and soreness in the muscle, tenderness and swelling of the local lymph nodes and, if the vaccine is potent enough, even fever (and that associated generally crappy feeling).
This is the balance of vaccine design maximizing protection and benefits while minimizing their uncomfortable, but necessary, side effects. Thats not to say that serious side effects dont occur they do but they are exceedingly rare. Two of the most discussed serious side effects, anaphalaxis (a severe allergic reaction) and Guillain-Barr Syndrome (nerve damage due to inflammation), occur at a frequency of less than 1 in 500,000 doses.
Early data suggest that the mRNA vaccines in development against SARS-CoV-2 are highly effective upwards of 90%. That means they are capable of stimulating robust immune responses, complete with sufficient danger signaling, in greater than nine out of 10 patients. Thats a high number under any circumstances, and suggests that these vaccines are potent.
So lets be clear here. You should expect to feel sore at the injection site the day after you get vaccinated. You should expect some redness and swelling, and you might even expect to feel generally run down for a day or two post-vaccination. All of these things are normal, anticipated and even intended.
While the data arent finalized, more than 2% of the Moderna vaccine recipients experienced what they categorized as severe temporary side effects such as fatigue and headache. The percentage of people who experience any side effects will be higher. These are signs that the vaccine is doing what it was designed to do train your immune system to respond against something it might otherwise ignore so that youll be protected later. It does not mean that the vaccine gave you COVID-19.
It all comes down to this: Some time in the coming months, you will be given a simple choice to protect yourself, your loved ones and your community from a highly transmissible and deadly disease that results in long-term health consequences for a significant number of otherwise healthy people. It may cost you a few days of feeling sick. Please choose wisely.
This article is republished from The Conversation under a Creative Commons license. Read the original article.
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Vaccines against the coronavirus will have side effects and thats a good thing - PBS NewsHour
Shawn stepped into the UCLA Vine Street Clinic in Hollywood with confidence. He offered up his arm. The UCLA doctor injected him. It took seconds; there was barely a sting.
Twenty-four hours after the first of two shots, given 28 days apart, he suffered the headaches and fatigue associated with a milder case of COVID-19. But Shawn remained calm, resolved to honor the memory of his mother, a nurse who had died in May 2020 from an unrelated cause.
The 57-year-old nonprofit worker had been thinking about the challenges of COVID-19 for a long time, and he decided to go through the lengthy consent process for the medical trial. It gave me something to do with my anger that was so much better than yelling at someone for not wearing a mask, he says. And [at UCLA] I felt I was in good hands.
Shawn is one of many volunteers who have stepped up to participate in medical trials at UCLA, which is part of a global network thats determined to help find a vaccine against the novel coronavirus.
The stakes are huge. More than 250,000 Americans have already died, and there have been more than 1 million deaths around the world. Economies have been brought to their knees, social tensions have disrupted communities and emotional maladies are on the rise.
In response, doctors and scientists have been challenged to be resilient and ingenious. Theyre taking an array of different approaches, knowing that public confidence in vaccines hangs in the balance.
In addition, it has been a challenge to create a vaccine in such a short amount of time similar efforts have taken five to 10 years. Pharmaceutical giant Pfizer and biotech firm Moderna have both reported remarkable progress, announcing in November that their vaccine candidates were more than 90% effective. All of which has raised questions about the next steps, such as how the vaccines will be distributed.
I dont want to make a vaccine to protect against mild disease, says Dr. Marcus Horwitz, distinguished professor of medicine and microbiology, immunology and molecular genetics at the David Geffen School of Medicine at UCLA. I want to protect people who are going to get severe disease.
Horwitz has already developed vaccines against the bacteria behind tuberculosis, anthrax and the tick-borne disease tularemia, but he has never tried to create a vaccine against a virus. When faced with a worldwide pandemic, we thought we might be able to make a contribution, he says.
Vaccines work by training the immune system to recognize and fight disease-causing pathogens, such as viruses or bacteria. Doctors introduce the bodys immune system to antigens, which are molecules from the virus or bacteria, and the immune system responds by making proteins called antibodies and immunity-building T cells, which both neutralize the pathogen.
The delivery of these antigens requires a delicate calculus: It must provoke the immune system, but not go so far as to make the patient ill. You need a vector that will wake up the immune system of the host, but not cause any further harm, Horwitz says.
The vaccine approach by Horwitz and his team, including lead investigator Qingmei Jia, is a medical outlier: They adapted an existing antibacterial platform to build protection against SARS-CoV-2, the virus that causes COVID-19. The team has shown that their vaccine candidate protects hamsters, which develop severe disease in a way similar to humans.
Some of the potential vaccines for SARS-CoV-2 use a weakened form of an adenovirus, which causes the common cold, to deliver the S protein that is found on the surface of the SARS-CoV-2 virus. Horwitzs vaccine stands out from the pack because it uses a weakened bacterium to deliver two SARS-CoV-2 proteins, the M and N proteins.
That difference could have a tremendous impact. Billions of COVID-19 vaccine doses are needed, and bacteria, unlike viruses, are easy and cheap to produce and transportable.
The success of a COVID-19 vaccine also depends on the immune system, which can be less robust in older people.
This is a problem that has driven Song Li, chair of the bioengineering department at the UCLA Samueli School of Engineering, who has focused his career on cell and tissue engineering. Adapting a concept from cancer immunotherapy, Li is developing a biomaterial vaccine booster using artificial cells that could improve the immune systems ability to generate long-term protection.
When the immune system encounters a destructive pathogen, it produces cells that are designed to attack the invader. A small number of those cells, called T memory stem cells, can stay in the system for years ready for a future invasion. Unfortunately, our ability to produce T memory stem cells declines as we get older. Li hopes his booster, in combination with a vaccine, can help fragile immune systems effectively fight against the SARS-CoV-2 virus.
My goal at the outset was to help the elderly population, Li says. But it could be useful for any person whose immune system needs help generating protection from the virus.
Another UCLA team led by Bogdan Pasaniuc, Dr. Manish Butte and Dr. Daniel Geschwind, the Gordon and Virginia MacDonald Distinguished Professor of Human Genetics at the Geffen School of Medicine is trying to find out why the virus significantly impacts some, but leaves others relatively unscathed.
We know age is a major factor, but we see older people who get infected and do quite well, Geschwind says. We have a limited ability to predict how sick someone will get. His team hopes that studying whole-genome sequences from thousands of COVID-19 patients will reveal hidden factors that make some more vulnerable than others. The research could help identify people who are at higher risk for infection as well as develop new treatment and prevention strategies.
Dr. Brigitte Gomperts, professor of pediatrics and pulmonary medicine and a member of the UCLA Broad Stem Cell Research Center, is studying how COVID-19 affects lung tissue. By using stem cellderived clusters of lung cells, known as organoids, she can rapidly screen thousands of prospective treatments. Because the organoids are grown from human cells and reflect the cell types and architecture of the lungs, they can offer insights into how the virus infects and damages the organ.
At UCLA medical centers around Los Angeles County, physicians are ensuring that their medical trials include diverse groups of people and women of all ages.
COVID-19 has hit the African American and Latino communities particularly hard, says Dr. Jesse Clark, associate professor-in-residence in the department of medicine at the Geffen School of Medicine. We have to make sure that any vaccine has been determined to be safe and effective in all populations that will receive it.
COVID-19 has hit the African American and Latino communities particularly hard. We have to make sure that any vaccine has been determined to be safe and effective in all populations that will receive it.
Dr. Jesse Clark, associate professor-in-residence in the department of medicine at the David Geffen School of Medicine at UCLA
Clark is medical director of the UCLA Vine Street Clinic, which is involved in the Moderna clinical trial. Notably, Modernas vaccine works differently from a typical vaccine, because it doesnt contain the virus at all. Instead, it uses messenger RNA, or mRNA, which uses the bodys genetic code to produce antibodies against the virus.
CNN mentioned that the vaccine trials were having trouble finding minorities to participate, says Roderick, a 37-year-old IT manager and father of two, who is participating in the Moderna trial. Being Black and Mexican, and knowing how hard my demographic has been hit, I just went ahead and signed up online. Its worth doing to help out.
Meanwhile, Dr. Katya Corado, an infectious disease specialist at Harbor-UCLA Medical Center in Torrance, has been enrolling patients in a phase 3 clinical trial of an adenovirus vector vaccine thats under development by the University of Oxford and the biopharmaceutical company AstraZeneca.
All vaccines undergo three phases of clinical trials, according to rules set by the Food and Drug Administration. Phase 1, which involves 20 to 100 volunteers, tests the safety and dosage of the vaccine. Phase 2 tests the drugs efficacy and side effects among several hundred participants, and phase 3 gathers more information about a vaccines safety and effectiveness by studying thousands of volunteers.
In the phase 3 trial, we focus on studying how effective the vaccine is in populations that need it most, Corado says.
Clark and Corado are both hopeful that their work can protect the most vulnerable, which includes people over 65, patients with chronic conditions, those facing economic disadvantages and essential workers.
Inoculations have eradicated past epidemics, such as smallpox. But public faith in vaccines has wavered, especially when a now-disproven report in 1998 suggested that the measles, mumps and rubella vaccine was linked to autism spectrum disorder. That has led to U.S. outbreaks of measles, which had been previously eliminated. So scientists recognize the importance of getting the COVID-19 vaccine right.
There are other factors to consider as well. Vaccine distribution will be high on the agenda of the incoming White House administration, but if supply is limited, the Centers for Disease Control and Prevention recommends prioritizing certain groups, such as medical workers.
Also, some vaccines currently in development need to be stored in ultra-cold conditions. For example, Pfizers vaccine must be stored at minus 70 degrees Celsius, while Modernas vaccine must be kept at minus 20 degrees Celsius the temperature of a regular freezer. These factors will affect how the vaccines are distributed.
Some lawmakers have advocated letting the virus run its course in the hopes of achieving herd immunity, which is when enough people have become immune to an infectious disease, either through being infected or vaccination. Since the COVID-19 vaccine is still pending, a majority of people will need to be infected in order to achieve herd immunity and that comes at a terrible cost.
According to Dr. Robert Kim-Farley, professor-in-residence of epidemiology at the UCLA Fielding School of Public Health, up to 2 million Americans would have to die before the country reached herd immunity.
He argues that vaccines work, even if they are not perfectly safe or perfectly effective, as proven by the near-eradication of polio. But approving vaccines prematurely to buckle under the pressure of politics or profit could cause a terrible backlash against being vaccinated, which could lead to future outbreaks.
We want to make sure we are not cutting corners, Kim-Farley says, that we are getting the best vaccine that has the highest efficacy, the longest duration, the fewest number of side effects [with] the fewest number of doses.
This is a very high-stakes game, and its important to get it right, without recalls or playing into the [anti-vaccination] narrative. What still concerns me is the equitable distribution of vaccines to make sure that countries that are not as wealthy as us have access to these life-saving vaccines. We are all members of one global community.
The new collection includes Immune Therapy, Stress Therapy, and Gut Therapy that synergistically nourish the gut microbiome, nervous system, gut-lung axis, and gut-brain axis.
The formulations are the culmination of immune research and over four decades of experience from Co-Founder Paul Schulick. As the companys formulator, Schulick launched For The Biome after parting ways with New Chapter, a company he founded in 1982 which was later acquired by Procter & Gamble in 2012.
We identify For The Biome as a wellness company and although we launched with skincare, my intention has always been to expand into ingestibles. We like to say that you have to treat as a whole to heal as a whole so its only natural that we offer products designed for internal and topical use. The choice to move into immunity was simply nature calling. It was an opportunity to make a contribution, which is what I am here to do, said Schulick.
The master herbalist explained that the products target specific biomarkers to bring an exhausted or overactive immune system back to balance.
We looked at a panel of cytokines, both pro and anti-inflammatory, and a window of immediate effects and response to the exposure of the products. We wanted to see the acute effects and what was moving the needle, said Schulick.Examples of the biomarkers include IL-1B, IL-Ra., IL-2, CD69, CD25, and G-CSF, which help modulate inflammation, signal an immune response, and support renewal. We also looked at the CAP-e antioxidative capacity for the product, or its ability to get into the cells and protect them from the inside out.
Schulick said the Immune Therapy and Stress Therapy are both backed by clinical studies and the probiotic strains in Gut Therapy are backed by several clinical studies as well, adding, We invest heavily to conduct ongoing research and will share this with our customers as it breaks.
In-vitro testing suggests that Immune Therapy balances immunomodulating markers within 2 hours as it coats the mouth and gut microbiome with a protective liquid infusion.
Stress Therapy is a restorative infusion that delivers stress relief by soothing the immune system, nervous system, and supporting the gut microbiome.
The company said Gut Therapy is a first-to-the-world fermentate featuring clinically studied prebiotics, postbiotics, para-probiotics, and live probiotics that support a resilient gut microbiome and its connection to immune, respiratory, and emotional health.
We select the most healing and restorative prebiotic, whole-food, and certified organic botanicals for the digestive system (eg., flax, chaga, aloe, and moringa) and then utilize the power of fermentation to further amplify their benefits. This is no ordinary fermentation process. It is a dual-stage process using the yeast Saccharomyces cerevisiae and two of the most researched probiotic strains from Lactobacillus and Bifidobacteria genera, GG and BR03. These strains produce many important immunologically active peptides also known as postbiotics.
Schulick added that Gut Therapy then completes the formulation with a therapeutically validated, live dose of Lactobacillus plantarum DR7, a probiotic with multiple positive effects on immunity (NK cell upregulation, respiratory protection), stress response (cortisol, serotonin) and cognition (enhanced learning and social emotional reasoning).
When formulating these products, I referenced groundbreaking research that focused on advancements in immune support around the world. This research, coupled with my passion for herbalism, guided me as I chose plants, mushrooms, and probiotics renowned for their ability to support a wiser immune response.
Schulick told NutraIngredients-USA that his goal was to source the best possible forms of these components and introduce some of them for the first time to North America. One of the most remarkable is the herb Cistus incanus, popular in the Mediterranean, and known for its remarkable restorative and protective abilities. Its featured in Immune Therapy because of its notable ability to signal immune response and recovery. Whats more is that, while this ingredient is phenomenal on its own, its even more effective when paired with symbiotic nutrients. We saw increased activity of Cistus incanus when we paired it with vitamin C-rich black currant leaves and rose hips, and birch-grown chaga with betulinic acid. All three of our formulas deliver these kinds of extraordinary synergies.
Schulick said identifying the ingredients is the easier part. Getting the level of efficacy and quality that meets our standards is another story.
For the most part, this has always been the case, COVID or not. Certainly, this period of time during COVID has made that more difficult and weve had to search around the world two or three times, sometimes, to find what we needed. We then independently test and confirm for levels of active compounds to deliver what we are seeking.
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For the Biome makes leap from skin to immune health - NutraIngredients-usa.com
December 2, 2020
Arizona State University has been awarded a $12.5 million multiyear subcontract from the Frederick National Laboratory for Cancer Research (FNL), operated by Leidos Biomedical Research on behalf of the National Cancer Institute, to join the NCIs Serological Sciences Network (SeroNet), the nations largest coordinated effort to study peoples immune response to COVID-19.
SeroNet was enacted as a result of $306 million in emergency supplemental funding from the U.S. Congress for the NCI to study serological sciences related to COVID-19.
ASU is one of just four Capacity Building Centers (CBCs) selected nationally for SeroNet. The goal is to develop high performance serological tests to determine a persons previous exposure to SARS-CoV-2. The network aims to combat the ongoing COVID-19 pandemic by improving the ability to test for an antibody response to infection, especially among diverse and underserved populations, and to accelerate the development of treatments and vaccines aimed at preventing COVID-19 and improving patient outcomes.
This award will now establish Arizona State University as the most comprehensive COVID testing research center in the Southwest, and is a testament to our commitment and scientific capabilities to be offered the opportunity to join SeroNet and to provide a critical service to our community and nation, said ASU Biodesign Institute Executive Director Dr. Joshua LaBaer. It builds upon the great successes of our innovative antibody testing platform, robust biomarker discovery and diagnostic assay development capabilities; our extensive experience at successfully completing large federal contracts, grants and FDA emergency use authorizations; and our response to this pandemic through large-scale PCR-based SARS-CoV-2 testing of saliva samples.
According to ASU Biodesign Institute Executive Director Dr. Joshua LaBaer, ASU hopes to develop a simple, FDA-approved COVID-19 antibody test to detect for previous SARS-CoV-2 exposure and to better understand a persons immune response to COVID-19.
The NCI, FNL and ASU were able to pivot to support COVID-19 research because of their deep experience in virology and immunology research, including research on viruses that cause cancer, such as HPV, and experience in immunotherapy.
In March, LaBaer, a medical oncologist by training who co-discovered breast cancer biomarkers included in a CLIA-approved breast cancer test with colleague Dr. Karen Anderson, shifted his laboratory to become a CLIA-certified clinical laboratory to fully support COVID-19 testing.
In May 2020, LaBaer and Vel Murugan, an ASU associate research professor and co-principal investigator on the SeroNet CBC subcontract, created the first saliva-based COVID-19 test in the Western United States.
To date, ASU has provided more than 300,000 free saliva tests to the general public, first responders, doctors, nurses and medical personnel, and the entire ASU community to help Arizona in the response to keep individuals safe and healthy during the pandemic.
As part of the national SeroNet, ASUs interdisciplinary team of expert scientists and researchers at the Biodesign Institute, led by LaBaer, will establish the ASU Biodesign Capacity Building Center (ABCBC). Other key individuals involved in this project are Ji Qiu, Jin Park, Femina Rauf, Lusheng Song, Mitch Magee and Michael Fiacco.
Through this latest project, we hope to develop a simple, FDA-approved COVID-19 antibody test to detect for previous SARS-CoV-2 exposure and to better understand a persons immune response to COVID-19, said LaBaer. We ultimately want to develop a test for any exposures people may have had to all known human coronaviruses and other respiratory pathogens in order to improve patient outcomes.
The core of the technology builds upon a novel ASU platform (called MISPA) that uses rapid DNA sequencing to monitor many patients immune responses to multiple viral proteins simultaneously, via a molecular barcoding. ASU has tested the platform on cancer subtypes caused by HPV. Now, they want to adapt the same technology for understanding COVID-19.
This system exploits the power of DNA next-generation sequencing (NGS) technology to quantify COVID virus antigens and their interactions with antibodies produced in the body to fight the infection, said Murugan. With this assay, we 'barcode' individual proteins called antigens within the virus with unique DNA sequences that interact in solution with patient serum, followed by quantification of the antibody-bound barcodes by NGS.
Unlike current commercially available serological tests, the MISPA-based test is designed to be quantitative about the strength of the immune response while providing information about responses to multiple proteins and eventually, multiple viruses simultaneously. In addition, because individual reactions can also be indexed (or barcoded) in parallel, thousands of patient samples can be combined, and all the results determined in a single NGS run (many barcoded patients versus many barcoded proteins).
MISPA will also be deployed through a similar high-throughput, fully automated test that can process thousands of samples per day as we have successfully demonstrated from our COVID-19 saliva test, said Murugan.
Initial tests will rely on a testing pool of individuals who have recovered from the infection. Potential sites for serological tests include: ValleyWise, Midwestern/Abrazo hospital networks, Dignity Health hospital network, Columbia University, Colorado River Indian Tribal community through their tribal government, ASU students and population, other universities in Arizona and essential infrastructure partners.
Should the test validation and FDA EUA become approved, testing will expand to essential infrastructure employees, health care professionals and residents in long-term care facilities or other congregate living settings, including prisons and shelters. Community surveillance for asymptomatic population will be conducted at a lower priority when needed.
The lessons learned from ASUs role in SeroNet research could be applied immediately to the COVID-19 pandemic crisis and may prove valuable to public health beyond the pandemic.
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While having a robust immune response to coronavirus infection may sound helpful, a new study shows the opposite may be true.
To better understand how variations in early host immune responses affect disease outcomes, researchers at the Tulane National Primate Research Center followed the course of disease in the four weeks following COVID-19 infection in non-human primates.
They discovered robust early immune responses to the virus and a recruitment of immune cells from the blood to the lungs. They also found that certain cytokinei.e., cell-signaling proteins that help to regulate pro- and anti-inflammatory responsesmay prove helpful in predicting disease outcomes.
These results suggest that in these early weeks post-infection, the stronger the initial host immune response, the worse the disease outcome, says Monica Vaccari, associate professor of microbiology and immunology at the Center and lead author of the study in Nature Communications.
Vaccari explains that while the body mounts a pro-inflammatory innate immune response as a first line of defense to protect against the spread of infection and heal damaged tissue, it is a dysregulated or over-reactive immune response that can cause severe damage. Too much inflammation in the lungs, for example, can result in decreased oxygen.
A pro-inflammatory response is usually our bodys first line of defense, and it can be a very helpful mechanism. But what were seeing with coronavirus infection is that somewhere down the line, there is uncontrolled inflammation. We want to know when and why this happens, Vaccari says.
Understanding what happens in the immune system during this short period following infection will be essential in developing effective therapeutics against COVID-19. While immune functions can be modulated, scientists want to avoid turning off immune responses that may be critical to fighting infection.
One of the most vexing aspects of the novel coronavirus is the broad spectrum of disease outcomes associated with it. A disease that causes few or mild symptoms for most also has the capacity to cause severe and lasting damage or death for others.
While scientists and clinicians have long suspected that it is the hostor person that acquires the diseasethat dictates disease severity, they have not known which specific individual immune markers are harmful and which are protective, particularly in the earliest stages of disease.
This new study identified variations in early host immune responses that may be predictive of COVID-19 disease severity.
Source: Tulane University
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Stronger early immune reaction might make COVID worse - Futurity: Research News
By Graham Lawton
Ted Shaffrey/AP/Shutterstock
UK regulators have authorised a covid-19 vaccine created by Pfizer and its partner BioNTech for emergency use, meaning that vaccine rollout is planned to begin soon. Here, we answer questions about the science of the vaccine, who will get it first, how confident we can be in the authorisation process and the logistics of vaccinating everyone in the UK.
How effective is the vaccine?About 95 per cent. The phase 3 trials of the Pfizer/BioNTech vaccine involved 42,000 people, about half of whom got the experimental vaccine and the rest a placebo. In total, 170 people fell ill with covid-19. Only eight of them were in the vaccine group; 162 had received the placebo. So around 5 per cent of cases were in the vaccine group, which is where the 95 per cent figure comes from. That is a very healthy number: the World Health Organization (WHO) has said it would be happy with 50 per cent.
What is in the vaccine?The active ingredient is messenger RNA that carries instructions for making the viruss spike protein, which it uses to gain entry to cells. The mRNA is synthetic, not extracted from actual viruses. It is delivered in a tiny sphere of inert fatty material called a lipid nanoparticle.
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The RNA-bearing nanoparticles are suspended in saline solution and injected into muscle tissue in the upper arm. The mRNA is then taken up by specialist immune cells, which follow its instructions to make the spike protein, just as they would do if they had become infected with the actual virus.
The spike protein is recognised as foreign by the immune system, which mounts an attack against it. Antibodies, B cells and T cells are activated, according to Uur ahin, the chief executive of the small German company BioNTech that co-developed the vaccine with US drug giant Pfizer. An immune memory is also laid down, he says, which means the immune system has learned how to defeat the pathogen and is primed to mount a swift response if it encounters the coronavirus again.
How long does the immune memory last?Its hard to say at this point, because the clinical trials werent set up to answer that question, and in any case, they only began dispensing second doses of the vaccine four months ago. The WHO says that a minimum of six months would be acceptable. It will become clearer as time marches on and the volunteers continue to be monitored. Sahin says he expects protection to last months or even years. Given what we know about natural immunity that looks about right, says Eleanor Riley at the University of Edinburgh in the UK. She envisages people needing annual boosters, at worst.
How long does it take for immunity to develop fully after vaccination?The trial began assessing immunity seven days after the second shot. We know that protective immunity builds up within four weeks of the first dose, but Sahin says that it appears to develop earlier than that. Further details will be published in a matter of days, he says.
What happens to the mRNA in the body?It is active for a few days then decays rapidly.
Its a two-shot vaccine, so what happens if people miss their second shot? Is a single shot still protective?Two shots are needed, and the second shot is required to attain immunity. The gap between doses in the trial ranged between 19 and 42 days. Only 2 per cent of people in the trial missed their second dose so it isnt entirely clear what happens under those circumstances.
Are there any side effects?Sometimes, but they are mild. In the trial, the vaccine was generally well-tolerated, and an independent data monitoring committee reported no serious safety concerns. The worst side effects were fatigue and headaches after the second dose. About 4 per cent of people reported fatigue and 2 per cent a headache. Other side effects were pain at the injection site and muscle pain. These are common reactions you would have with vaccination, says zlem Treci, chief medical officer at BioNTech. Older adults reported fewer and milder side effects.
Does it work in older people?Yes. Trial participants were aged up to 85, and the efficacy in people over 65 was 94 per cent a tiny bit lower than the overall number but still very protective, and much higher than some vaccine experts feared. The vaccine hasnt been tested in people aged over 85.
What about other vulnerable groups?The vaccine appears to be equally effective regardless of recipients age, sex and ethnicity, according to BioNTech. It has been tested extensively in people who have already had the virus and doesnt cause any ill effects. It has also been tested in people with stable pre-existing conditions also known as comorbidities including diabetes, cancer, hepatitis B, hepatitis C and well-managed HIV. Their response was as good as anyone elses.
People with serious or worsening comorbidities will also be eligible for the vaccine. BioNTech says it has data on this group and will release it in a matter of days.
Does it protect everyone?No. In the trials, out of about 20,000 people who were given the vaccine, eight caught covid-19 and one became seriously ill. In contrast, 164 people who received the placebo fell ill, nine severely. It isnt known why some people didnt respond to the vaccine. But a success rate of 95 per cent is about as good as it gets with any vaccine.
Does it stop people from catching and transmitting the virus?We still dont know. The trial was designed to test for symptomatic covid-19 and confirmed infection with the virus. Assessing whether the vaccine prevents transmission which is probably a prerequisite for attaining vaccine-induced herd immunity is much harder. But Pfizer says it is carrying out more studies on this important question and will release information soon.
Some vaccines can paradoxically make a disease worse through a process called antibody-enhanced disease. Is that a risk?Yes, theoretically. But it hasnt been seen with this vaccine or any other against covid-19, and hasnt occurred naturally, as sometimes happens with other viruses.
Has the the full data from the trial been published yet?No, it hasnt, but there is nothing sinister about that. Companies can release news to the market as soon as they have it, which is a much speedier process than preparing a scientific manuscript. According to Pfizer, every last detail of the science will be submitted to a top-ranking peer-reviewed journal as soon as it is ready. It will then be up to the journal how long it takes to publish.
Who is first in the queue in the UK?When a vaccine is approved it is customary to first offer it to people who took part in the clinical trial but received the placebo. However, as the trial wasnt done in the UK, there is nobody in this category.
Care home residents and their carers have the highest priority, according to a priority system devised by the UKs Joint Committee on Vaccination and Immunisation. But there are problems with delivering this particular vaccine to care home residents because it needs to be transported at very cold temperatures in special cases that carry around 1000 doses. These cases cannot be broken up for distribution, which makes it very hard to get the required doses into individual care homes.
Next in line are people aged over 80 and frontline healthcare workers, followed by people aged over 75, then people in increasingly younger age groups and/or with underlying health conditions.
Will anyone be excluded from the vaccine programme?Yes. Pregnant women and children under 16 wont be eligible, at least at first. The vaccine hasnt been tested on pregnant women or children under 12, and there isnt enough data on children age 12 to 15. But trials in those groups are ongoing or planned.
Everyone else can get it?Yes, but most will have to wait their turn. According to Sean Marett at BioNTech, the exact delivery schedule depends on how fast the factories can churn it out and where else the vaccine is approved, as the company is committed to equitable access. We will deliver as many doses as we can as quickly as we can, he says.
What does temporary authorisation for emergency use mean?Exactly what it says on the tin. The UKs Medicines and Healthcare products Regulatory Agency (MHRA) has expedited the approval process in recognition of a public health emergency, and could rescind the approval just as quickly. But that is highly unlikely as it says it has done a thorough assessment of the safety and efficacy data and has seen nothing to give it reason not to approve.
Will the vaccine inevitably progress from temporary to full authorisation?Probably, but it isnt a given. Pfizer says it expects so, but that is in the hands of the regulators.
It all happened very quickly, can we be confident corners werent cut?Yes. The MHRA is an independent body and so is the Commission on Human Medicines, which also had a say in the decision to approve the vaccine in the UK. Even though the MHRA only received the full clinical trial data just over a week ago, the vaccine developers have been submitting information since October, which has been subject to ongoing review.
The European Medicines Agency, the drug regulator that approves covid-19 vaccines for the European Union, said in a statement that its process for assuring the safety and efficacy of the vaccine is based on more evidence and more checks than the emergency authorisation used in the UK.
According to the vaccine developers, the MHRA asked for exactly the same amount of information as any other regulatory agency. It has been working 24/7 to assess it, says Treci.
Are other countries likely to approve the vaccine soon as well?Yes. Pfizer/BioNTech have also applied for approval in the US, EU, Australia, Canada, Japan and New Zealand, and say they are preparing to submit applications to other regulatory agencies around the world. Decisions are expected from the US and EU this month.
How many doses is the UK getting?In total, the UK government has pre-ordered 40 million single doses, which is enough for 18 million people assuming double dosing and about 10 per cent wastage. But it wont get all 40 million at once. The full order will be delivered in batches over the course of 2020 and 2021.
When will the vaccine reach the UK?The first batch is currently being packaged at Pfizers vaccine factory in Puurs, Belgium, and will be dispatched to the UK by lorry and plane as soon as it is ready possibly as early as the coming weekend. UK health minister Matt Hancock has said he expects the UK to receive 800,000 doses over the next few days.
When will vaccination start?Again, as soon as possible.
Doesnt the vaccine require complicated cold storage?Yes and no. For long-term storage meaning for six months or so the vaccine has to be kept at -70 C, which requires specialist cooling equipment. But Pfizer has invented a distribution container that keeps the vaccine at that temperature for 10 days if unopened. These containers can also be used for temporary storage in a vaccination facility for up to 30 days as long as they are replenished with dry ice every five days. Once thawed, the vaccine can be stored in a regular fridge at 2C to 8C for up to five days.
Could the supply chain be disrupted by the UKs formal departure from the EU as of 1 January?Possibly. But according to Marett, if there is disruption we will find another route.
Where will people be vaccinated?The usual places: GP surgeries, health centres and hospitals. People will be invited by the NHS. The entire supply is going to the various NHS bodies in the UK and nobody will be able to jump the queue by buying a vaccine privately, according to Pfizer.
Could something still go wrong?Yes, but that is highly unlikely. Vaccine effectiveness in the real world is almost always lower than efficacy in trials, but the drop-off would have to be spectacular to dip below the 50 per cent threshold accepted by the WHO.
There could still be rare severe adverse effects down the road, especially as mRNA vaccines are a new technology and have never been rolled out on a massive scale before.
Vaccine clinical trials arent big or long enough to rule out rare but serious side effects, which sometimes appear months or even years after vaccination. People who have been vaccinated will be followed up for two years to ensure that there are no serious adverse effect waiting in the wings.
But these are small, theoretical risks. As Fiona Watt at the UK Medical Research Council (MRC), said: This is great news.
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Everything you need to know about the Pfizer/BioNTech covid-19 vaccine - New Scientist News
For those who have a family history of chronic diseases, this is great news because it means that you can take control of your future by taking control of your health. Furthermore, you can focus your attention on lifestyle factors that you can control as opposed to the genetics that you cant control.
Seriously, stop it.
The fact is that your favorite snacks, fast food meal, and other processed foods are rich in sugar, salt, and trans fats all of which greatly increase your risk for chronic diseases that include cancer, heart disease, hypertension, and diabetes.
You are what you eat and if you want to be the epitome of longevity, then you need to eat foods that improve your lifespan, not shorten it. Adopting a plant-based diet is a great way to ensure that your body gets all the nutrients it needs to keep itself healthy in the coming years. Having said that, eating healthy doesnt mean that you need to say goodbye to all of your favorite treats. They can still be enjoyed, just in moderation.
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15 Things To Stop Doing If You Want To Live To 100 - Longevity LIVE - Longevity LIVE
Significant bonuses from Fleckvieh calves and cull cows have been important cash flow tools in a rain-fed Victorian dairy herd this year.
This has come on top of the Fleckvieh attributes of longevity, fertility, robustness and temperament for Richard Humphris of Beech Forest.
Dr Humphris left consulting work as a veterinarian 20 years ago to go full-time dairying.
He milks 200 cows off 110ha set in a 2000mm rainfall zone comprising clay loam soils.
Richard has 69ha of lower rainfall country for growing out the rising one-year-old and two-year-old heifers.
Originally we had a fair proportion of stud Holstein-Friesians in the herd but when we moved (from South Australia) to this high rainfall climate, it was a fair challenge for standard Jersey and Friesian cows, Dr Humphris said.
We ran into problems with fertility and mastitis so we moved to a Jersey/Friesian cross using New Zealand sires.
With the low milk prices, I thought I needed to do something different and saw an advertisement for dual-purpose Fleckviehs about eight years ago.
It was ideal a dual-purpose cow producing milk with the value-added beef component.
Dr Humphris initially used Fleckvieh semen over selected cows and has graded up to the point where matings are 100 per cent Fleckvieh.
Most of the milking herd is now three-quarter-bred Fleckvieh.
Dr Humphris was visited on-farm in 2015 by Dr Thomas Grup of Bayern-Genetik, Germany, and South African researcher Dr Carel Muller.
Dr Muller encouraged him to do simple comparative trials of the Fleckvieh crosses against other crossbreeds through herd testing on longevity and lifetime production.
We get much greater longevity from the Fleckviehs due to better fertility, less mastitis and a better recovery if mastitis does occur, Dr Humphris said.
The Saputo suppliers have transitioned to once-a-day milking to reduce stress on the family and herd, and leave extra time for essential farm maintenance and pasture production.
The move also meant they could use the existing 20-a-side swing-over dairy, avoiding extra capital costs.
In the first year of once-a-day milking, the herd produced 75,000kg of milk solids and had jumped to 99,000kg by the third season.
The herd averages 3932 litres, 4.9 per cent butterfat, 3.8 per cent protein and 348kg of milk solids across 287 days.
Last herd test, the highest daily lactation was Flekmaid at (once-a-day milking, second lactation) 31.8 litres, 4.5 per cent butterfat, 3.2 per cent protein and 2.45kg of milk solids.
Rurex daughter Joygirl showed what Fleckvieh crossbreds are capable of under Australian conditions by producing 6209litres, five per cent butterfat, 3.8 per cent protein, and 569kg of milk solids across the 305 day lactation (once a day).
Components over the spring months in the herd are four per cent protein and 4.7 per cent butterfat, increasing to 4.2 per cent protein and five per cent butterfat over the summer.
The most important thing is their temperament, they are beautiful cattle to work with and they have the other option of beef income, Dr Humphris said.
Due to the once-a-day milking and the environment, we find we do need excellent udders with a particular emphasis on udder depth and suspensory ligament.
If a Fleckvieh has to leave the herd it will mainly be due to a low-slung udder.
We are getting some really good uddered cows coming through now and that has helped our udder health.
If they do get mastitis, I have observed Fleckviehs have a better ability to recover they are sturdy, robust cows in this harsh Victorian climate where it can snow in the winter.
Where another cow may produce more on an individual daily basis, these cows have the ability to go on for a lot longer than our traditional Australian genetics in terms of fertility, lack of mastitis and survivability.
We have very few problems with lameness compared with our earlier years with other breeds but once a day milking does contribute to this reduced lameness.
Dr Humphris said the Fleckvieh added frame to the smaller crossbred females.
Fleckvieh fertility and once-a-day milking results in high conception rates with 80 per cent on the first service in the August-calving herd.
The couple joins 100 per cent of the herd to Fleckvieh sires, and they have daughters of Round Up, Rijeka, Waldoer, Reumut, Mahango, Waldbrand and Walfried.
We mop up with Fleckvieh beef bulls the calves have been one of the most exciting complements to the whole exercise, Dr Humphris said.
This year I did not sell one calf for slaughter at five days of age they all went for pasture finishing to adult animals in the local area.
I either sold them at one week of age or at eight weeks of age as a reared calf.
This gives a significant cash flow at the beginning of lactation through the sale of those calves for continuing beef production.
This results in the equivalent of 50kg of milk solids start on any other cow in terms of profitability.
Dr Humphris said the value of cull cows was a bonus on top.
I recently sold Jersey/Friesian cross cows for $850 compared to $1200 for the Fleckvieh crosses, he said.
During his career as a vet, Dr Humphris has experienced a range of calving difficulties in cattle.
At the beginning I was rather cautious about what I would have to face up to with the Fleckviehs calving, he said.
But they dont require assistance unless there is a malpresentation.
We dont select sires on calving ease but rather for production, udders and milk quality.
Our heifers are calved at two years of age we are not convinced this is the best but it suits our system.
The milkers are rotationally grazed across perennial rye-grass pastures and fed a mixed grain ration of 2.5kg in the bail.
Dr Humphris and his wife Christine have travelled to Bavaria, in Germany, to experience the Fleckvieh breed in its native environment and inspect sires.
We aim to select the highest TMI bulls with a big focus on udder, shape and function, he said.
It was enlightening going over there, talking to the breeders and seeing 100 per cent Fleckvieh herds.
Offering dual-purpose flexibility, they are a breed well worthwhile considering as we face these different economic and climatic challenges.
We love our Fleckviehs. They have strength, vitality and production of milk and meat, and live for the moment.
The Fleckviehs have a wonderful temperament they live life to the full full of grass, full of milk and full of meat. They cycle full-on and conceive full-on.
For more information on Bayern Genetik, phone George Cassar on 0265507661.
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Ticking the boxes in a rain-fed dairy system - Dairy News Australia
NEW YORK, Dec. 03, 2020 (GLOBE NEWSWIRE) -- IN8bio, Inc., a clinical-stage biotechnology company focused on developing innovative allogeneic, autologous and genetically modified gamma-delta T cell therapies for the treatment of cancers (IN8bio or the Company), today announced an upcoming presentation that provides an update of the ongoing Phase I clinical trial of their product candidate INB-100 at the 62nd American Society of Hematology Annual Meeting & Exposition (ASH), which will take place virtually from December 5 to 8, 2020. INB-100 is designed for the treatment of patients with leukemia undergoing hematopoietic stem cell transplantation with haploidentical donors.
The poster and accompanying narrated slide presentation is titled, First-in-Human Phase I Trial of Adoptive Immunotherapy with Ex Vivo Expanded and Activated gamma delta T-Cells Following Haploidentical Bone Marrow Transplantation and Post-BMT Cyclophosphamide and reviews the study design and provides a brief update on enrollment and patient status.
The company reported that, as of abstract submission, three female subjects with acute leukemia had been enrolled in the INB-100 Phase 1 trial, of whom two had been dosed, and that no treatment-related adverse events had been recorded. The trial is continuing to enroll and treat patients. The abstract for the presentation can be found at https://ash.confex.com/ash/2020/webprogram/Paper142876.html.
The poster and slide presentation are jointly authored by the scientific and physician investigators from IN8bio and The University of Kansas Cancer Center (KU Cancer Center), and will be presented by the studys Principal Investigator, Dr. Joseph McGuirk, Schutte-Speas Professor of Hematology-Oncology, Division Director of Hematological Malignancies and Cellular Therapeutics and Medical Director, Blood and Marrow Transplant at KU Cancer Center.
This preliminary data report from KU Cancer Center with our allogeneic product candidate, INB-100, demonstrates the absence of significant GvHD in these initial patients, said William Ho, Chief Executive Officer of IN8bio. This suggests that gamma delta T-cells delivered as an off-the-shelf allogeneic cell therapy may be well tolerated and have significant potential to treat patients with serious and life-threatening cancers.
Dr. McGuirk, commented, Potentially curative stem cell transplants using partially matched donors -- called haploidentical transplants have greatly expanded access to stem cell transplantation. The infusion of donor-derived gamma delta T-cells from the stem cell donor, offers the hope of diminishing this risk of relapse and curing more patients.
About IN8bioIN8bio is a clinical-stage biotechnology company focused on developing novel therapies for the treatment of cancers, including solid tumors, by employing allogeneic, autologous and genetically modified gamma-delta T cells. IN8bios technology incorporates drug-resistant immunotherapy (DRI), which has been shown in preclinical studies to function in combination with therapeutic levels of chemotherapy. IN8bio is currently conducting two investigator-initiated Phase 1 clinical trials for its lead gamma-delta T cell product candidates: INB-200 for the treatment of newly diagnosed glioblastoma, which is a difficult to treat brain tumor that progresses rapidly, and INB-100 for the treatment of patients with acute leukemia undergoing hematopoietic stem cell transplantation. For more information about the Company and its programs, visit http://www.IN8bio.com.
Forward Looking StatementsCertain statements herein concerning the Companys future expectations, plans and prospects, including without limitation, the Companys current expectations regarding the curative potential of its product candidates, constitute forward-looking statements. The use of words such as may, might, will, should, expect, plan, anticipate, believe, estimate, project, intend, future, potential, or continue, the negative of these and other similar expressions are intended to identify such forward looking statements. Such statements, based as they are on the current expectations of management, inherently involve numerous risks and uncertainties, known and unknown, many of which are beyond the Companys control. Consequently, actual future results may differ materially from the anticipated results expressed in such statements. Specific risks which could cause actual results to differ materially from the Companys current expectations include: scientific, regulatory and technical developments; failure to demonstrate safety, tolerability and efficacy; final and quality controlled verification of data and the related analyses; expense and uncertainty of obtaining regulatory approval, including from the U.S. Food and Drug Administration; and the Companys reliance on third parties, including licensors and clinical research organizations. Do not place undue reliance on any forward-looking statements included herein, which speak only as of the date hereof and which the Company is under no obligation to update or revise as a result of any event, circumstances or otherwise, unless required by applicable law.
Contact:IN8bio, Inc.Kate Rochlin, Ph.D.+1 646.933.5605info@IN8bio.com
Investor Contact:Julia Balanova+ 1 646.378.2936jbalanova@soleburytrout.com
Media Contact:Ryo Imai / Robert Flamm, Ph.D.Burns McClellan, Inc.212-213-0006 ext. 315 / 364Rimai@burnsmc.com/rflamm@burnsmc.com
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IN8bio announces first-in-human Phase 1 trial Update from The University of Kansas Cancer Center using INB-100, IN8bio's Gamma Delta T-cell product...
The feasibility of a precision medicinebased approach was demonstrated for patients with newly diagnosed acute myeloid leukemia (AML), according to findings from a phase 1/2 clinical trial reported in Nature Medicine.
The current standard of care for the treatment of patients diagnosed with AML involves prompt initiation of intensive induction chemotherapy, such as 7 days of standard-dose cytarabine and 3 days of daunorubicin, or administration of a hypomethylating agent for those deemed unable to tolerate standard induction therapy, to prevent rapid progression of disease in this predominantly older patient population.
Hence, time for comprehensive molecular characterization of the disease is not built into typical treatment protocols for patients with newly diagnosed AML. However, long-term outcomes of patients with newly diagnosed AML treated with intensive chemotherapy without autologous hematopoietic stem cell transplantation have been shown to be poor, and hypomethylating agents are not a curative approach in the setting of AML.
This nonrandomized, open-label, multicenter, umbrella protocol study sponsored by the Leukemia & Lymphoma Society (BEAT AML Master Trial; ClinicalTrials.gov Identifier: NCT03013998) enrolled adult patients with suspected AML prior to the administration of frontline treatment.
During a 7-day period prior to treatment assignment, bone marrow biopsy specimens of eligible patients were subjected to cytogenetic analysis, comprehensive molecular profiling using next-generation sequencing, and a FLT3-ITD ratio testing. On the basis of these results, patients with a dominant AML clone characterized by an actionable alteration were assigned to 1 of multiple molecularly defined substudy treatment arms, whereas those without evidence of such an alteration were assigned to the marker-negative subgroup.
In describing the purpose of this study, the investigators stated that they collaboratively implemented a new prospective clinical trial approach aimed at facilitating frontline treatment assignments to specific genomic-defined AML subtypes.
Of the 395 eligible patients, approximately 95% were assigned to treatment within 7 days of bone marrow biopsy collection. Of note, only 26 of these patients exhibited evidence of rapid disease progression necessitating initiation of therapy during the 7-day testing window.
The most common mutational drivers identified were DNMT3A (22.7%), TET2 (19.6%), TP53 (19.1%), ASXL1 (19.1%) and SRSF2 (18.4%).
Regarding molecularly based treatment assignment, the study authors commented that these data show that there were few co-occurring dominant mutations that could have been used for an alternative therapeutic assignment.
Only 224 (56.7%) of patients agreed to receive treatment according to their assigned BEAT AML substudy treatment arm, with 103, 28, and 38 patients selecting standard-of-care treatment, alternative investigational therapy, and palliative care, respectively.
Patients were encouraged to select an alternative therapy (alternative investigational therapy, [standard of care] or palliative care) if the patient with their health-care providers deemed this a better option, the study investigators noted.
A key finding from this study was the 30-day mortality of patients starting at initial study enrollment was 3.7% for patients enrolled on the BEAT AML trial protocol and 20.4% for those who choose to receive standard-of-care therapy.
Furthermore, rates of 1-year overall survival were 54.7%, 27.6%, 11%, and 57.4% for patients treated on the BEAT AML protocol, or with standard-of-care therapy, palliative care, and alternative investigational therapy, respectively.
However, the study investigators noted that while our study demonstrates the feasibility of precise molecular treatment assignment in older adults with AML, it does not clearly differentiate the benefit of treatment assignment based on a molecular target from better outcome that occurs simply from enrolling on a clinical trial.
They also emphasized that this approach requires a detailed team-coordinated effort by investigators, patients and caregivers, genomic laboratories, cytogenetic laboratories and a central treatment assignment team.
In their concluding remarks, the researchers commented that randomization of specific large genomic groups to targeted therapy versus [standard of care] or, in less common genomic groups, comparison of treatment with targeted therapy to either real-world data or synthetic controls, will be required to determine the comparative effectiveness of a precision medicine-based approach vs standard-of-care therapy in patients with newly diagnosed AML.
Reference
Burd A, Levine RL, Ruppert AS, et al. Precision medicine treatment in acute myeloid leukemia using prospective genomic profiling: feasibility and preliminary efficacy of the Beat AML Master Trial. Nat Med. Published online October 26, 2020. doi:10.1038/s41591-020-1089-8
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Possible Role for Comprehensive Molecular ProfilingBased Treatment Selection in Newly Diagnosed AML, Study Suggests - Cancer Therapy Advisor
DRESDEN, Germany, Dec. 3, 2020 /PRNewswire/ -- GEMoaB, a biopharmaceutical company focused on the development of next-generation immunotherapies for hard-to-treat cancers, today announced that it has apheresed the first patient in a Phase IA study with UniCAR-T-PSMA, the lead solid tumor product candidate from its proprietary UniCAR cellular immunotherapy platform. UniCAR-T-PSMA is investigated in late-stage, relapsed/refractory solid tumors expressing the PSMA antigen. The UniCAR platform has been designed to ensure excellent control over the universal CAR-T effector cell through a rapidly switchable on/off capability. This is combined with high flexibility to effectively target tumor antigens of choice by re-directing and activating UniCAR-T cells through soluble adapters termed Targeting Modules (TMs).
"The unique ability to rapidly switch on and off the UniCAR-T effector cells and thereby tightly control their activity as we have now clinically validated in our ongoing UniCAR-T-CD123 study in AML may help to overcome many of the limitations that conventional CAR-T therapies face when targeting less differentially expressed antigens, especially in solid tumors", said Prof. Dr. Gerhard Ehninger, GEMoaB's co-founder and Chief Medical Officer. "Our first UniCAR clinical study in solid tumors is of utmost importance for GEMoaB. We believe that the PSMA antigen is a great initial target as it is not only expressed on the tumor surface but also on the tumor neo-vasculature, allowing for a double attack of the malignant cells by UniCAR-T cells."
The Phase IA study includes patients with late-stage PSMA-positive relapsed/refractory solid tumors such as Castrate Resistant Prostate Cancer (CRPC), Non-small Cell Lung Cancer (NSCLC) or Triple Negative Breast Cancer (TNBC). It will examine the feasibility, safety and potential efficacy of the combined application of a single dose of UniCAR-T and the continuous infusion of the PSMA-specific TMpPSMA.
According to Prof. Dr. Ralf Bargou, Head of Comprehensive Cancer Center Mainfranken at the University Hospital Wrzburg and coordinating investigator of this trial, the study could be an important step in the ongoing intensive research efforts to establish cellular immunotherapies as a key therapeutic pillar to improve patient outcomes in hard-to-treat solid tumor cancers. "At our National Cancer Center in Wrzburg we are focusing a significant amount of our ongoing research and clinical efforts on developing breakthrough immunologic treatments of solid tumors together with our partners", said Prof. Bargou. "PSMA is a very promising target expressed in multiple late-stage cancers that do not sufficiently benefit from currently existing therapies and the UniCAR platform provides many features to finally obtain meaningful safety and efficacy results for this innovative treatment modality. We are very much looking forward working closely with the GEMoaB team on this important study."
About the UniCAR-T-PSMA Study
This first-in-human phase I study is an open-label, non-randomized, dose-finding study designed to evaluate the safety and activity of UniCAR-T-PSMA in up to 16 patients with advanced relapsed/refractory, PSMA-positive solid tumors such as CRPC, NSCLC or TNBC. Its purpose is to determine the maximum tolerated dose (MTD), dose limiting toxicities (DLT) as well as the recommended Phase II dose for the combined application of a single dose of UniCAR-T and the continuous infusion of TMpPSMA over 25 days. The study will also investigate response rates, persistence of UniCAR-T cells over time as well as the ability to rapidly switch UniCAR-T cells on and off in case of side effects through stopping the TM infusion. The study will take place at selected Phase I and CAR-T experienced University centers in Germany. It is supported by a grant from the European Regional Development Fund (ERDF) provided through Saxony's Development Bank (SAB). To learn more about the trial, please visit clinicaltrials.gov.
About UniCAR
GEMoaB is developing a rapidly switchable universal CAR-T platform, UniCAR, to improve the therapeutic window and increase efficacy and safety of CAR-T cell therapies in challenging cancers, including acute leukemias and solid tumors. Conventional CAR-T cells depend on the presence and direct binding of cancer antigens for activation and proliferation. An inherent key feature of the UniCAR platform is a rapidly switchable on/off mechanism (less than 4 hours after interruption of TM supply) enabled by the short pharmacokinetic half-life and fast internalization of soluble adaptors termed TMs. These TMs provide the antigen-specificity to activate UniCAR gene-modified T-cells (UniCAR-T) and consist of a highly flexible antigen binding moiety, linked to a small peptide motif recognized by UniCAR-T.
About GEMoaB
GEMoaB is a privately-owned, clinical-stage biopharmaceutical company that is aiming to become a fully integrated biopharmaceutical company. By advancing its proprietary UniCAR, RevCAR and ATAC platforms, the company will discover, develop, manufacture and commercialize next-generation immunotherapies for the treatment of cancer patients with a high unmet medical need.
GEMoaB has a broad pipeline of product candidates in pre-clinical and clinical development for the treatment of hematological malignancies as well as solid tumors. Its clinical stage assets GEM333, an Affinity-Tailored Adaptor for T-Cells (ATAC) with binding specificity to CD33 in relapsed/refractory AML, and GEM3PSCA, an ATAC with binding specificity to PSCA for the treatment of castrate-resistant metastatic prostate cancer and other PSCA expressing late stage solid tumors, are currently investigated in Phase I studies and globally partnered with Bristol-Myers Squibb. A Phase IA dose-finding study of the first UniCAR asset in hematological malignancies, UniCAR-T-CD123 for treatment of relapsed/refractory AML, is currently recruiting patients.
Manufacturing expertise, capability and capacity are key for developing cellular immunotherapies for cancer patients. GEMoaB has established a preferred partnership with its sister company Cellex in Cologne, a world leader in manufacturing hematopoietic blood stem cell products and a leading European CMO for CAR-T cells, co-operating in that area with several large biotech companies.
More information can be found at http://www.gemoab.com.
For further information please contact
Jana Fiebigerj.fiebiger@gemoab.com; Tel.: +49 351 4466-45012
Investor Contact
Michael Pehlm.pehl@gemoab.com; Tel.: +49 351 4466-45030
Forward-looking Statements This announcement includes forward-looking statements that involve risks, uncertainties and other factors, many of which are outside of our control, that could cause actual results to differ materially from the results and matters discussed in the forward looking statements. Forward looking statements include statements concerning our plans, goals, future events and or other information that is not historical information. The Company does not assume any liability whatsoever for forward-looking statements. The Company assumes that potential partners will perform and rely on their own independent analyses as the case may be. The Company will be under no obligation to update the Information.
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Initiation of First UniCAR Cellular Immunotherapy Study in Advanced Solid Tumors - BioSpace
Abstract
While a genetic component of preterm birth (PTB) has long been recognized and recently mapped by genome-wide association studies (GWASs), the molecular determinants underlying PTB remain elusive. This stems in part from an incomplete availability of functional genomic annotations in human cell types relevant to pregnancy and PTB. We generated transcriptome (RNA-seq), epigenome (ChIP-seq of H3K27ac, H3K4me1, and H3K4me3 histone modifications), open chromatin (ATAC-seq), and chromatin interaction (promoter capture Hi-C) annotations of cultured primary decidua-derived mesenchymal stromal/stem cells and in vitro differentiated decidual stromal cells and developed a computational framework to integrate these functional annotations with results from a GWAS of gestational duration in 56,384 women. Using these resources, we uncovered additional loci associated with gestational duration and target genes of associated loci. Our strategy illustrates how functional annotations in pregnancy-relevant cell types aid in the experimental follow-up of GWAS for PTB and, likely, other pregnancy-related conditions.
Spontaneous preterm birth (PTB), defined as spontaneous labor and birth before 37 weeks of gestation, is associated with considerable infant mortality and morbidity, as well as long-term health consequences into adulthood (1). A genetic component to PTB has long been recognized, but the significant role of environmental factors and the etiologic heterogeneity of birth before 37 weeks (24) have made it challenging to discover genetic associations and causal genes. For example, recent genome-wide association studies (GWASs) of gestational duration in 43,568 women (3331 with a preterm delivery) (5) and in 84,689 infants (4775 born preterm) (6) reported six and one genome-wide significant associations, respectively, with gestational duration considered as a continuous variable. Three loci were also associated with PTB (defined as a categorical variable of birth) in the maternal GWAS (5), but no loci were associated with PTB in the infant GWAS (6). These studies highlight the challenges of such complex and multifactorial phenotypes and the need for additional approaches to facilitate discovery of genes contributing to gestational duration and PTB.
Integrating GWAS that results with genomic and epigenomic annotations is a promising approach for assigning function to variants discovered by GWAS, as well as for identifying additional associations that do not reach stringent genome-wide significance threshold (7, 8). While large consortia [e.g., ENCODE (Encyclopedia of DNA Elements) (9), GTEx (Genotype-Tissue Expression Project) (10), and Roadmap Epigenomics (11)] have generated annotations of putative functional elements and genetic variants for many human cell types and tissues, there is a remarkable absence in these databases for the cell types and tissues that are relevant to pregnancy in general and to PTB in particular. Because the regulation of transcription has strong cell typespecific components and because annotations in disease-relevant tissues or cells tend to be most enriched among GWAS signals for those specific diseases (10, 12), follow-up studies of GWASs of pregnancy-associated conditions have been disadvantaged compared to most other complex diseases due to the paucity of functional annotations in cells relevant to pregnancy. To fill this gap in knowledge, we characterized the transcriptional and chromatin landscapes of cultured mesenchymal stromal/stem cells (MSCs) collected from human placental membranes and decidualized MSCs, also known as decidual stromal cells (DSCs). These cells play critical roles in promoting successful pregnancy, interfacing with fetal cells throughout pregnancy, and the timing of birth (13, 14). We then built a computational framework that integrated these decidua-derived stromal cell annotations with the results of a large GWAS of gestational duration to facilitate discovery of PTB genes.
This integrated analysis revealed a significant enrichment of heritability estimates for gestational duration in decidua-derived stromal cell genomic regions marked by open chromatin or histone marks. Leveraging those functional annotations in a Bayesian statistical framework, we discovered additional loci associated with gestational duration and improved fine mapping in regions associated with gestational duration. Last, using promoter capture Hi-C (pcHi-C), we linked functionally annotated gestational age-associated variants to their putative target genes. More generally, these functional annotations should prove a valuable resource for studying other pregnancy-related conditions, such as preeclampsia and recurrent miscarriage, as well as conditions associated with endometrial dysfunction, such as endometriosis and infertility.
Decidualization is the process of transformation of endometrial MSCs into DSCs that is induced by progesterone production that begins during the luteal phase of the menstrual cycle and then increases throughout pregnancy when successful implantation occurs [reviewed in (15)]. Using progesterone and estrogen or cyclic adenosine 5-monophosphate (cAMP) to induce decidualization of MSCs in culture has been used in cells derived from endometrial biopsies in nonpregnant women to characterize their transcriptomes and epigenomes and to identify genes and molecular pathways involved in this process (1621).
Because obtaining endometrial cells in nonpregnant women through biopsies requires an invasive procedure that carries some risk and MSCs can also be obtained from human placentas (2224), we isolated these cells from the decidua parietalis of three women who had delivered at term and established one primary MSC line from each to model the process of decidualization (see Materials and Methods). Briefly, cells were treated with medroxyprogesterone acetate (MPA) and cAMP for 48 hours, and a paired set of untreated samples was cultured in parallel for 48 hours. Three replicates of treated/untreated sets of each cell line were studied to assess experimental variability in the two conditions. Each of the 18 samples (3 individual lines 3 replicates 2 conditions) were assayed to generate transcriptome [RNA sequencing (RNA-seq)], open chromatin [assay for transposase-accessible chromatin sequencing (ATAC-seq)], and histone modification [chromatin immunoprecipitation sequencing (ChIP-seq)] maps. A summary of those data is shown in table S1, and a representative example of the full set of annotations for one primary cell line is shown in Fig. 1. The number of reads generated for each sample in each condition and other descriptive data are provided in data file S1.
Each histone modification and RNA-seq track shows read counts per base pair for each experiment. The pcHi-C signal track shows the number of reads per MboI restriction fragment. Arcs in the pcHi-C interactions track show significant interactions between the promoter of the PRL gene and putative distal regulatory elements identified with pcHi-C. Pooled data (three replicates) for one cell line are shown for untreated cells (MSCs, in green) and decidualized cells (DSCs, in purple). pcHi-C data were generated in a fourth cell line that was decidualized.
Analysis of the RNA-seq data using DESeq2 (25) revealed 1135 differentially expressed genes after decidualization (table S1). Genes with decreased expression after 48 hours of treatment were highly enriched for cell cycle genes (data file S2), consistent with observations from endometrial biopsies from nonpregnant women that decidualization is associated with cell cycle arrest (19, 26). Genes with increased expression after treatment were enriched for insulin-related terms, also consistent with previous results from endometrial biopsies (26), and for glucose metabolism (18).
To identify putative regulatory elements in MSCs and DSCs, we assayed H3K27ac, H3K4me1, and H3K4me3 histone modifications, which are markers of active enhancers, poised enhancers, and active promoters, respectively [reviewed in (27)]. We also used ATAC-seq to identify open chromatin regions to complement ChIP-seq data. To identify regulatory regions that might be altered in response to, and potentially regulate decidualization, we compared read counts of ATAC-seq and ChIP-seq peaks in untreated and decidualized cells, revealing tens of thousands of regions that differed between untreated and treated samples (table S1). Most of the differential peaks were marked with H3K27Ac and H3K4me1, indicating that the epigenetic changes underlying alterations in gene expression during decidualization predominantly occur in distant regulatory elements, such as enhancers.
We observed a moderate degree of overlap between the differential peaks across ATAC-seq and ChIP-seq data, with the two enhancer marks, H3K27ac and H3K4me1, showing the most overlap (Fig. 2A). In addition, putative regulatory regions that showed chromatin changes in response to decidualization were associated with genes whose expression also changed in response to decidualization (Fig. 2B). Regulatory regions with increased read counts clustered around genes that were more highly expressed after decidualization, indicating increased chromatin accessibility or activation of enhancers of those genes. Conversely, genes that were more lowly expressed after decidualization were enriched for enhancers that became less accessible or active. These observations indicate that the differential peaks of open chromatin and histone marks observed after decidualization correspond to regulatory elements that become more or less active, resulting in correlated gene expression changes of the nearby genes.
(A) Plot showing the overlap between the different histone modifications and ATAC-seq maps (intersection between annotations). Peaks were assigned to 100-bp bins to avoid ambiguity in overlap due to different peak borders. Black circles indicate overlap with other annotations; light gray circles indicate that the annotation does not overlap others. (B) Each data point shows the ratio between the number of increased/decreased differential peaks nearby genes that increase expression after decidualization (blue, positive log ratios; upper half of the figure) or decrease expression after decidualization (orange, negative log ratios; lower half of the figure). Genes that were more highly expressed in decidualized cells were flanked by a higher number of ChIP-seq and ATAC-seq peaks that displayed increased read counts in decidualized samples compared to peaks that displayed decreased read counts (top inset). Genes that were down-regulated in decidualized cells showed the opposite trend (bottom inset). All enrichments: P < 1025. (C) DNA binding motifs of transcription factors relevant in decidualization are enriched in peaks that change following decidualization treatment. Motifs are color-coded by similarity. (D) Colocalization of PGR, FOSL2, FOXO1, GATA2, and NR2F2 with ATAC-seq and ChIP-seq peaks. Transcription factor binding sites co-occur with ATAC-seq and ChIP-seq peaks in both untreated (green) and decidualized (purple) cells more often than with random peaks. Enrichment of the co-occurrences of PGR, FOXO1, GATA2, and NR2F2 are higher when co-occurring with peaks that have increased read counts (navy blue) and lower with peaks that have decreased read counts (orange) in decidualized compared to untreated cells. Enrichment of co-occurrences with peak sets was calculated as the fold difference between the number of transcription factor peaks overlapping with ATAC-seq/ChIP-seq peaks and with a random set of peaks (see Materials and Methods).
Previous work identified transcription factors that play critical roles in decidualized stromal cells (2832). Several of the DNA binding motifs that were enriched in peaks with increased or decreased read counts in our data correspond to transcription factors previously implicated in decidualization (Fig. 2C), such as CAAT-enhancer binding protein (CEBP) (33), progesterone receptor (PGR) (28) that shares the same motif with androgen response element, and glucocorticoid receptor, FOSL2 (Fos-related antigen 2) (28), that shares the same motif with Fra1 (Fos-related antigen 1), Atf3 (Activating transcription factor 3), and BATF (basic leucine zipper ATF-like transcription factor), and TEA (transcriptional enhancer factor) domain transcription factors (21, 34). Whereas CEBP and PGR were exclusively enriched in peaks with increased read counts in decidualized cells, the FOSL2 motif was present in peaks that both changed positively and negatively in decidualized cells.
To better understand the role of these transcription factors in decidualization, we obtained publicly available ChIP-seq data for PGR (28) and FOSL2 (28) from endometrial biopsies and analyzed the colocalization of their binding locations with the putative regulatory elements identified by ATAC-seq and ChIP-seq identified in our study (Fig. 2B). We additionally analyzed FOXO1 (Forkhead box O1) (29), NR2F2 (nuclear receptor subfamily 2 group F member 2) (30), and GATA2 (GATA binding protein 2) (31) ChIP-seq data because these transcription factors have also been implicated in decidualization (2931). With the exception of FOSL2, the colocalization enrichments of PGR, FOXO1, GATA2, and NR2F2 with ATAC-seq and ChIP-seq peaks were higher (9 to 16 folds) among peaks that were increased in decidualized cells (more open chromatin or increased histone modification levels) compared to all peaks (7.5 to 12.8 folds) and to peaks that decreased in decidualized cells (2 to 5 folds). This observation supports the notion that these transcription factors are involved in regulation of decidualization (2831, 35). Although FOSL2 has been reported as a positive coregulator of PGR (28), the presence of FOSL2 motifs in peaks that both increased and decreased in decidualized cells (Fig. 2C) and the lack of difference in the colocalization enrichment between these two sets of peaks (Fig. 2D) suggests that FOSL2 may have a dual role in decidualization.
Together, our results support a model of decidualization that involves changes in the regulatory landscape during the differentiation of MSCs into DSCs, including alterations in chromatin accessibility and in the activation levels of distant regulatory elements, accompanied by the differential binding of key transcription factors, resulting in increases or decreases in gene expression.
As shown in Fig. 2B, the surrounding regions of differentially expressed genes were enriched for differential ChIP-seq and ATAC-seq peaks that changed in the same direction as the genes in decidualized samples. Accordingly, when we paired differential peaks with the nearest expressed gene as its putative gene target, we observed that these pairs were more likely to have matching directions of change (i.e., both the peak and the gene have increased or decreased read counts in decidualized samples) than nonmatching directions when compared with pairs that were assigned randomly (Fig. 3A).
(A) Randomly assigning a gene to a peak (see Materials and Methods) resulted in fewer peaks that matched the direction of change with that of differentially expressed genes than when using pcHi-C interactions or the nearest gene to pair peaks to genes. (B) The FOXO1 gene is more highly expressed in decidualized samples (fourfold increase, P = 7 1022) and its promoter physically interacts (red arcs) with distal regulatory elements (yellow highlights) that show increased activation in decidualized samples. The nearest expressed gene to these differential peaks is COG6.
In many cases, however, the target gene for a regulatory element is not the nearest gene (36), and therefore, information about distal chromatin interactions can be useful in prioritizing candidate gene targets of variants identified in GWAS. To this end, we generated a pcHi-C map of a decidualized cell line, thus enriching for the identification of long-range chromatin interactions between promoters and distant regulatory elements (3739). We identified a total of 161,337 interactions, of which 53,211 were between promoters and distal regions of accessible chromatin assayed by ATAC-seq and ChIP-seq, suggestive of their regulatory role. We used the significant interactions between promoters and distal regions that we identified to pair differential peaks with putative target genes. As shown in Fig. 3A, using pcHi-C interactions as a pairing method resulted in enhanced identification of differential peak/differential target gene pairs that have matching directions of change compared to random assignment of gene-target pairs.
Whereas assigning peaks to the nearest expressed gene also led to enhanced assignment of differential peaks to target genes with matching directions of change (Fig. 3A), pcHi-C was helpful in identifying less obvious target genes, as shown in Fig. 3B. In this example, several pcHi-C interactions link distal regulatory elements up to 847 kb away that became more active in decidualized cells to the promoter of a gene (FOXO1) that was up-regulated in decidualized cells and is known to be involved in decidualization (32). The nearest expressed gene method assigned those differential peaks to COG6, a gene that does not change expression in decidualized samples and is therefore a less likely target.
In conclusion, by combining pcHi-C interactions with the epigenome maps and transcriptome data, we were able to identify genes and putative regulatory elements that respond to, or regulate, the decidualization process. We next used these functional genomic maps and datasets to fine map GWAS loci for gestational duration and identify new candidate genes with a potential role in PTB.
To identify candidate genes that may play a role in gestational duration and PTB, we used summary data from a GWAS of gestational duration based on a meta-analysis of a 23andMe GWAS (n = 42,121) (5) and the results from six European datasets (n = 14,263). A detailed description of the GWAS is in the Supplementary Materials and figs. S1 and S2. After filtering for single-nucleotide polymorphism (SNPs) that are present in the 1000 Genomes Project data and minor allele frequency of >0.01, we identified SNPs at six autosomal loci, defined as approximately independent blocks by LDetect (40), that were associated with gestational duration at genome-wide significance of P < 5 108 (table S2). We then created a computational pipeline to assess enrichment of GWAS signals in functional annotations that we generated in untreated (MSCs) and decidualized (DSCs) stromal cells to fine map GWAS loci and discover candidate causal genes and to potentially provide support for additional loci that did not reach genome-wide significance in the GWAS (Fig. 4A). Each step of this procedure is explained below and described in details in Materials and Methods.
(A) Computational pipeline for analyzing GWAS of gestation duration. Yellow boxes (input data): GWAS summary statistics and functional annotations from endometrial stromal cells (in both untreated and decidualized cells). Green boxes: Stages of statistical analysis (see Materials and Methods). (B) Stratified LDSC heritability analysis of GWAS of gestational duration using functional annotations. Left: Fold enrichment of heritability in each annotation. Dashed line shows values at 1, i.e., no enrichment. Center: Proportion of heritability explained by each annotation. Right: Proportion of SNPs across the genome that fall within an annotation. For each annotation, enrichment (left) is the ratio of h2 proportion (center) divided by the SNP proportion (right). Error bars represent 95% confidence intervals.
We first used stratified linkage disequilibrium (LD) score regression (S-LDSC) (41) to assess enrichment of GWAS signals in functional annotations in endometrial stromal cells. S-LDSC takes as input GWAS summary statistics across the genome and functional annotations of SNPs, e.g., whether an SNP is in ATAC-seq peak, and returns as output heritability enrichment of each annotation. S-LDSC is a commonly used tool for estimating the proportion of heritability of complex phenotypes that is explained by variants in certain functional annotations. The heritability enrichment is defined by the proportion of heritability explained by annotations divided by the expected proportion, which is the percent of SNPs genome wide that are in these functional annotations. To account for possible systematic bias in this analysis, i.e., SNPs within annotations of interest may differ from background SNPs in systematic ways such as their LD structure and epigenomic properties, we included a range of baseline annotations (default S-LDSC setting), including LD-related annotations, deoxyribonuclease (DNase) hypersensitivity, enhancer annotation, H3K27ac, H3K4me1, and other histone marks (the union across cell types). Thus, if an annotation is shared by many cell types, then it would not show the enrichment in S-LDSC analysis (see Materials and Methods).
Using S-LDSC, we found 5- to 10-fold enrichments of GWAS heritability for gestational duration in our functional annotations compared to the baseline model of S-LDSC (Fig. 4). The enrichment of enhancer marks H3K27ac and H3K4me1 was higher in decidualized than in untreated cells, but the opposite pattern was observed for the promoter mark H3K4me3, which was more enriched in untreated (MSCs) than in decidualized (DSCs) cells. These findings are consistent with previous observations that enhancers are often more dynamic and condition- or tissue-specific than promoters (10). We observed weaker heritability enrichments of open chromatin regions defined by ATAC-seq and of interaction regions in pcHi-C. However, because we performed joint analysis of all annotations together, the enrichment of one annotation (e.g., ATAC-seq peaks) will be reduced if the enrichment is partially explained by other, overlapping annotations (e.g., H3K27ac). Although the promoter mark H3K4me3 in untreated cells showed the highest enrichment, the annotations that contributed most to the heritability of gestational duration were enhancers (Fig. 4) due to the much larger number of enhancer histone marks than promoters in the genome. Our results thus highlight the importance of functional annotations in endometrial stromal cells at GWAS loci for gestational duration.
We next developed a computational procedure, based on fine mapping, to integrate the decidua stromal cell functional maps with a GWAS of gestational duration to identify putative causal variants (Fig. 4A). Because of extensive LD in the human genome, the causal variants driving the associations are unknown at most loci discovered by GWAS. Fine mapping is a Bayesian statistical procedure that takes as input GWAS summary statistics and patterns of LD at trait-associated loci and computes the probability of each variant at a locus to be a causal variant (7). These probabilities, known as posterior inclusion probabilities (PIPs), reflect our confidence of certain SNPs being causal variants. The PIP of a variant ranges from 0 to 1, with 1 indicating full confidence that the SNP is a causal variant. If a region contains a single causal variant, the PIPs of all SNPs in the region should approximately sum to 1.
While fine mapping has been commonly used in identifying putative causal variants from GWAS of complex traits (7), it is often difficult to narrow down causal signals to one or a small number of variants in most GWAS loci. Standard fine mapping treats all SNPs at a locus equally. Recent work suggests that incorporating Bayesian prior probabilities that favor functional SNPs improves fine mapping (8, 42). We posited that integrating functional annotations in pregnancy-relevant cells in a statistical fine-mapping framework would aid in (i) identifying candidate causal variants at each locus associated with gestation duration, (ii) linking those variants to their target genes, and (iii) discovering additional loci and genes associated with gestational duration that may have failed to reach the stringent threshold for significance in GWAS.
We first leveraged the enrichments of DSC annotations to create Bayesian prior probabilities for a variant being causal. On the basis of the results of S-LDSC, we chose H3K27ac, H3K4me1, and pcHi-C interactions from the decidualized cells, and H3K4me3 from untreated cells, as functional genomic annotations to create informative priors using TORUS (42). TORUS takes as input genome-wide summary statistics from GWAS and the functional annotations of SNPs and computes enrichment parameters of annotations, which reflect how much more likely an SNP is a causal variant than randomly chosen SNPs (table S3). SNPs associated with functional annotations are generally assigned higher prior probabilities. In addition, TORUS computes statistical evidence at the level of genomic blocks, defined as the probability that a block (determined by LD) contains at least one causal SNP. Without including any histone marks or chromatin accessibility annotations, TORUS implicated six autosomal blocks in the genome at false discovery rate (FDR) of < 0.05, including five of the six genome-wide significant autosomal loci identified in the GWAS (P < 5 108). One locus on chromosome 3 had an FDR = 0.11 and was therefore not identified by TORUS, and one locus on chromosome 9 that was not identified in the GWAS was implicated by TORUS (data file S3). By including the functional genomic annotations from endometrial stromal cells, the number of high confidence blocks increased to 10, including all 6 that were significant in the gestational duration GWAS and 4 that were not significant in the GWAS (data file S3).
We next performed computational fine mapping on these 10 blocks, with the informative priors learned by TORUS, using sum of single effects (SuSiE) regression (43). Conceptually, SuSiE is a Bayesian version of the stepwise regression analysis commonly used in GWAS (i.e., conditioning on one variant and testing if there is any remaining signal in a region). SuSiE accounts for the uncertainty of causal variants in each step and reports the results in the form of PIPs. Including the priors defined by TORUS using DSC functional annotations significantly improved fine mapping (Fig. 5A, table S3, and data file S4). For example, only one SNP reached PIP > 0.3 across all 10 blocks using the default setting under SuSiE (uniform prior, treating all SNPs in a block equally). This reflects the general uncertainty of pinpointing causal variants due to LD, e.g., a strong GWAS SNP in close LD with nine other SNPs would have PIP about 0.1. By using the annotation-informed priors, eight SNPs in six different blocks reached PIP > 0.3 (Fig. 5A). In some blocks, we were able to fine-map a single high-confidence SNP, e.g., the FOXL2 locus on chromosome 3, while in other blocks, we had considerable uncertainty of the causal variants, as shown by large credible sets, i.e., the minimum set of SNPs to include the causal SNP with 95% probability (Fig. 5B). Table 1 summarizes the most probable causal variants in eight blocks (fine mapping in the remaining two blocks produced large credible sets with no high-PIP SNPs) and their likely target genes based on promoter assignment or chromatin interactions from pcHi-C. We note that our results of the WNT4 locus identified rs3820282 as the likely causal variant. This is consistent with our previous results demonstrating experimentally that the T allele of this SNP disrupts the binding of estrogen receptor 1 (5). This SNP was among the three most likely SNPs in our fine-mapping study, with a PIP of 0.27 (Table 1).
(A) PIPs of SNPs using uniform vs. functional priors in SuSiE (each dot is an SNP). The functional prior of an SNP is based on SNP annotations and is estimated using TORUS. (B) Summary of fine-mapping statistics of all 10 regions. X axis: The size (number of SNPs) of credible set. Y axis: The maximum PIP in a region. We label each region by its top SNP (by PIP) and the likely causal gene, according to Table 1 or the nearest gene of the top SNP. (C) Likely causal variants near HAND2 and their functional annotations. The top panel shows the significance of SNP association in the GWAS and the middle panel shows fine-mapping results (PIPs) in the region. The vertical yellow bar highlights the two SNPs with high PIPs. These SNPs are located in a region annotated with ATAC-seq, H3K27ac, H3K4me1, and H3K4me3 peaks (bottom). This putative enhancer also had increased ATAC-seq, H3K27ac, and H3K4me1 levels in decidualized samples and interacts with the HAND2 promoter (red arc).
Functional annotations are based on data from endometrial stromal cells. We list an annotation if the SNP is located in a sequence with that annotation in either untreated or decidualized condition. Functional prior is the prior probability of an SNP being a causal variant. For an SNP without any functional annotation, its prior probability is 3.6 106. We list the pcHi-C annotation if the SNP is within 1 kb of a region involved in a pcHi-C interaction. We call a gene the target of an SNP if (i) the SNP is located in the promoter (< 1 kb of transcription start site) of that gene or (ii) the promoter of that gene has a pcHi-C interaction with a region within 1 kb of the SNP. In the case of rs147843771 at the FOXL2 locus, the target was defined by literature evidence (69). The number of credible SNPs at each region is shown in Fig. 5B. SNPs in bold are discussed in the text. FOXL2 (69), forkhead box L2; GATA2, GATA-binding protein 2; HAND2, heart and neural crest derivatives expressed 2; KCNAB1, potassium voltage-gated channel subfamily A member regulatory beta subunit 1; WNT4, Wnt family member 4.
We highlight the results from two regions. In both cases, we were able to identify putative risk genes with relatively high confidence, and neither is the nearest gene of lead SNPs in GWAS. In the first case, two adjacent SNPs [311base pair (bp) apart], rs13141656 and rs7663453, on chromosome 4q34 did not reach genome-wide significance in the GWAS (P = 3.9 107 and 4.5 107, respectively). After using functional annotations in decidua-derived stromal cells, the block containing these SNPs was highly significant (TORUS q = 0.02), suggesting the presence of at least one causal variant in this block. The two SNPs together explained most of the PIP signal in the block (PIP 0.38 and 0.33, respectively, Table 1). The two SNPs are located in a region of open chromatin in endometrial stromal cells, with enhancer activity marked by both H3K27ac and H3K4me1 (Fig. 5C). Only 9 of the 129 tissues from the Epigenome Roadmap (11) also had H3K27ac, H3K4me1, or H3K4me3 peaks spanning the rs13141656 locus and only 2 spanning the rs7663453 locus. In addition, this putative enhancer is bound by multiple transcription factors, including GATA2, FOXO1, NR2F2, and PGR, based on ChIP-seq data. The only physical interaction of this enhancer in the pcHi-C data in decidualized stromal cells is with the promoter of the HAND2 gene, located 277 kb away (Fig. 5C). Summing over the PIPs of all SNPs whose nearby sequences interact with HAND2 (heart and neural crest derivatives expressed 2) via chromatin looping gives an even higher probability, 0.89, suggesting that HAND2 is very likely to be the causal gene in this region (table S4). HAND2 is an important transcription factor that mediates the effect of progesterone on uterine epithelium (44). Thus, in this example, we identified a previously unknown locus, the likely causal variant(s), the enhancers they act on, and an outstanding candidate gene for gestational duration and PTB.
The second example focuses on the locus showing a strong GWAS association with gestational duration on chromosome 3q21. The lead SNP, rs144609957 (GWAS P = 4 1013), is located upstream of the EEFSEC (eukaryotic elongation factor, selenocysteine-tRNAspecific) gene. There is considerable uncertainty of the causal variants in this region, with 50 SNPs in the credible set and the lead SNP explaining only a small fraction of signal (PIP = 0.02). Among all 12 SNPs with PIP > 0.01, 11 have functional annotations, most commonly H3K4me1 and pcHi-C interactions. For nine SNPs (first three shown in Table 1), the sequences in which they are located physically interact with the promoter of GATA2 in the pcHi-C data but not with any other promoters in the region (fig. S3). The PIPs of all SNPs in the genomic regions that likely target GATA2 through chromatin looping sum to 0.68 (table S5). Thus, despite uncertainty of causal variants in this region, our results implicate GATA2 as a candidate causal gene in endometrial stromal cells. GATA2 is a master regulator of embryonic development and differentiation of tissue-forming stem cells (45). As support for the possible role of GATA2 in pregnancy, GATA2 deficient mice show defects in embryo implantation and endometrial decidualization (35), making this another excellent candidate causal gene for gestational duration and PTB.
The molecular processes that signal the onset of parturition in human pregnancies, and how perturbation of those processes result in PTB, are largely unknown. Yet, understanding these processes would reveal important insights into the potential causes of adverse pregnancy outcomes, including spontaneous labor before 37 weeks gestation, and potentially lead to the identification of biomarkers and therapeutic targets for PTB. Although it is experimentally challenging to link decidualization processes directly to parturition in humans, it is well accepted that shallow implantation due to suboptimal decidualization is associated with poor pregnancy outcomes in general (4648) and that the decidua is key in triggering parturition (13, 14). Thus far, however, specific genes that perturb decidualization processes and lead to PTB are poorly defined.
Unbiased GWASs do not require prior knowledge of molecular processes underlying disease phenotypes and have the potential to identify novel genes and pathways contributing to common diseases. However, the significant heterogeneity of most common diseases and small effects of most common disease-associated variants lead to the requirement for very large sample sizes (in the tens to hundreds of thousands of cases) to discover more than a handful of associated loci that meet stringent criteria for genome-wide significance. To address this limitation and provide orthogonal evidence for assessment of associations, we characterized the transcriptional and chromatin landscapes in decidua-derived stromal cells and integrated those functional annotations with a GWAS of gestational duration to discover novel loci and genes. The primary motivation for these studies was the notable paucity of genomic and epigenomic functional annotations in pregnancy-relevant primary cells among those studied by large consortia (911). Here, we filled a significant gap by providing maps in untreated and decidualized stromal cells and used these maps for annotating GWAS of pregnancy-related traits.
We chose to focus these studies on endometrial stromal cells because of their central importance in both the establishment and maintenance of pregnancy, as well as their intimate juxtaposition to fetal trophoblast cells throughout pregnancy. Of particular relevance are the roles that decidualized stromal cells play in regulating trophoblast invasion, modulating maternal immune and inflammatory responses at the maternal-fetal interface, and controlling remodeling of the endometrium (48). Defects in all of these processes have been considered a contributing factor to pregnancy disorders (48, 49). Moreover, we showed that the SNPs in regions with endometrial stromal cell functional annotations explained more of the heritability of gestational duration compared to just using baseline annotations. Among all annotations, enhancer marks H3K4me1 (in both decidualized and untreated stromal cells) and H3K27ac (in decidualized cells) were 8- to 10-folds enriched at GWAS loci after adjusting for the general annotations and accounted for 50 to 70% of the GWAS heritability. The lack of complete independence between these marks makes it difficult to delineate their individual effects but, nonetheless, highlights the importance of enhancers and of gene regulation in endometrial stromal cells in modulating the effects of GWAS variants on gestational duration. This is consistent with both the known tissue-specific roles of enhancers and the observation that more than 90% of GWAS loci reside outside of the coding portion of the genome and are enriched in regions of open chromatin and enhancers (12, 41).
Integrating transcriptional and chromatin annotations of gene regulation from MSCs and DSCs improved our ability to discover novel GWAS loci and identify likely causal SNPs and genes associated with gestational duration. We illustrate how our integrated platform identified a novel causal locus and candidate gene (HAND2) associated with gestational duration, as well as refined the annotation of loci that had been previously identified. Our data suggest that in endometrial stromal cells, GATA2 is likely the target gene of enhancers harboring SNPs associated with gestational duration. This does not exclude the possibility that the nearest gene to the associated SNPs, EEFSEC, may be a target gene in other cell types. Both HAND2 (50) and GATA2 (51) are involved in decidualization processes in humans, and perturbations in this process have been linked to poor pregnancy outcomes (4648). Neither GATA2 nor HAND2 was identified as potential candidate genes in previous GWASs of gestational duration, or PTB supports our approach and the importance of using functional annotations from cell types relevant to pregnancy to fine map and identify candidate genes for the pregnancy-related traits. Overall, the integrated analyses performed in this study resulted in the identification of both novel GWAS loci and novel candidate genes for gestational duration, as well as maps of the regulatory architecture of these cells and their response to decidualization.
However, there are some limitations. Our results are based on cells from only three individuals, which may not fully capture the regulatory landscape of endometrial stromal cells. For pcHI-C, we used cells from a single individual to generate the chromatin interactions map. Another limitation is that we focused on only one cell type, albeit one that plays a central role in pregnancy and only one exposure (hormonal induction of decidualization) at one time point (48 hours). Furthermore, it is unclear how our model of in vitro decidualization mimics the endogenous decidualization of endometrial cells during pregnancy. While we chose decidualization as a perturbation to ascertain the dynamic features of functional genomic annotations, we fully anticipate that obtaining annotations in other cell types and in response to other relevant perturbations will improve the ability to identify novel loci, variants, and genes associated with PTB. Future studies that include fetal cells from the placenta and uterine or cervical myometrial cells could reveal additional processes that contribute to gestational duration and PTB, such as those related to fetal signaling and the regulation of labor, respectively. Inclusion of additional exposures, such as trophoblast conditioned media (52) and additional exposure times, may further reveal processes that are pregnancy specific. Second, to maximize power, we focused on a GWAS of gestational duration and not PTB per se. While previous GWAS have shown that all PTB loci were among the gestational age loci (5), we realize that some of the loci that we identified could be related to normal variation in gestational duration and not specifically to PTB. Nonetheless, our findings contribute to our understanding of potential mechanisms underlying the timing of human gestation, about which we still know little. Last, although our ChIP-seq results revealed an association between GATA2 binding and decidualization, confirming the role of this transcription factor in decidual cell biology (53, 54), and studies in murines support its role in endometrial processes (35), we do not yet have direct evidence showing that perturbations in the expression of GATA2, or any of the other target genes identified, influence the timing of parturition in humans. Future studies will be needed to directly implicate the expression of these genes in gestational duration or PTB. Our study highlights the importance of generating functional annotations in pregnancy-relevant cell types to inform GWASs of pregnancy-associated conditions. Our results suggest that the expression of two transcription factors, GATA2 and HAND2, in endometrial stromal cells may regulate transcriptional programs that influence the timing of parturition in humans, which could lead to the identification of biomarkers of or therapeutic targets for PTB.
This study was approved by the Institutional Review Boards at the University of Chicago, Northwestern University, and Duke University Medical School. Informed consent for the use of data collected via questionnaires and clinics was obtained from participants following the recommendations of the ALSPAC (Avon Longitudinal Study of Parents and Children) Ethics and Law Committee at the time. Informed consent for the use of genetic data in the other six GWASs used in this study was also obtained from participants. Details are available in the Supplementary Materials.
Placentas were collected from three African American women (18 years old) who delivered at term (37 weeks) following spontaneous labor; all were vaginal deliveries of singleton pregnancies. Within 1 hour of delivery, 5 cm by 5 cm pieces of the membranes were sampled from a distant location of the rupture site. Pieces were placed in Dulbeccos modified Eagles medium (DMEM)-Hams F12 media containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin. Samples were kept at 4C and processed within 24 hours of tissue collection. This study was approved by the Institutional Review Boards at the University of Chicago, Northwestern University, and Duke University Medical School.
Third trimester placental tissue was enzymatically digested by a modification of previously described methods (55, 56). Decidua tissue was gently scraped from chorion, and tissue was enzymatically digested in a solution (1 Hanks balanced salt solution, 20 mM Hepes, 30 mM sodium bicarbonate, and 1% bovine serum albumin fraction V) containing collagenase type IV (200 U/ml; Sigma-Aldrich, C-5138), hyaluronidase type IS (1 mg/ml; Sigma-Aldrich, H-3506), and DNase type IV (0.45 KU/ml, Sigma-Aldrich, D-5025) at 37C, until a single-cell suspension was obtained (usually three rounds of 30 min digestion using fresh digestion media each round). Epithelial cells were removed by filtering through a 75 M nylon membrane and RPMI (Sigma-Aldrich) containing 10% FBS was added for enzyme inactivation. Dissociated cells were collected by centrifugation at 400g for 10 min and washed in RPMI/10% FBS. Erythrocytes were removed by cell pellet incubation with 1 red blood cell lysis buffer (Sigma-Aldrich) for 2.5 min at room temperature. The resulting cells were counted and resuspended in seeding media [1 phenol red-free high-glucose DMEM (Gibco)] supplemented with 10% FBS (Thermo Fisher Scientific), 2 mM l-glutamine (Life Technologies), 1 mM sodium pyruvate (Fisher Scientific), 1 insulin-transferrin-selenium (ITS; Thermo Fisher Scientific), 1% penicillin/streptomycin, and 1 antibiotic-antimycotic (Thermo Fisher Scientific). Dissociated cells were plated into a T75 flask and incubated at 37C and 5% CO2 for 15 to 30 min (enrichment by attachment). The supernatant was carefully removed, and loosely attached cells were discarded. Plates were allowed to grow in fresh media containing 10% charcoal-stripped FBS (CS-FBS), and 1 antibiotic-antimycotic until the plate was 80% confluent. The antibiotic-antimycotic was removed from the culture media after 2 weeks of culture. We obtained >99% vimentin-positive cells after three passages (fig. S4). Cells were expanded, harvested in 0.05% trypsin, and cryopreserved in 10% dimethylsulfoxide culture media for subsequent use. Each cell line was defined as coming from a different sample collection (different pregnancy).
Cells were plated and grown for 2 days in cell culture media (1 phenol red-free high-glucose DMEM, 10% CS-FBS, 2 mM l-glutamine, 1 mM sodium pyruvate, and 1 ITS). After 2 days, cells were treated either with control media (1 phenol red-free high-glucose DMEM, 2% CS-FBS, 2 mM l-glutamine) or decidualization media (1 phenol red-free high-glucose DMEM, 2% CS-FBS, 2 mM % l-glutamine, 0.5 mM 8-Br-cAMP, and 1 M MPA) for 48 hours. Cells were incubated at 37C and 5% CO2 and harvested for ATAC-seq, ChIP-seq, and RNA-seq, and prolactin (PRL) and insulin-like growth factor-binding protein 1 (IGFBP1) mRNA were assessed by quantitative real-time polymerase chain reaction (PCR) before each downstream assay was performed.
Total RNA was extracted from approximately 1 million cells using the AllPrep DNA/RNA Kit (QIAGEN) according to manufacturers instructions. RNA quality (RNA integrity number) and concentration was assessed by Bioanalyzer 2100 (Agilent technology). RNA-seq libraries were generated by a TruSeq stranded total RNA library prep kit (Illumina) and TruSeq RNA CD Index Plate.
For ChIP experiments, cells were cross-linked by adding to the media 37% formaldehyde to a final concentration of 1%, gently mixed, incubated for 10 min, and quenched for 5 min with 2.5 M glycine for a final of 0.125 M per plate. Cells were washed using cold 1 phosphate-buffered saline and scraped in 15 ml of cold Farnham lysis buffer and protease inhibitor (Roche, 11836145001), and cell pellets were flash frozen and kept at 80C. Thawed pellets were resuspended in radioimmunoprecipitation assay buffer on ice, aliquoted into 20 million cells per tube, and sonicated by Bioruptor (three 15-min rounds of 30 s ON, 30 s). ChIP was performed on 10 million cells using antibodies to H3K27ac, H3K4me3, and H3K4me1 histone marks (ab4729/lot no. GR274237, ab8580/lot no. GR273043, and ab8895/lot no. GR262515, respectively). M-280 sheep anti-rabbit immunoglobulin G Dynabeads (Invitrogen, 11203D) was used for chromatin immunoprecipitation. DNA was purified using the Qiagen MinElute PCR Purification Kit, quantified by Qubit, and prepared for sequencing using the Kapa Hyper Prep Kit. All libraries were pooled to 10 nM per sample before sequencing.
Approximately, 50,000 cells were harvested and used for ATAC-seq library preparation as described in the Fast-ATAC protocol (57). ATAC-seq libraries were uniquely indexed with Nextera PCR Primers and amplified with 9 to 12 cycles of PCR amplification. Amplified DNA fragments were purified with 0.8:1 ratio of Agencourt AMPure XP (Beckman Coulter) to sample. Libraries were quantified by Qubit, and size distribution was inspected by Bioanalyzer (Agilent Genomic DNA chip, Agilent Technologies). All libraries were pooled to 10 nM per sample before sequencing.
In situ Hi-C was performed as described previously (58). Briefly, 5 million decidualized cells were treated with formaldehyde 1% to cross-link interacting DNA loci. Cross-linked chromatin was treated with lysed and digested with MboI endonuclease (New England Biolabs). Subsequently, the restriction fragment overhangs were filled in and the DNA ends were marked with biotin-14-dATP (Life Technologies). The biotin-labeled DNA was sheared and pulled down using Dynabeads MyOne Stretavidin T1 beads (Life Technologies, 65602) and prepared for Illumina paired-end sequencing. The in situ Hi-C library was amplified directly off of the T1 beads with nine cycles of PCR using Illumina primers and protocol (Illumina, 2007). Promoter capture was performed as described previously (39). The Hi-C library was hybridized to 81,735 biotinylated 120-bp custom RNA oligomers (Custom Array) targeting promoter regions (four probes/RefSeq transcription start sites). After hybridization, postcapture PCR was performed on the DNA bound to the beads via biotinylated RNA.
Read counts per gene were calculated with Salmon (59) version 0.12.0 on transcripts from human Gencode release 19 (ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_19/gencode.v19.pc_transcripts.fa.gz and ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_19/gencode.v19.lncRNA_transcripts.fa.gz). Estimated counts were used in exploratory analysis (transformed with DESeq2s rlog function) and in DESeq2 (25) version 1.24.0 to identify differentially expressed genes (adjusted P 0.05 and absolute fold change of 1.2). After observing that replicates for each cell lines clustered together, we pooled reads for each cell line, combining three decidualization experiments in each sample. We then performed a paired analysis to obtain genes that were differentially expressed between untreated and decidualized samples. The six samples clustered by treatment and by cell line and analysis with svaseq (60) showed that the two surrogate variables identified correlated with cell line, and therefore, a paired analysis was enough to correct the data.
Similarly to RNA-seq, we pooled reads from replicates for each cell line. We called peaks for each of the six samples using MACS2 and converted peak coordinates into 100-bp contiguous bins. Bins covered by less than 60% of their extension were excluded. To identify reproducible peaks, we only kept bins that were present in at least two of the three cell lines in each condition, allowing for condition-specific peaks. See table S7 for an assessment of the contribution of each cell line to the universe of peaks obtained. We then merged all adjacent bins, expanding them back into longer peaks. We counted the number of reads in all peaks and in all samples and compared the read counts using DESeq2 (adjusted P < 0.05 and absolute fold change >1.2).
The P values in Fig. 2B were calculated with a chi-square test of the number of peaks with increased or decreased numbers of reads observed and an expected probability based on the number of peaks in each category for each dataset. Bonferroni correction was performed to correct for multiple testing.
ChIP-seq reads were downloaded from National Center for Biotechnology Information Gene Expression Omnibus and processed locally. HOMER 4.9 (63) was used to call peaks for the following samples: PGR (GSE94038); NR2F2 (GSE52008); FOSL2 (GSE94038), FOXO1 (GSE94037); and NR2F2 input (GSE52008); and FOXO1, PGR, and FOSL2 input (GSE94038).
Reproducible peaks were converted into 100 bp bins and those with >60% of their extension covered by a peak was retained. Common bins were counted, and the number of counts was plotted with UpSetR 1.4.0.
We used HOMER 4.9 to identify DNA binding motifs enriched in peaks with parameters -len 8,10,12 -size 200 -mask.
Enrichment was calculated as the observed number of overlapping peaks divided by the expected number of overlapping peaks using bedtools intersectBed with a 1 bp minimum. The expected number of overlapping peaks was obtained by averaging 100 random samples of peaks with bedtools shuffle excluding gaps annotated by the University of California, Santa Cruz Genome Browser (64). While shuffling peaks does not account for mapping and other biases that make peak locations nonuniform and may result in overestimation of enrichment, our results are limited to comparisons between enrichments, which should cancel any biases.
We used HiCUP v0.5.9 (65) to align and filter Hi-C reads. HiCUP used bowtie2 version 2.2.3 to align reads. Unique reads were used as input by CHiCAGO (66) version 1.2.0, and significant interactions were called with default parameters. We only kept interactions identified by CHiCAGO that were in cis and with an end located at least 10 kb from a capture probe.
To pair peaks using pcHi-C, significant interactions identified by CHiCAGO that overlapped an ATAC-seq or ChIP-seq peak and were less than 300 kb away from a promoter were used. We chose 300 kb because the mean distance between interacting promoters and other regions was 280 kb (median, 200 kb). To pair peaks to the nearest gene, BEDTools closest -t first -d was used to find the gene closest to a peak, up to 300 kb away. To pair peaks to a random gene, all genes up to 300 kb from a peak were selected and one gene was randomly assigned to each peak. For each of these sets of pairs, we calculated the fraction of peak/gene pairs that had the same direction of change according to differential read count analysis with DESeq2, of the total number of peak/gene pairs. Only genes expressed at >1 transcript per million across all samples were used in the nearest and random gene assignments.
P values were calculated with a chi-square test comparing the number of cases in the matched and unmatched categories observed in the random set (average from 200 iterations) and in the two peak/gene pairing methods: nearest gene and pcHi-C interactions.
The GWAS results used in this study was an extension of our previously published results (5). Like our previous study, we used summary results from 23andMe, which were obtained from GWAS of gestational duration in 42,121 mothers of European ancestry. In addition, we performed GWA analyses in 14,263 European mothers from six academic datasets. To increase the power of GWA discovery, we performed meta-analysis between the results from 23andMe and the results from the six datasets. See the Supplementary Materials for a full description of the GWAS.
We assessed how much of the heritability of gestational duration is contained within ATAC-seq, H3K4me1, H3K4me3, H3K27ac, and pcHi-C peaks using S-LDSC (41). S-LDSC is a generalization of LD score regression, a method for estimating the heritability of a trait using SNP-level GWAS summary statistics and SNP-level estimates of the amount of genetic variation tagged at each variant, known as LD scores. Under the LD score regression model, the expected value of the GWAS summary statistic for a variant (specifically, the expected value of the 2 statistic) is a linear function of the LD score at that site, and h2, the per-SNP heritability, and a an intercept parameter. Under the S-LDSC model, rather than estimating a single per-SNP heritability parameter, a parameter is estimated for each of several functional annotations. In a standard S-LDSC analysis, user-provided annotations are combined with a baseline set of genomic annotations from publicly available datasets. For this analysis, LD scores were calculated using the peaks identified as reproducible across either treated or untreated samples as annotations and the genotype data from the European individuals from phase 3 of the 1000 Genomes project (obtained from the Price Lab website: https://alkesgroup.broadinstitute.org/LDSCORE/) as a reference LD panel, using only the HapMap3 SNP list (also from the Price lab website). S-LDSC was performed on the gestational duration GWAS using the endometrial-tissue derived LD scores and the baseline LD scores contained in version 2.2 of the LD score regression baseline LD model. We include all annotations from the baseline LD model except those flanking annotations. This resulted in a total of 64 baseline annotations used in our S-LDSC analysis.
Fine mapping proceeded in three stages. In the first stage, we partitioned the genome into 1703 regions approximately independent regions using breakpoints derived by Berisa et al. (40). Next, we constructed an SNP-level prior probability of being causal variant, informed by the functional genomic data that we collected. We used a Bayesian hierarchical model [TORUS (42)]. TORUS takes as input GWAS summary statistics and genomic annotations and estimates the extent to which SNPs with functional genomic annotations are likely to be causal for a trait of interest. Specifically, under TORUS, each SNP has a small prior probability of being a causal variant, which is a logistic function of the annotations of the SNP. Then, TORUS estimates the parameters of this logistic function using genome-wide summary statistics. Once these parameters are estimated, each SNP will have a prior causal probability based on its unique functional annotations. We ran TORUS with the gestational age GWAS summary statistics and the reproducible H3K27ac and H3K4me1 peaks from the treated samples along with the pcHi-C contact regions to obtain an SNP-level prior.
Last, fine mapping was performed using a summary statistics-based version of the sum of single effects model (43) using 1000 Genome as reference panel. SuSiE (as implemented in the R package susieR) was run on the 10 regions believed to have one or more causal variants with an FDR of 0.1 as estimated by TORUS. For each region, SuSiE was run with a uniform prior (default setting of SuSiE) and with an informed prior learned by TORUS. The parameter L of SuSiE (maximum number of causal variants) is set at 1 when running SuSiE (67, 68).
H3K27ac, H3K4me1, and H4K4me3 histone modification peak coordinates were downloaded from the Epigenome Roadmap data website, and bedtools intersect was used to find peaks that overlapped SNPs coordinates.
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Transcriptome and regulatory maps of decidua-derived stromal cells inform gene discovery in preterm birth - Science Advances
Loretta J. Nastoupil, MD, associate professor, director, Lymphoma, Outcomes Database Section chief, New Drug Development Department of Lymphoma/Myeloma ,Division of Cancer Medicine at The University of Texas MD Anderson Cancer Center, discussed the use of chimeric antigen receptor (CAR) T-cell therapy in patients with diffuse large B-cell lymphoma.
The discussion occurred among a group of oncologist during a Targeted Oncology Case Base Peer Perspective event.
Targeted Oncology: What clinical trial data support the use of CAR T-cell therapy for this patient?
NASTOUPIL: The ZUMA-1 study [NCT02348216] enrolled patients with refractory large cell lymphoma and included about 30% of patients with double-hit features. [It] also included [patients with] primary mediastinal transformed follicular lymphoma. There was a relatively small sample size of 101 patients. This was a single-arm, phase 2 [design]. However, they had a high success rate in terms of enrollment and treatment of patients where 91% of the patients who were enrolled received cell therapy.
ZUMA-1 [examined axicabtagene ciloleucel (axi-cel; Yescarta)], an autologous CD19-directed CAR T-cell therapy. It has a CD28 costimulatory molecule. The lymphocyte depleting regimen is high in this study: 500 mg/m2 of cyclophosphamide and 30 mg/m2 of fludarabine for 3 consecutive days.
The median progress-free survival [PFS] in this study was about 6 months [5.9 months; 95% CI, 3.3-15.0]. The best objective response rate [ORR] was 83% and best complete response [CR] rate was 58%.
There was a stark drop-off and then a flattening of the [Kaplan-Meier PFS] curve. [Experience has shown that] theres about 40%, to maybe as high as 50%, of patients who can be cured with this, but its hard to identify who they are. The patients who dont respond generally do poorly within the first 3 to 6 months.
The JULIET study [NCT02445248] was a bit different. Its a larger multicenter study [that examined tisagenlecleucel (Kymriah)]. It was a much longer time from enrollment to infusion of CAR T cells; as a result, bridging therapy was allowed. They also included relapsed, not just refractory, patients, and they excluded patients with primary mediastinal disease.2
There [were] lower response rates [in] this study population of 52%. The CR rate, though, is notable at 40%. The patients who had CR had durability of that CR. About 40% of the patients had a meaningful outcome with this CAR-T cell therapy, which was a 4-1BB construct. This is an autologous [product] with a CD19 target.
The efficacy is hard to compare across the studies because they were different in terms of patient eligibility and trial conduct. However, my general sense is that the vast majority of patients have about a 40%, to maybe as high as 50%, meaningful CR that is durable, and the overall survival [OS] is quite notable. With ZUMA-1, the median OS settles in at 27.1 months.
Are there any CAR T-cell therapies that may be added to the list of available products for these patients?
Liso-cel [lisocabtagene maraleucel] is the third [CAR T-cell product that is] anticipated for FDA approval. Thats also a 41BB construct similar to tisagenlecleucel. Its different in that theres a fixed CD4 to CD8 ratio and a longer time for manufacturing in comparison to axi-cel. But again, there is meaningful efficacy.3
How does the toxicity compare between these agents?
The toxicity looks to be different, but different grading systems were applied in the studies. When you apply the same rating system retrospectively, patients have fewer grade 3 or higher cytokine release syndrome in the JULIET study than what was initially reported.4
Axi-cel tends to have the highest rate of grade 3 or higher neurotoxicity and liso-cel tends to have the most favorable toxicity profile. Though because its the third [agent to become available], weve [become] much better at identifying and mitigating some of these acute toxicities.
There are differences, in my opinion, across the 3 constructs in terms of safety, despite the efficacy being quite similar.
Why are these data important to review?
We know CAR-T cell therapy has transformed outcomes for about 40% of patients; however, its logistically challenging....Weve struggled with identifying what makes a good CAR-T cell candidate outside of having chemotherapy-refractory disease and being in a third-line setting.
What other therapy options could be used in this patient if she is not a candidate for CAR T-cell therapy?
Polatuzumab vedotin [Polivy] in combination with bendamustine and rituximab [BR] was approved based on a randomized phase 2 study [NCT02257567].5 Of note, this was a study that included both follicular and large cell lymphoma. However, the follicular [cohort showed] a negative result. There was no significant impact with the addition of polatuzumab vedotin to BR, which is not necessarily surprising given that bendamustine is a very active agent for follicular lymphoma.
It is not an active agent in large cell lymphoma. One of the reasons why it was included in this study design is because the potential for challenge with polatuzumab was identifying an agent in third-line large cell lymphoma setting where you wouldnt have additive.
Please describe the trial that led to the approval of polatuzumab vedotin.
For baseline characteristics, and this is specifically looking at the patients with large cell lymphoma, the median age was 67 years [range, 33-86] in the polatuzumab/BR arm versus 71 years [range, 30-84] in the BR-only arm. In terms of median number of prior lines of therapy, it was 2 for both arms. In terms of prior stem cell transplant, about 25% had undergone transplant in the polatuzumab-BR arm versus 15% in the BR-arm.
ORR by independent review with the polatuzumab-BR was much higher versus the BR-only arm [45% versus 17.5%].6
Importantly, the median PFS was significantly different. If patients received polatuzumab, the median PFS was 9.5 months versus 3.7 months in the control arm [0.36; 95% CI, 0.21-0.63; P < .001].
The important message is that there werent any subgroups that benefited from BR alone, and this included criteria such as bulky disease, number of prior lines of therapy, and duration of response with the prior line of therapy.
The OS was significantly better if you had polatuzumab plus BR, with a median of 12.4 months versus 4.7 months [HR, 0.42; 95% CI, 0.24-0.75; P = .002]. Similarly, there were no subgroups that tended to benefit from receiving BR alone.
What was the toxicity profile of this regimen for patients?
[It is] important to note that peripheral neuropathy, which is an adverse event associated with this antibody-drug conjugant, was mostly reported as grade 1 events. [The effect was] slightly additive if you had the BR and polatuzumab versus no polatuzumab.
In terms of neutropenia, grade 3/4 events with the combination occurred in 46.2% of patients, and thats higher when compared with BR alone [33.3%]. However, febrile neutropenia events were no different between arms [10.3% vs 12.8%].
References:
1. Neelapu SS, Locke FL, Bartlett NL, et al. Axicabtagene ciloleucel CAR T-cell therapy in refractory large B-cell lymphoma. N Engl J Med. 2017;377(26):2531-2544. doi:10.1056/NEJMoa1707447
2. Schuster SJ, Bishop MR, Tam CS, et al; JULIET Investigators. Tisagenlecleucel in adult relapsed or refractory diffuse large B-cell lymphoma. N Engl J Med. 2019;380(1):45-56. doi:10.1056/NEJMoa1804980
3. Abramson JS, Palomba ML, Gordon LI, et al. Lisocabtagene maraleucel for patients with relapsed or refractory large B-cell lymphomas (TRANSCEND NHL 001): a multicentre seamless design study. Lancet. 2020;396(10254):839-852. doi:10.1016/S0140-6736(20)31366-0
4. Abramson JS. Anti-CD19 CAR T-cell therapy for B-cell non-Hodgkin lymphoma. Transfus Med Rev. 2020;34(1):29-33. doi:10.1016/j.tmrv.2019.08.003
5. FDA approves polatuzumab vedotin-piiq for diffuse large B-cell lymphoma. FDA. June 10, 2019. Accessed November 13, 2020. https://bit.ly/2IBZGrv
6. Sehn LH, Herrera AF, Flowers CR, et al. Polatuzumab vedotin in relapsed or refractory diffuse large B-cell lymphoma. J Clin Oncol. 2020;38(2):155-165. doi:10.1200/JCO.19.00172
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Therapy Options Compared for the Treatment of Recurrent DLBCL - Targeted Oncology
INTRODUCTION
The adaptive immune system arguably represents one of the major evolutionary novelties that distinguish vertebrates from their nonvertebrate ancestors. About half a billion years ago, specialized cell types, such as lymphocytes, and new organs, such as the thymus, emerged, contributing to the radical redesign of animal immunity (13). These morphological and cytological innovations likely occurred in the ancestor common to all vertebrates, since they are present in both of the two extant groups of vertebrates, the jawless and jawed vertebrates (3). Additional novelties, such as the chemokine and chemokine receptor systems, enabled new types of cellular interactions, for instance, between hematopoietic progenitor cells and the emerging thymopoietic tissue (4). The thymic microenvironment provides distinct molecular cues such as Notch ligands, chemokines, and cytokines that interact in a synergistic, context-dependent, and hierarchical manner and, in this way, determine the outcome of hematopoietic precursor cell differentiation (5). The key importance of the thymic microenvironment for T cell development was first revealed through studies of rodents homozygous for mutations at the nude locus (68), which disrupt thymus development, causing animals to be immune deficient. The nude locus encodes a transcription factor of the forkhead class (9), now designated as Foxn1. Subsequent studies in mice indicated that the Foxn1 gene is dispensable for the formation of the thymic anlage during embryonic development (8) but is required for the subsequent steps of differentiation of primitive precursor cells into the typical cortical and medullary subsets of the thymic epithelium (10). Foxn1-expressing thymic epithelial precursors (11) are bipotent (12, 13), with each cell able to give rise to a self-organizing thymopoietic unit containing cortical and medullary compartments capable of supporting T cell development (12). Thus, in the absence of Foxn1, the master regulator of the thymic epithelium in mammals, thymus differentiation is aborted, and T cell development fails (9). Attempts to identify the key functional elements of the thymic epithelium through transgenic expression of candidate genes has highlighted the roles of the chemokines Cxcl12 and Ccl25, the cytokine/stem cell factor Scf, and the Notch ligand Dll4 (5), which direct the early steps of T cell development in the thymic microenvironment. However, the individual components of the genetic network downstream of Foxn1 that regulates the emergence of distinct subsets of thymic epithelial cells (TECs) are unknown.
So far, it has not been possible to reconstruct the nature and evolutionary sequence of the steps that gave rise to a functional thymus, as no extant species representing intermediate phylogenetic stages along the transition from innate to adaptive immunity are available for analysis. To begin to address this problem, we have developed an in vivo reconstruction strategy that rests on the exchange of the mammalian version of the Foxn1 transcription factor with its evolutionarily distant relatives of nonvertebrate and vertebrate origin. Since the decisions controlling alternative differentiation pathways in the hematopoietic system are strongly influenced by extrinsic cues (5, 1417), we hypothesized that it should be possible to directly examine and compare the thymopoietic properties of distinct types of epithelial microenvironments in the thymus as a result of the activities of different Foxn1/4 family members.
Foxn1 and its paralog Foxn4 comprise a distinct two-member family of vertebrate wing-helix transcription factors that recognize a unique (G+C)-rich DNA target sequence, distinguished by the core tetranucleotide sequence, 5-ACGC (18, 19). This sequence is also recognized by the DNA binding domain (fig. S1A) encoded by the Foxn4 gene of amphioxus (19), indicating that the evolutionary conservation of the protein sequence of the DNA binding domains encoded by this gene family (4) is mirrored in identical target recognition sequences. In addition to the centrally located DNA binding domain, Foxn1/4 transcription factors exhibit N-terminal domains of variable lengths and acidic transcriptional activation domains (20) in their C-terminal region (fig. S1A); of note, the activation domains are functionally interchangeable, as indicated by the fact that the C terminus of the amphioxus (lancelet) Foxn4 protein can replace that of the mouse Foxn1 protein in in vitro assays of transcriptional activation (21). These observations suggest that the N-terminal regions of Foxn1/4 proteins have been important targets for evolutionary modifications, possibly related to changes in function.
To determine the thymopoietic properties of different members of the Foxn1/4 transcription factor family in the context of the mouse hematopoietic system, we have developed a generic transgenic replacement strategy. It begins with Foxn1-deficient mice, in which the thymic epithelium is functionally inactive (10); it is important to note that, because immature progenitor cells persist in the organ anlage, a functional thymus can be formed upon reactivation of the Foxn1 function (12). We then introduce a transgenic construct that contains all regulatory sequences of the mouse Foxn1 gene (fig. S1B) that are necessary to direct tissue-specific and orthotopic expression of any complementary DNA (cDNA) to the endogenous Foxn1 expression domains into this Foxn1-deficient background. A previous study using this system demonstrated that the expression of the cognate mouse Foxn1 cDNA rescued the pleiotropic nude phenotype in the thymus and the skin (22), thus functionally validating the replacement strategy in vivo. In the first application of this method, we showed that the mouse Foxn4 transcription factor gene [which is paralogous to mouse Foxn1 (4), although not expressed in the mouse thymic epithelium (22)] is nonetheless capable of supporting a degree of lymphopoiesis in the reconstructed thymi (22). These results encouraged us to extend our studies to Foxn1/4 family members (fig. S1C) identifiable in extant representatives of evolutionarily more ancient chordates, using the phenotypes of mouse Foxn1 and mouse Foxn4 replacements as references.
For centuries, biologists have debated the evolutionary origin of vertebrates (23); the current scenario of chordate taxa suggests that lancelets are the sister group to tunicates and vertebrates (24, 25). This phylogenetic relationship is mirrored in our analysis of the chordate Foxn1/4 gene family, which suggests that an ancestral metazoan Foxn4 gene gave rise to the Foxn1 and Foxn4 genes of vertebrates (Fig. 1 and fig. S2) (4). Although tunicates are considered to be phylogenetically closest to vertebrates (24, 25), we chose the Foxn4 gene of amphioxus for our functional analyses, because tunicate development is substantially secondarily modified (26). Hence, to understand the role of Foxn4 in the emergence of specific aspects of the vertebrate body plan, lancelets appeared to be better proxies than tunicates. Moreover, we had previously shown that the amphioxus Foxn4 gene is expressed in the pharyngeal endoderm, the future site of the thymic epithelium in vertebrates (4). For the present experiments, we focused on one species of lancelets (Branchiostoma lanceolatum). To study vertebrate-specific aspects of the Foxn1/4 gene family, we turned to an extant representative of the most ancient group of jawed vertebrates, cartilaginous fishes. To this end, we identified and isolated the Foxn1 and Foxn4 genes of elephant shark (Callorhinchus milii) for our replacement studies.
Vertebrate Foxn1 and Foxn4 clades recapitulate the known phylogenetic relationships of vertebrates (representatives of mammals, monotremes/marsupials, birds, reptiles, amphibians, and bony and cartilaginous fishes are depicted). The Foxn1 proteins in vertebrates form a monophyletic clade. The Foxn4 proteins are paraphyletic in vertebrates and in tunicates. The Foxn4 proteins in lancelets form the base of the tree. The support from 1000 bootstrap replicates is shown as color-coded branches. The vertebrate Foxn1 and Foxn4 clades are boxed in different colors. The scale is in units of average amino acid substitutions per site.
To reconstruct the functional changes that occurred along the evolutionary trajectory of the thymic microenvironment in vertebrates, we examined the developmental fate of mouse hematopoietic progenitors in the different types of thymic microenvironments. Since the Foxn1-deficient thymic epithelium fails to differentiate and does not support lymphoid development (fig. S3) (69), any lymphopoietic activity in the reconstituted thymic microenvironment must be driven by the expression of the respective Foxn1/4 family member under study. The transgenic thymi were examined both for their lymphopoietic capacity and the characteristics of the epithelial microenvironment. Whereas the hematopoietic compartment was analyzed by cell surface markers and in situ analysis of tissue sections, TECs were additionally characterized by RNA sequencing (RNA-seq). Guided by our previous work (22), we focused our attention on three major phenotypic aspects of the thymi that were reconstituted by the Foxn1/4 gene family members of amphioxus and shark. With regards to the composition of the thymic microenvironment, we specifically addressed the question of whether they are capable of supporting the formation of a distinct medullary area, a key compartment associated with the selection of a self-tolerant T cell repertoire (27). With respect to the lymphopoietic properties of the reconstructed thymi, we paid particular attention to their capacity to support the differentiation of thymocytes throughout the known developmental trajectory (17); moreover, we scored the presence and localization of immature and mature B cells, since our previous studies indicated a propensity of the mouse Foxn4 gene to support B cell poiesis when expressed in the thymic epithelium (22), a capacity that the wild-type mouse thymus lacks.
We first examined the thymopoietic capacity of lancelet Foxn4 (Bl_Foxn4), the sole family member of the Foxn1/4 gene family in the genome of the cephalochordate B. lanceolatum. Lancelets lack an adaptive immune system, although cytological evidence for the presence of lymphocyte-like cells has been reported in some species (28, 29). Bl_Foxn4 exhibits some thymopoietic activity. After replacement of mouse Foxn1 (Mus musculus, hereafter Mm_Foxn1) with Bl_Foxn4, the transgenic thymic microenvironment predominantly harbors CD4+CD8+ double-positive (DP) immature thymocytes (Fig. 2A), although their number amounts to only about 1% of that in wild-type thymi (Fig. 2B). Two other features distinguish the hematopoietic compartment of Bl_Foxn4 thymi from the corresponding wild-type situation. First, very few, if any, single-positive T cells are detectable (Fig. 2A), and second, the CD4CD8 double-negative compartment is much larger than in wild-type mice (Fig. 2A). Notably, the absolute number of CD45+CD4CD8CD19+B220+IgM+CD93 mature B cells present in Bl_Foxn4 thymi (Fig. 2C) is only 10-fold lower than that in wild-type thymi (Fig. 2D), indicating that, relative to a mouse wild-type thymus, the transgenic microenvironment tends to be more favorable for mature B cells than for immature T cells.
(A) Flow cytometric analysis of CD45+ thymocytes, stained for T cell markers; wt (n = 6) and Bl_Foxn4 (n = 7). (B) Absolute numbers of total thymocytes and CD4+CD8+ DP T cells in wt (n = 7) and Bl_Foxn4 transgenic thymi (n = 6); ***P < 0.001; two-tailed t test for both groups. (C) Flow cytometric analysis of CD45+ thymocytes and B cell markers; wt (n = 6) and Bl_Foxn4 (n = 7). (D) Absolute numbers of immature CD45+CD4CD8CD19+IgMCD93+ B cells; P = 0.1058, two-tailed t test; wt (n = 6) and Bl_Foxn4 (n = 7). (E) Ly51 expression and UEA1 binding on EpCAM+CD45 TECs; wt (n = 5) and Bl_Foxn4 (n = 5). (F) Heatmap of differential gene expression patterns of TECs. Genes whose expression is associated with particular TEC subsets are indicated (green, cTEC-like; red, mTEC-like; blue, mature cTEC); analysis based on 18,808 protein-coding genes. Scale refers to the percentage of maximum and minimum values of transcript counts of individual genes. (G) Total numbers of CD45EpCAM+ TECs; wt (n = 5) and Bl_Foxn4 (n = 8). (H and I) T and B cell poietic indices calculated from ratios of means (SDs correspond to propagated errors); ***P < 0.001 two tailed t test.
The unique lymphoid signature in the Bl_Foxn4-reconstituted thymi is the result of a microenvironment characterized by epithelial cysts (fig. S4, A and B), dominated by cells reminiscent of cortical TECs (cTECs), as determined by cell surface phenotype (EpCAM+Ly51+UEA1) (Fig. 2E) and the keratin signature (K8+K5) in tissue sections (fig. S4A); we note a conspicuous lack of medullary TECs (mTECs) both in flow cytometric (EpCAM+Ly51UEA1+) (Fig. 2E) and immunohistological (K8K5+) (fig. S4A) analyses. Accordingly, the epithelium has a global transcriptional profile heavily skewed toward a cTEC signature (high levels of Bmp4, Psmb11, Cxcl12, and Dll4 genes), with low levels of genes typically associated with mTECs (Trpm5 and Aire) (30); of note, the near-complete absence of mature TECs is also reflected in low levels of Mhc2 gene expression (Fig. 2F). In the wild-type thymus, the Aire gene is expressed in the CD80+MHCIIhi subset of mature mTEC and involved in the regulation of promiscuous gene expression that is required for proper negative selection of autoreactive T cells (31).
Overall, this constellation gives rise to a low thymopoietic index (calculated as the ratio of hematopoietic cells to TECs) for immature CD4+CD8+ T cells; the capacity of Bl_Foxn4 thymi to generate these immature T cells is two orders of magnitude lower than that of wild-type thymi, compatible with the immature status of the transgenic TECs. Because immature CD45+CD4CD8CD19+B220+IgMCD93+ (henceforth IgMCD93+) B cells are barely detectable in the transgenic thymi (Fig. 2, G to I), the reduction of B poietic capacity can be less confidently determined but appears to be at least 10-fold. Collectively, mice expressing Bl_Foxn4 instead of Mm_Foxn1 in TECs fail to support proper T cell development in the thymus, lack appreciable B cellgenerative capacity, and are most likely incapable of executing the necessary positive and negative selection steps that normally give rise to a self-tolerant repertoire of mature T cells. As a consequence, transgenic mice rapidly (fig. S4C) succumb to an inflammatory syndrome, chiefly affecting the intestine (fig. S4D), occasionally accompanied by vitiligo (fig. S4E). Nonetheless, our data indicate that Bl_Foxn4 is preadapted to support the early stages of T lymphopoiesis when expressed in the context of a vertebrate immune system, attesting to the strong evolutionary conservation of the Notch signaling pathway in regulating the differentiation of hematopoietic precursors [reviewed in (14)].
To assess the functional changes associated with the emergence of a vertebrate form of the Foxn4 gene, we next examined the lymphopoietic capacity of the Foxn4 gene of an extant representative of an evolutionarily ancient group of jawed vertebrates (Fig. 1 and figs. S1 and S2). When the thymic epithelium expresses the Foxn4 gene of the cartilaginous fish C. milii (Cm_Foxn4) instead of Mm_Foxn1, the lymphoid compartment (Fig. 3, A to E) features a large fraction of IgMCD93+ immature B cells, which amounts to about 10% of all hematopoietic cells. This represents an increase of three orders of magnitude when compared to the fraction of immature B cells among the thymocytes of wild-type mice, which averages about 0.01% of all thymocytes. In absolute terms, the Cm_Foxn4 thymi harbor only about 1% of the hematopoietic cell numbers in wild-type mice. Despite the comparatively low number of T cells in the transgenic thymi, their differentiation appears to proceed normally, as reflected by the presence of DP and single-positive thymocytes and the absence of systemic inflammation. These results suggest that the Cm_Foxn4 thymic microenvironment is conducive to both T and B cell differentiation (Fig. 3, F to H); this type of unusual lymphoid bipotency was previously observed in Mm_Foxn4 transgenic thymi (22).
(A to C) Total numbers of CD45+ hematopoietic cells {wt (n = 20), Cm_Foxn4 (n = 7), Cm_Foxn1 (n = 11), and Cm_Foxn1/Cm_Foxn4 double transgenics [Cm_dtg (n = 5)]}, DP T cells [wt (n = 20), Cm_Foxn4 (n = 7), Cm_Foxn1 (n = 11), and Cm_dtg (n = 5)], and CD93+ immature B cells [wt (n = 13), Cm_Foxn4 (n = 7), Cm_Foxn1 (n = 7), and Cm_dtg (n = 5)] in thymi of mice with the indicated genotypes. (D and E) Representative flow cytometric profiles for mice summarized in (A to C). (D) wt (n = 16), Cm_Foxn4 (n = 7), Cm_Foxn1 (n = 9), Cm_dtg (n = 5). (E) wt (n = 13), Cm_Foxn4 (n = 7), Cm_Foxn1 (n = 7), and Cm_dtg (n = 5). (F) Total numbers of CD45EpCAM+ TECs; wt (n = 17), Cm_Foxn4 (n = 6), Cm_Foxn1 (n = 11), and Cm_dtg (n = 5). (G) T cell poietic indices; wt (n = 20), Cm_Foxn4 (n = 6), Cm_Foxn1 (n = 11), and Cm_dtg (n = 5). (H) B cell poietic indices; wt (n = 13), Cm_Foxn4 (n = 6), Cm_Foxn1 (n = 7), and Cm_dtg (n = 5). In (A) to (C) and (F) to (H), each data point represents one mouse. ***P < 0.001; one-way ANOVA with Tukeys multiple comparison test in (A) to (C) and (F) to (H).
Compared to the situation in Bl_Foxn4 transgenic mice, the epithelial microenvironment of Cm_Foxn4 thymi exhibits the cell surface phenotype (Fig. 4A) and the keratin (Fig. 4B) and gene (Fig. 4C) expression patterns of a more mature cTEC compartment; this is particularly evident from the much higher expression levels of Prss16 and Ccl25 genes that are elevated to wild-type levels (Fig. 4C).
(A) Representative flow cytometric analyses of Ly51 expression and UEA1 binding on TECs for mice; wt (n = 22), Cm_Foxn4 (n = 6), Cm_Foxn1 (n = 11), and Cm_dtg (n = 5). (B) Epithelial microenvironment of reconstructed thymi resolved by keratin 5 (K5) (in green) and K8 (in red) staining; 4-week-old mice. m, medulla; c, cortex. Note the small size of the Cm_Foxn4-reconstructed thymus. (C) Differential gene expression patterns in TEC transcriptomes relative to wild-type mice; Bl_Foxn4 (n = 4), Cm_Foxn4 (n = 4), and wt (n = 3). (D) Localization of Aire+ cells relative to cortical (K8) and medullary (K5) areas. (E) Differential gene expression patterns in TEC transcriptomes of transgenic relative to wild-type mice; wt (n = 3), Mm_Foxn4 (n = 6), and Cm_Foxn4 (n = 4). (F) Localization of B220+ B cells (in green) adjacent to ER-TR7+ mesenchyme (in red). PVS, perivascular space. (G) Differential gene expression patterns in TEC transcriptomes of transgenic relative to wild-type mice; wt (n = 3), Cm_Foxn4 (n = 4), Cm_Foxn1 (n = 3), and Cm_dtg (n = 5). In (C), (E), and (G), each data point represents the average value of at least three mice; all values are significantly different from the wild-type genotype (adjusted P values of <0.05), except those data points falling on 0 Arrows indicate the directions of changes in expression levels between transgenic mice.
Although no histologically distinct medullary region is detectable (Fig. 4B), the expression levels of genes indicative of different subsets of mTECs (Fig. 4C) are higher than in the Bl_Foxn4-driven epithelium. Although the morphology of the transgenic thymus lacks the characteristic zonation of cTECs and mTECs that is typical of the wild-type epithelium, low levels of Aire gene expression are detectable (Fig. 4C). Immunohistological analysis indicates the presence of only few Aire+ TECs, which are observed in the edges of epithelial cellfree regions in the reconstituted thymus, in contrast to the obvious Aire+ mTEC clusters in the wild-type thymus (Fig. 4D).
In line with the remarkable sequence conservation of vertebrate Foxn4 proteins (figs. S1, S2, and S5), the structures of the thymic microenvironments driven by Cm_Foxn4 (Fig. 4B) and Mm_Foxn4 (32) genes are essentially identical, despite 500 million years (Ma) of independent evolution. However, compared to the situation in Cm_Foxn4 transgenic mice, Mm_Foxn4-driven epithelia express lower levels of Prss16 and Aire, suggesting that with evolutionary progression, Foxn4 genes have gradually lost the capacity to support maturation of both cTECs and mTECs (Fig. 4E).
Previously, we have shown that the B cells generated in the Mm_Foxn4 thymus are preferentially located in close proximity to the vasculature, i.e., in the mesenchymal perivascular space (22). This finding highlighted the presence of anatomically distinct niches supporting the development of the two principal lymphocyte lineages in a primordial thymus; T cells differentiate in an epithelial environment, whereas B cells differentiate in a mesenchymal niche, similar to the situation in the sinusoidal environment of the bone marrow (33). In notable similarity, B cells in the Cm_Foxn4-expressing thymi are again found in the perivascular space (Fig. 4F), indicating that Foxn4 proteins favor the formation of anatomically separated domains specialized in either T or B cell differentiation.
Next, we tested the thymopoietic capacity of a Foxn1 gene that is suggested by phylogenetic analysis to have emerged from the ancestral vertebrate Foxn1/4-like gene, following a gene duplication event at the base of vertebrate evolution (Fig. 1 and figs. S1 and S2). With respect to mammalian Foxn1 genes, the elephant shark Cm_Foxn1 gene is the evolutionarily most distant form of a Foxn1-like gene of jawed vertebrates examined here (Fig. 1 and figs. S1, S2, and S6). Despite more than 400 Ma of independent evolution, the lymphopoietic capacity of shark Cm_Foxn1 is remarkably similar to that of mouse Mm_Foxn1. The total numbers of CD4+CD8+ immature thymocytes in Cm_Foxn1-expressing thymi approach those observed in mouse wild-type thymi; moreover, differentiation into CD4+ and CD8+ single-positive T cells occurs; as a result, the relative proportions of immature and mature thymocytes are identical to wild-type thymi (Fig. 3, B and D). With respect to intrathymic B cell development, we find that the absolute numbers of immature B cells are about 10-fold lower in the Cm_Foxn1 transgenic thymi than in the corresponding Cm_Foxn4 reconstitution (Fig. 3, C and E); however, they are slightly increased when compared to the wild-type mouse thymus.
As expected from the near-normal hematopoietic compartment in Cm_Foxn1 thymi, their microenvironment also resembles a wild-type mouse thymus. This is evident from the cytometric profiles of Ly51 and UEA1 markers (Fig. 4A) and the anatomical segregation of K5+K8 (medullary) and K5K8+ (cortical) areas in tissue sections (Fig. 4B); except for a somewhat smaller overall size, the histology of the Cm_Foxn1 thymus is essentially identical to the wild-type form. As expected, Aire+ TECs are present in the distinct medullary areas, sparing the thymic cortex (Fig. 4E). The expression patterns of signature genes in Cm_Foxn1 TECs indicate the remarkable similarity to wild-type TECs in the mouse thymus (Fig. 4G). However, subtle differences in the gene expression profiles exist; the increased levels of Prss16 suggest the presence of a bias toward mature cTECs at the expense of certain mTEC populations, for instance, those expressing Trpm5 (Fig. 4G). Nonetheless, our observations suggest that the T cellbiased lymphopoietic properties of Foxn1-like genes, as exemplified by the mammalian thymus, had already emerged in the ancestor of jawed vertebrates and were maintained throughout subsequent evolution.
With respect to the reconstructions described above, it is important to note that they represent an artificial disentanglement of Cm_Foxn1 and Cm_Foxn4 functions, since in the thymus of cartilaginous fish, Foxn1 and Foxn4 paralogs are coexpressed (fig. S7) (22). However, the expression patterns of the two genes are not completely identical; whereas they are both expressed in the shark retina, the expression of Foxn4 in distinct cell clusters in the spinal cord is unique (fig. S7). To mimic the physiological coexpression of both genes in TECs of cartilaginous fish, we generated Cm_Foxn1/Cm_Foxn4 double-transgenic mice (hereafter Cm_dtg). When compared to the number of thymocytes in Cm_Foxn4 and Cm_Foxn1 single-transgenic mice, this constellation of coexpression results in an intermediate number of T cells, although the cellularity is closer to the situation in Cm_Foxn1 thymi (Fig. 3A). Unexpectedly, coexpression of Cm_Foxn1 and Cm_Foxn4 leads to markedly increased numbers of immature B cells, almost two orders of magnitude more than in the Cm_Foxn1 single transgenic (Fig. 3, C and E). The higher capacity for B cell development in the double-transgenic thymus does not affect their anatomical localization; B cells still reside in close proximity to the vasculature, as seen in thymi driven by the expression of Cm_Foxn4 alone (Fig. 4F). The TECs of the bipotent lymphoid organ in double-transgenic mice exhibit a phenotype intermediate between the single transgenics, as reflected in their cell surface phenotype (Fig. 4A); cTECs expressing high levels of Ly51 still predominate, although UEA1+ mTECs make up a quarter of the TEC compartment. The keratin expression pattern indicates that the medullary and cortical regions are not as precisely demarcated as in the Cm_Foxn1 single transgenic (Fig. 4B); however, the medulla contains a large number of Aire+ cells (Fig. 4E), in line with the gene expression pattern (Fig. 4G). In terms of lymphopoietic capacity, the double-transgenic TECs are distinguished by a markedly increased capacity for B cell development (about 10 times higher than that of the Cm_Foxn4 thymus), whereas the capacity for immature T cells is only slightly reduced compared to the Cm_Foxn1 single-transgenic thymus (Fig. 3, G and H). The unique morphological and functional characteristics of the double-transgenic thymus are reflected in an intermediate gene expression pattern, demonstrating that the combination of signature genes selected here faithfully report the thymopoietic characteristics of TECs. Collectively, our results indicate that the coexpression of Cm_Foxn1 and Cm_Foxn4 in the same TECs recapitulates the observed bipotent nature of lymphopoiesis in the thymi of extant cartilaginous fishes (34), providing an important validation of the biological relevance of the present reconstruction strategy.
Whereas Foxn4 proteins are well conserved during the course of vertebrate evolution (fig. S5), Foxn1 proteins are much more variable (Fig. 1 and fig. S6) in particular, with respect to the lengths and amino acid sequence compositions of their N-terminal domains. When viewed through the lens of the mouse proteins, the sequences encoded in coding exons 2 and 3 of mouse Foxn4 are replaced by unrelated sequences in a single exon (coding exon 2) of mouse Foxn1 (fig. S8). This observation suggested that, after gene duplication, the evolution of protein domain(s) in Foxn1 proteins was associated with increasing lymphoid selectivity, from bipotency of Foxn4 to unipotency of Foxn1. We set out to test this hypothesis by creating a chimeric protein, Foxn1*4, in which the sequence encoded by coding exon 2 of the mouse Foxn1 gene was replaced by coding exons 2 and 3 of mouse Foxn4 (Fig. 5A and fig. S8). The overall cellularity in the thymus of Mm_Foxn1*4 transgenic mice was reduced to about 20% of wild-type numbers, but the differentiation of T cells occurred normally, as revealed by the presence of normal percentages of CD4+ and CD8+ single-positive cells (Fig. 5, B and C). However, the CD4CD8 double-negative compartment was increased in the Mm_Foxn1*4 transgenic thymi, likely caused by an increase in the number of B cells (Fig. 5D). Expression of the Mm_Foxn1*4 chimeric protein led to a 10-fold increase of B cell poietic capacity, without appreciable loss of T cell poietic capacity, when compared to Mm_Foxn1 (Fig. 5, E and F).
(A) Schematic representation of the N-terminal domains of mouse Foxn4, Foxn1, and the Foxn1*4 chimera; boxes correspond to exons, and colored lines correspond to conserved amino acid residues in Foxn4 and Foxn1 clades (see figs. S2 and S8 for details). The > sign denotes the DNA binding and activation domains, which are not shown here. (B) Intermediate cellularity of Foxn1*4 thymi (***P < 0.001; two-tailed t test); wt (n = 5), Mm_Foxn4 (n = 6), and Foxn1*4 (n = 13). (C) Enlarged CD4CD8 DN compartment in Foxn1*4 thymi (P < 0.001; two-tailed t test); wt (n = 5) and Foxn1*4 (n = 13). (D) Moderately increased numbers of IgMCD93+ immature B cells (P = 0.293; two-tailed t test, compared to wt); wt (n = 3) and Foxn1*4 (n = 7). (E) Foxn1*4 supports intrathymic T cell development (P = 0.6654; two-tailed t test, compared to wt); wt (n = 5) and Foxn1*4 (n = 13). (F) Increased B cell development (*P = 0.0335; two-tailed t test, compared to wt); wt (n = 8), Mm_Foxn4 (n = 7), and Foxn1*4 (n = 13). In (E) and (F), data for Mm_Foxn4 transgenics (shaded area) are taken from (22). (G) Flow cytometric analyses of Ly51 expression and UEA1 binding of EpCAM+CD45 TECs; wt (n = 5) and Foxn1*4 (n = 13). (H) Epithelial microenvironment of reconstructed thymi resolved by keratin 5 (K5) (in green) and K8 (in red) staining; 4-week-old mice. (I) Localization of B220+ B cells (in green) adjacent to ER-TR7+ mesenchyme (in red); inset shows a higher magnification of the indicated region highlighting the perivascular space. (J and K) Differential gene expression patterns in TECs; see legend in Fig. 4 for details; wt (n = 3), Mm_Foxn4 (n = 6), Foxn1*4 (n = 3), and Cm_dtg (n = 5). In (B), (E), and (F), each data point represents one mouse.
Cell surface markers (Fig. 5G) of TECs in the Mm_Foxn1*4 thymus are reminiscent of the reconstructed thymus in Cm_dtg mice (Fig. 4A). This is evident from a 10-fold greater fraction of Ly51+UEA1 cTECs in the transgenic thymus, with a corresponding reduction of Ly51UEA1+ mTECs. This conclusion is supported by the pattern of K5 and K8 keratin expression and the histological features of cortical and medullary areas (Fig. 5H). Notably, as is the case in Cm_dtg transgenic thymi (Fig. 4F), B cells are situated in the perivascular space of the thymus of Mm_Foxn1*4-transgenic mice (Fig. 5I). Collectively, this finding demonstrates that the sequences in the evolutionarily dynamic N-terminal domains of Foxn1 and Foxn4 proteins have important roles in controlling the extent of B cell development in the thymic microenvironment. In further support of this conclusion, we find that the lancelet Foxn4 protein [which does not support B cell development (Fig. 2, C, D, and I)] lacks most of the conserved amino acid sequence signature of the vertebrate Foxn4 family in this domain (fig. S2). Last, as expected from flow cytometric profiles of TECs and the distinct histological features seen in the tissue sections, the gene expression signature of Foxn1*4-expressing TECs suggests a bias toward the cTEC lineage at the expense of mature mTECs (Fig. 5J), much like the situation in Cm_dtg mice (Fig. 5K).
Our results provide a previously unattainable possibility to compare the transcriptional profiles of thymic microenvironments established by the activity of the cephalochordate Bl_Foxn4, the combinatorial activities of shark Cm_Foxn1 and Cm_Foxn4, and the activity of the mammalian Mm_Foxn1 genes. On the basis of the expression levels of selected TEC signature genes, a clear evolutionary trend becomes apparent: A gradual decrease in expression of cTEC-like genes is accompanied by an increase in expression of the genes that are characteristic of the mTEC compartment (Fig. 6A). This genetic constellation is associated with the more than 100-fold increase in overall T lymphopoietic capacity when comparing the thymic microenvironment established by the activities of the amphioxus Bl_Foxn4 and the mammalian Mm_Foxn1 genes. At the same time, appreciable B lymphopoietic capacity appears to have been a transient phenomenon, absent in Bl_Foxn4-driven and Mm_Foxn1-driven thymic microenvironments but present in the unique Foxn1 and Foxn4 coexpressing microenvironments characteristic of cartilaginous and teleost fishes (22). Hence, we became interested to determine the potential mechanistic basis of the bipotent microenvironment. Our previous experiments (22) suggested that the ratio of Dll4 and Il7 expression levels in the thymic microenvironment is an important determinant of its lymphopoietic properties, with respect to the balance between T and B cell poiesis. The Notch1/Dll4 signaling pathway is essential for the initiation of T cell development in the thymus (5, 15, 16, 35), whereas Il7 functions as a general lymphopoietic growth factor (36). The Dll4 gene is known to be a direct target of the Foxn1 (5, 37) and Foxn4 (4, 38) transcription factors, whereas the expression of Il7 is independent of Foxn1 activity (39). In support of the latter conclusion, we observed similar expression levels of the Il7 gene in all reconstituted TEC compartments examined here. Hence, since the denominator in the Dll4/Il7 ratio is a constant, it follows that the Foxn1/4-dependent expression levels of Dll4 determine the particular type of lymphopoietic activity in the thymus. In the reconstructions with Cm_Foxn1 and Cm_Foxn4 genes, we observed that, compared to the single transgenics, the Cm_dtg thymus had the highest capacity for B cell development (Fig. 6B), in line with the natural bipotency of the thymus of cartilaginous fish (34, 40). The ratio of T cell poiesis and B cell poiesis (here referred to as the T/B index) positively correlated with the ratio of expression levels of Dll4 and Il7 genes (Fig. 6C). In the comparison of Mm_Foxn4, Mm_Foxn1, and Mm_Foxn1*4 transgenics, the same positive relationship between T/B index and Dll4/Il7 ratio holds (Fig. 6, D and E). As compared to the situation in wild-type mice, Dll4 expression is several fold higher in Bl_Foxn4 transgenic microenvironments than it is in Cm_Foxn4-driven TECs, reflecting the T cell bias in the former and the presence of B cell development in the latter. Overall, the Dll4 expression levels vary by about one order of magnitude (Figs. 4, C, E, and G, and 5, J and K). Although it is likely that other factors affect the lymphopoietic properties of the thymic microenvironment, the modulation of Dll4 expression through Foxn1/4 transcription factors emerges as an evolutionarily conserved and functionally relevant mechanism by which the lymphopoietic capacity and the bias for or against B cell development of the thymus could be modulated.
(A) Differential gene expression patterns in TECs; see legend in Fig. 2 for details. (B and D) T and B cell poietic indices; arrows indicate the altered balance between T and B cell generation. (C and E) Ratios of T and B cell indices as a function of the ratios of Dll4 and Il7 expression levels; Cm_Foxn4 (n = 6), Cm_Foxn1 (n = 7), Cm_dtg (n = 5), wt (n = 3), Mm_Foxn4 (n = 6), and Foxn1*4 (n = 7). ***P < 0.001 and *P < 0.05; one-way ANOVA with Tukeys multiple comparison test; SDs correspond to propagated errors. (F) Schematic summarizing gene content and expression characteristics and associated lymphopoietic properties of thymi during vertebrate evolution.
The in vivo reconstitution experiments described here suggest a sequence of events during vertebrate evolution that culminated in the emergence of the T cellbiased thymus. We hypothesize that the primordial vertebrate Foxn4-like gene was expressed in the pharyngeal endoderm in the ancestor common to all vertebrates, much like its ortholog in lancelets (4). After the emergence of lymphocytes, which may have had their evolutionary origin in lymphocyte-like cells of tunicates (41), the Foxn4-expressing patch of pharyngeal endoderm cells may have supported the development of T-like cells; we further propose that this primordial type of lymphopoietic activity initially supported their development only up to the stage where their germline-encoded antigen receptors were expressed (Fig. 6F). Our previous studies demonstrated that the expression of the Notch ligand Dll4 and the chemokine Cxcl12 in Foxn1-deficient TECs suffices to support T cell differentiation up to the CD4+CD8+ DP stage (5), albeit at a much lower efficiency than we observe here in Bl_Foxn4 reconstitutions. Nonetheless, these results collectively suggest that a small number of effector molecules suffice to jump-start the formation of a lymphopoietic environment. We consider it likely that at this particular stage of immune system evolution, the facility of somatic recombination of antigen receptor genes and an associated quality control mechanism(s) mitigating any potential autoreactivity was not yet established (42). Nonetheless, lymphocytes in the vertebrate ancestors immune system may have expressed different kinds of germline-encoded antigen-specific receptors, analogous to pattern recognition receptors; variegated expression of these sensory modules would have afforded early vertebrates with the capability of immune responses and memory functions through clonal proliferation, akin to natural killer cells in mammals (43). Collectively, the phenotype of the Bl_Foxn4 epithelium defines a previously unidentified checkpoint during TEC differentiation, which marks the support of T cell development up to the CD4+CD8+ DP stage.
The emergence of a typical vertebrate-like Foxn4 gene (here exemplified by Cm_Foxn4) heralds another critical transition point in the immune systems of early vertebrates, as it established an environment supporting the development of the two principal lymphocyte lineages. Within the epithelial TEC compartment, it fostered the further development of T cells to reach the single-positive stage, albeit at low efficiency, and at the interface between epithelial and mesenchymal components of the microenvironment, it established conditions conducive to B cell development, as indicated by the presence of substantial numbers of immature B cells in and around the perivascular space. A comparison of protein sequences suggests that changes in the N-terminal domain of Bl_Foxn4 facilitated this process. Since the predicted Foxn4 protein of tunicates assumes an intermediate position in the phylogeny of chordate Foxn1/4 proteins (Fig. 1), it will be of interest to examine its capacity to support the development of B cells.
After the emergence of the Foxn1 gene in a primordial vertebrate, as a result of a gene duplication event, coexpression in the pharyngeal epithelium of the paralogous Foxn4 and Foxn1 genes was maintained; this coexpression signature still persists in extant cartilaginous (fig. S7) (4) and bony fishes (22, 44). Protein sequence comparisons indicate that the emergence of the Foxn1 paralog was accompanied by a radical modification of the amino acid sequence composition of the N terminus. This finding strongly supports the notion that exon replacement event(s) accompanied the emergence of the first Foxn1 genes that exchanged two exons of the Foxn4 gene by a single exon of substantially different sequence. In the Cm_Foxn1 protein, the N terminus is much shorter than it is in the living representatives of evolutionarily more recent taxa, such as the mouse Foxn1 protein, suggesting that structural features of this domain rather than primary amino acid sequence similarities underlie the equivalent functionalities of the Cm_Foxn1 and Mm_Foxn1 proteins.
Because the overall number of TECs present in the thymic lobes was essentially invariant in all reconstructed thymi and similar in magnitude to that in the wild-type mouse thymus, the main difference between Bl_Foxn4 and the vertebrate versions of Foxn1/4 proteins is the much lower lymphopoietic capacity of the former. This observation indicates that the key functions of the Foxn1/4 proteins are to qualitatively alter epithelial cell phenotypes rather than acting to simply quantitatively expand the epithelial compartment via proliferation. Our results indicate that the increase in lymphopoietic capacity occurred in a stepwise fashion, from Bl_Foxn4 to Cm_Foxn4 to CmFoxn1. In addition, the transition from Foxn4 to Foxn1 was accompanied by an increased size of the mTEC compartment, associated with a larger proportion of mature single-positive T cells among thymocytes. In the embryonic mouse thymus, cTECs develop earlier than mTECs (45, 46); this ontogenetic sequence closely resembles the phenotypes we observe in the phylogenetic sequence of Bl_Foxn4 to Cm_Foxn4 to Cm_Foxn1.
Another critical transition in the evolutionary trajectory of Foxn1/4 genes and vertebrate thymopoiesis occurred when cis-regulatory changes led to the loss of Foxn4 expression in TECs. This reorganization of genetic networks is exemplified by the reciprocal expression patterns of Foxn1 and Foxn4 in chicken tissues (fig. S9). As a result, T cell development became entirely dependent on Foxn1 (9, 47). At present, we do not know why a degenerate network structure [note that Foxn4 and Foxn1 are partially redundant in the teleost thymus (22)] was replaced by a nonredundant design. However, since the contribution of the thymus to B cell development was abolished in this process, loss of Foxn4 expression in TECs helped establish the strict anatomical segregation of developing lymphocyte lineages (48). As a result, the thymus was eventually transformed into an organ highly specialized for efficient T cell development (Fig. 6F).
C57BL/6J mice are maintained in the Max Planck Institute of Immunobiology and Epigenetics. Foxn1:Bl_Foxn4, Foxn1:Cm_Foxn4, and Foxn1:Cm_Foxn1 transgenic mice were constructed according to standard protocols by cloning a 27,970base pair mouse Foxn1 promoter fragment (GenBank accession number Y12488; nucleotides 5680 to 33,650) upstream of either B. lanceolatum Foxn4 cDNA (GenBank accession number AJ252025.1; nucleotides 1 to 1590), C. milii Foxn4 cDNA (GenBank accession number FJ176202.1, nucleotides 56 to 1615), or a C. milii Foxn1 cDNA (GenBank accession number FJ176201.1; nucleotides 76 to 1584), followed by the bovine growth hormone polyadenylation sequence (32); cDNAs of Cm_Foxn4 and Cm_Foxn1 were synthesized by Eurofins Genomics and cloned into peX-K248 vector; in the Foxn1:Foxn1*4 construct, nucleotides 267 to 728 of M. musculus Foxn1 (GenBank accession number NM_008238.2) were replaced by nucleotides 170 to 445 of M. musculus Foxn4 (GenBank accession number AF323488.1). To generate transgenic mice, constructs were linearized and injected into FVB pronuclei according to standard protocols.
Transgenic mice were subsequently backcrossed to Foxn1-deficient mice (10) on a C57BL/6J background. Mice were kept in the animal facility of the Max Planck Institute of Immunobiology and Epigenetics under specific pathogenfree conditions. All animal experiments were performed in accordance with the relevant guidelines and regulations, approved by the review committee of the Max Planck Institute of Immunobiology and Epigenetics and the Regierungsprsidium Freiburg, Germany (license AZ 35-9185.81/G-14/57). Transgene expression levels were determined by RNA-seq, comparing transgene-derived BGH_PolyA transcripts to lacZ transcripts, the latter representing the activity of the targeted endogenous Foxn1 locus (10); the ratios of lacZ transcript counts to those emanating from the 5 part of the Foxn1 gene [note that the 5 end of the Mm-Foxn1 sequence is still detectable in the transcriptome of Foxn1/ mice (10)] served as normalization. A negative feedback loop suppresses the endogenous Foxn1 locus activity for transgenes encoding proteins functionally equivalent to Foxn1; despite a 10-fold difference in expression levels, the transgenes are expressed in the range of the endogenous Foxn1 gene in wild-type mice (fig. S10). For identification of transgenes, the following primers were used for genotyping: Foxn1:Mm_Foxn1, SS40 (wild-type allele) + SS35 (wild-type and knockout allele) + JBS003 (knockout allele), Foxn1:Mm_Foxn1*4, XAH388 + SS6; Foxn1:Cm_Foxn1, XAH163 + RM19; Foxn1:Cm_Foxn4, XAH163 + RM22; Foxn1:Bl_Foxn4, JBS465 + JBS466; SS40, 5-CTGTGAACTCAGCCATACTC; SS35, 5-TGCACCAAGCCTCTGCTGGGA; JBS003, 5-TCGCCTTCTTGACGAGTTCT; XAH388, 5-CAGCAACTGATAAGGTCACC; SS6, 5-ACAGAATTCTTCCAGCCATCA; XAH163, 5-GTCCCTAATCCGATGGCTAGCTC; RM19, 5-TATCGCGTGCACGAGTTGTA; RM22, 5-GGTTAAAGTTCATGCGGCCG; JBS465, 5-CCAGCTCCGAAACAGCCTAA; JBS466, 5-GTCCTTTGTCGTCTGGTCGT.
Thymus organs were fixed for 120 min in 4% paraformaldehyde, washed with phosphate-buffered saline (PBS), and incubated in 20% sucrose overnight before mounting and snap-freezing in optimal cutting temperature (OCT) embedding compound. Tissue sections (8 m) were cut using a cryostat and mounted onto precoated slides (Superfrost plus, Thermo Fisher Scientific). Slides were dried, followed by a 30-min blocking step using mouse immunoglobulin G (IgG) at 1:50 diluted in PBS + 0.5% bovine serum albumin (BSA) + 0.2% Tween. K5 K8 staining was performed with rabbit anti-K5 antibody (Ab) (PRB-160P, Covance) at 1:500 and rat anti-K8 Ab (Troma1, in-house) at 1:200. As secondary Ab, goat anti-rabbit Alexa Fluor 488 (A11008, Thermo Fisher Scientific) at 1:500 and donkey anti-rat Cy3 (AB_2340668, Jackson ImmunoResearch) at 1:500 were used. For ER-TR7 B220 staining, the rat antiER-TR7 Alexa Fluor 647 Ab (sc-73355 AF647, Santa Cruz Biotechnology) at 1:50 and rat anti-B220 Alexa Fluor 488 Ab (RA3-6B2, eBioscience) at 1:200 were used. Sections were mounted with Fluoromount G before analysis (Apotome, Zeiss). For combined K5/K8/Aire staining, sections were dried, blocked, and stained with unlabeled primary Abs as above and then stained with the secondary Abs donkey anti-rabbit IgG Cy3 (Jackson ImmunoResearch 711-165-152) and mouse anti-rat light chain Alexa Fluor 647 (MAR 18.5.28, purified and labeled in-house). Sections were then blocked with rat IgG and subsequently stained with rat anti-mouse Aire Alexa Fluor 488 Ab (5H12, eBioscience 14-5934-82) at 1:200.
RNA in situ hybridization was carried out essentially as described (22) using the following probes: Gallus gallus Foxn1, nucleotides 1371 to 2557 in GenBank accession number XM_415816.6; G. gallus Foxn4, nucleotides 559 to 1779 in GenBank accession number NM_001083359.1; Scyliorhinus canicula Foxn1, nucleotides 37 to 346 in GenBank accession number FJ187748; and S. canicula Foxn4, nucleotides 1 to 422 combined from GenBank accession numbers Y11538, Y11539, and Y11540, respectively.
To generate single-cell suspensions for analytical and preparative flow cytometry of TECs, the procedures in (49) were followed. Note that the enzymatic cocktail required to liberate TECs destroys the extracellular domains of CD4 and CD8 surface markers (but not that of the CD45 molecule); hence, when analysis of thymocyte subsets was desired, thymocyte suspensions were prepared in parallel by mechanical liberation, best achieved by gently pressing thymic lobes through 40-m sieves. Cell surface staining [anti-CD45 (30-F11), conjugated with phycoerythrin (PE) Cy7 (BioLegend); anti-EpCAM (G8.8), conjugated with allophycocyanin (APC; BioLegend); anti-Ly51 (BP-1) (6C3), conjugated with PE (eBioscience); UEA1, conjugated with fluorescein isothiocyanate (FITC; Vector Biosciences); anti-CD4 (GK1.5), conjugated with FITC (BioLegend); anti-CD8a (53-6.7), conjugated with APC (eBioscience); anti-CD19 (eBio1D3), conjugated with PerCPCy5.5 or PeCy7 (eBioscence); anti-B220 (CD45R) (RA3-6B2), conjugated with biotin (eBioscience); anti-IgM (II/4.1), conjugated with PE (eBioscience), anti-CD93 (C1qRp) (AA4.1), conjugated with APC (eBioscience); streptavidin conjugated with eFluor 450 or FITC (eBioscience)] was performed at 4C in PBS supplemented with 0.5% BSA and 0.02% NaN3. Because of their small size in Bl_Foxn4 mice, the numbers of TECs and hematopoietic cells in thymi were determined independently; hence, B and T poietic indices were calculated from mean values with error propagation.
Single-cell suspensions were prepared by TEC digest as described above. CD45EpCAM+ cells [negative enrichment using anti-CD45 magnetic-activated cell sorting (MACS) beads and antiTer-119 MACS beads, Miltenyi Biotec] were sorted directly into TRI reagent (T9424, Sigma-Aldrich). RNA isolation was performed according to standard protocols. Libraries were prepared using the Ultra RNA Library Prep Kit (Illumina). Samples were run on HiSeq2500 and sequenced to a depth of > 60 106 to 100 106 reads per sample.
The relevant Foxn1 and Foxn4 amino acid sequences can be found under the following GenBank accession numbers: Foxn1: Rhincodon typus (XM_020525471); C. milii (XM_007896499); Amblyraja radiata (XM_033046380); Erpetoichthys calabaricus (XM_028808185); Acipenser ruthenus (XM_034049625); Lepisosteus oculatus (XM_015367325); Danio rerio (XM_009291615); Microcaecilia unicolor (XM_030186024.1); Nanorana parkeri (XM_018555008.1); Xenopus laevis (XM_018248776.1); Xenopus tropicalis (XM_018091796); Podarcis muralis (XM_028708697); Geotrypetes seraphini (XM_033921305); Anolis carolinensis (XM_016997340); G. gallus (XM_415816); Corvus cornix cornix (XM_019287554); Monodelphis domestica (XM_001375795); Ornithorhynchus anatinus (XM_029082501); M. musculus (NM_008238); Homo sapiens (NM_001369369); Foxn4: B. lanceolatum (AJ252025); Branchiostoma belcheri (XP_019621093); Phallusia mammillata (LR785254); R. typus (XM_020536376); A. radiata (XM_033043787); C. milii (NM_001292643); L. oculatus (XM_006640210); E. calabaricus (XM_028824927); D. rerio (NM_131099); Latimeria chalumnae (XM_014493627); Rhinatrema bivittatum (XM_029571604); X. laevis (BC142562); X. tropicalis (NM_001102862); G. seraphini (XM_033957269); P. muralis (XM_028705153); G. gallus (NM_001083359); C. cornix cornix (XM_020584559); Phascolarctos cinereus (XM_021008024); M. musculus (NM_148935); H. sapiens (NM_213596). The sequence of Foxn4 of Ciona intestinalis has been retrieved from the ENSEMBL database (ENSCING00000017653). Sequences were aligned using multiple sequence comparison by log-expectation (MUSCLE) (50), and the phylogenetic tree was reconstructed using the neighbor-joining method implemented in the BioNJ software (51) with 1000 bootstrap replicates and the Jones-Taylor-Thornton (JTT) substitution model (52). Both programs are available on the platform phylogeny.fr (53). The resulting phylogeny was visualized using the Interactive Tree of Life platform (54).
Transcriptomes were analyzed on the Galaxy platform using featureCounts (55) followed by DESeq2 analysis (56).
t tests (two-tailed) were used to determine the significance levels of the differences between the means of two independent samples, considering equal or unequal variances as determined by the F test. For multiple tests, the conservative Bonferroni correction was applied or as indicated, using one-way analysis of variance (ANOVA) with Tukeys multiple comparison test.
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Retracing the evolutionary emergence of thymopoiesis - Science Advances
Retinal ischemia emerges in many ocular diseases and is a leading cause of neuronal death and dysfunction, resulting in irreversible visual impairment. We previously reported that brain-derived neurotrophic factor (BDNF)-expressing human 293T cells could steadily express BDNF and play a protective role in ARPE-19 cells, a human retinal epithelial cell line. Thus, we hypothesized that exosomes might be essential in the interaction between BDNF-expressing 293T cells and recipient cells. The study investigated whether exosomes derived from BDNF-expressing 293T cells (293T-Exo) can be internalized by ischemic retinal cells and exert neuroprotective roles. The results demonstrated that 293T-Exo significantly attenuated the loss of cell proliferation and cell death in R28 cells in response to oxygen-glucose deprivation treatment. Mechanistic studies revealed that the endocytosis of 293T-Exo by R28 cells displayed dose- and temperature-dependent patterns and may be mediated by the caveolar endocytic pathway via the integrin receptor. In the retinal ischemia rat model, the administration of 293T-Exo into the vitreous humor of ischemic eyes reduced apoptosis in the retina. Furthermore, 293T-Exo was mainly taken up by retinal neurons and retinal ganglion cells. Together, the results demonstrated that 293T-Exo has a neuroprotective effect in retinal ischemia and has therapeutic potential for retinal disorders.
PubMed
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Exosomes derived from BDNF-expressing 293T attenuate ischemic retinal injury and . - Physician's Weekly
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Opthalmic Drugs Growth Investigation Reveals Enhanced Growth during the forecast Period, 2020 2025 - The Cloud Tribune
