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LorettaNastoupil, MD: Hello, and thank you for joining this Targeted Oncology presentation, entitled, CD19 asaTherapeutic TargetinDiffuse Large B-Cell Lymphoma [DLBCL]. Patients with relapsed/refractory [R/R] diffuse large B-cell lymphoma DLBCL who are ineligible for autologous stem cell transplant have relatively few treatment options and poor outcomes. CD19 [cluster of differentiation 19] has become a therapeutic target of increasing interest, and both CAR [chimeric antigen receptor] T-cell therapy and [use of] monoclonal antibodies directed at CD19 have shown promise in this patient population. In today's Precision Medicine and Oncology discussion, we will talk about the role of CD19 in the therapeutic landscape for patients with transplant-ineligible, R/R DLBCL. I'm Dr LorettaNastoupil, associate professor in the Department of Lymphoma/Myeloma at The University of Texas MD Anderson Cancer Center in Houston. Joining me today is my colleague, Dr John Burke, a hematologic oncologist at Rocky Mountain Cancer Center in Aurora, Colorado. Thank you so much for joining.

John, how common is DLBCL?

John Burke, MD:Hi, Loretta. DLBCL is the most common subtype of non-Hodgkin's lymphoma [NHL]. There are about 80,000 or so cases of NHL diagnosed each year in the US, and about one-third of these are DLBCL. It puts it around 25,000 cases per year in the US. The incidence is in the ballpark of 6 new cases per 100,000 per year, and it's slightly more common in men than in women. It's the most common of the NHLs, so I think most community oncologistsdefinitely seea fair amount.

LorettaNastoupil, MD:We spent the last probably 10-plus years talking about germinal center versus non-germinal center subtypes. How does this distinction impact prognosis, and do you use it for treatment selection?

John Burke, MD:Yes. We've known for more than 20 years that one can divide DLBCL into a couple of different groups based on the expression of genes within cancer cells. This can be done via a technique called gene-expression profiling. When you apply gene-expression profiling to large cell lymphoma, you can classify it as either a germinal-center B subtype or an activated B-cell subtype. Gene-expression profiling is a technique that's not widely used in practice. Several years after [this advance], it was discovered that using immunohistochemical staining canserve as an estimate of the gene expression profilerelated classification of these lymphomas.

What's usually done in clinical practice now is that pathologists will use immunohistochemical staining and algorithms to describe DLBCL as germinal center B or non-germinal center B subtypes. Then the question is, Does this impact your treatment? The answeris thata lot of attempts have been made in the last couple of decades to target therapies toward different subtypes of DLBCL, and really none of those has stuck or proven to be truly beneficial. At this point, at least in my practiceand I'm curious to hear about yoursit really hasn't affected treatment. As for prognosis, we do know that the activated B-cell subtype generally has a less favorable prognosis than [does] the germinal center B subtype when conventional treatments are used. How about you? Isthis something that affects your practice at all day-to-day?

LorettaNastoupil, MD:No, not really. And, as you mentioned, its not likely, because there has beena number ofrandomized studies that have failed to demonstrate an improvement over R-CHOP [rituximab, cyclophosphamide, hydroxydaunorubicin, vincristine sulfate (Oncovin), prednisone]. Well, it probably had the biggest impact, as we've just had more trials, generally speaking, forthe nongerminal center subtype. Moving forward, our trials have become agnostic to this.

Transcript edited for clarity.

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Overview of DLBCL - Targeted Oncology

From the Labs sat down with Dr. Nino Rainusso, assistant professor of pediatrics hematology/oncology and a member of the Dan L Duncan Comprehensive Cancer Center at Baylor College of Medicine. Dr. Rainusso shared what inspired him to become a pediatric oncologist, his experience finding a research position in a Baylor lab and something few know about him.

I was born and raised in Per where I attended medical school at Universidad Peruana Cayetano Heredia. Early in my training I realized that if I wanted to better understand the medical conditions of my patients, I had to be involved in biomedical research. I wanted to become a physician-scientist in the field of pediatric neurology. This changed when I met my wife. Her brother had neuroblastoma, a common pediatric cancer that frequently develops in nerves associated with the adrenal glands located on top of the kidneys. When he died of the cancer, my career took a different path. Instead of spending my life as a pediatric neurologist, I became a pediatric oncologist.

During my rotations in medical school, I saw that doctors were exceptionally good at providing medical care for their patients but didnt have time to do research. That motivated me to come to the U.S. where I would have opportunities to continue my career as a physician-scientist.

After I completed my residency in general pediatrics at the University of Illinois at Chicago, I was accepted at Baylor for my fellowship in pediatric oncology. I dove into research in the second and third years. Having many patients with different types of tumors for which the treatment outcome has not significantly changed for the last 30 years meant that there was a wealth of research opportunities. One day, I attended a talk about cancer stem cells that inspired me to apply that approach to pediatric solid tumors.

I joined Dr. Jeff Rosens lab at Baylor. I liked his lab for its open-minded environment and collaborative atmosphere that many Baylor labs have.

I was not sure about what his response would be when I proposed to work in his group.

He has spent his entire life doing research in breast cancer and I, with little lab experience under my belt, was proposing to do research in osteosarcoma stem cells. Osteosarcoma is the most common bone cancer in children and young adults. I was expecting that he would try to change my mind, but instead he said, OK, welcome! I loved it! I am very grateful that I ended up working in Jeffs lab. He has been a wonderful mentor, and I learned a lot working in his group.

When it was time for me to have my own lab, I joined Dr. Jason Yusteins group at Texas Childrens Cancer & Hematology Centers. We took a new approach to study osteosarcoma. One limitation of studying this condition is working with cell lines, which do not seem to recapitulate most of the characteristics of tumors in patients.

We decided to generate patient-derived tumor xenografts models of pediatric sarcomas where the tissue from a patients tumor is implanted into immunosuppressed mice. These tumors closely resemble the characteristics of the original tumor allowing to have better understanding of cancer biology and to evaluate novel therapies.

We collaborate with other investigators to test new treatments such us immunotherapy in these xenograft models, which may put us a step closer to bringing more effective therapies to patients. I believe that our research would not be possible without the participation of multiple colleagues at Texas Childrens Hospital and the nurturing scientific environment provided by Baylor College of Medicine.

My close friends Alicia and Miguel are superb science teachers in a high school that serves economically disadvantaged communities.

Their schools have many dropouts and one of the reasons seems to be lack of opportunities for students to know what they could become.

Most students, not only Hispanics, are not aware of what scientists do or what a research lab looks like.

One idea could be to sponsor science fairs in these schools and award prizes that also include student tours of Baylor or Texas Childrens lab facilities. Students also need to be aware of scholarships they could apply for to pursue a higher education.

Finally, academic institutions and researchers may also participate in school talks to promote a better understanding of science and its direct repercussions in our daily life and to reduce the mistrust in science, which is a growing topic of significant concern.

I am a Star Wars fan so my office has many items from a galaxy far, far away.

By Ana Mara Rodrguez, Ph.D.

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FROM THE LABS: Hispanic Heritage Spotlight: Interview with Dr. Nino Rainusso - Baylor College of Medicine News

Mirror photo by Patrick Waksmunski / Johnathan Dodson, an intensive care unit nurse practitioner who treats COVID-19 patients at UPMC Altoona, recently met the woman who donated the stem cells that helped him overcome leukemia.

A few weeks ago, nurse practitioner and former leukemia patient Johnathan Dodson interrupted a reporters phone interview to give his two young sons a hug and a kiss before they went to sleep.

The interview concerned the Claysburg natives recent appearance as a healthcare hero on Jimmy Kimmel Live, because Dodson treats COVID-19 patients at UPMC Altoona.

The segment also featured Dodsons surprise virtual meeting on the show with his own healthcare hero: the Texas woman who donated the stem cells that enabled Dodson to survive past his early 20s via a transplant.

Theyre here because of her, Dodson, 36, said of the little boys hed just sent off to bed.

In the interaction that followed the on-screen introduction to his donor, Dodson tried to explain his feelings about what the woman had done: how it hadnt been limited to saving his life, but had also kept his parents, siblings and friends from losing him and had spread out to allow for the establishment of his own family, including those kids, Chase, now 7, and Karter, now 4.

I dont think she realized the ripple effects, Dodson said.

He had long thought about a first encounter with Shannon Weishuhn of Rowlett, Texas.

I had kind of prepared this thank-you speech in my head, he said.

(But) how do you thank someone who saved your life? Dodson asked.

For Weishuhn, also a nurse, the donation was an ancient memory, Dodson said, based on an off-screen conversation he had with her, which included a virtual meeting with his family.

She had no idea of the butterfly effect that her action had on his world, he said, speaking of the idea that small occurrences can have big consequences. Thats the message I was trying to convey, he said.

Almost didnt make it

Dodson almost didnt make it to the transplant.

But in the process of getting through his difficulties with leukemia, he found his calling.

He was diagnosed initially in 2003.

He went through chemotherapy to wipe out my immune system, which also wiped out the cancer cells, he said.

The idea was to do an immune system reset, with the hope that the cancer cells wouldnt grow back, he said.

He went into remission, but relapsed at the beginning of 2004, he said.

So he underwent chemotherapy again.

He relapsed again.

The third time he got chemo was in preparation for the transplant.

He nearly died multiple times, and at one point, his survival chances shrunk to about 3 percent, Dodson said.

The cancer had broken into his spine and his brain, he said.

Only a handful of prior cases had been treated successfully when that had happened, he said.

There were three options a shunt in his head and more chemotherapy, spinal taps with chemo or hospice at home, he said.

His parents knew he didnt want a shunt in his head, so that was out of the question, Dodson said.

His parents asked the doctors what theyd do if he was their son, and they recommended hospice, he said.

But a nurse stepped in and said you need to give him a chance, arguing that his survival from two previous crises should merit another try, Dodson said.

Thats when my parents switched and opted for treatment, Dodson said. That sealed the deal.

Once the decision was made, there was talk about sending him to Texas, the only place where the contemplated treatment had been done successfully, he said.

Dodson nixed that.

If I was going to die, I was going to die here, he said.

The reason Im here today

By that time, the nurses who took care of him at West Penn Hospital, now part of Allegheny Health Network, had almost become family, he said.

They along with his donor are the reason Im here today, he said.

The nurses are also the reason hes a nurse himself.

The transplant, however, didnt suddenly make things all better.

He had a really rough go (afterwards), said Dr. John Lister, chief of the division of hematology and cellular therapy of Allegheny Health Network Cancer Institute and a member of Dodsons transplant team.

Caring for patients after leukemia transplants is as challenging as anything in medicine, said Lister, who is a descendant of Joseph Lister, a pioneer in antiseptic surgery.

Its challenging because the blood stem cells harvested from the donors blood, when injected into the recipient, create a new white-blood-cell immune system that attacks the recipients diseased white-blood-cell immune system, Lister indicated.

It can be fatal, he said. And extremely debilitating.

Doctors deal with it by giving powerful immunosuppressant medications, he said.

The direction of attack the donor material attacking the recipients is the opposite of the direction of attack with transplants of organs like kidneys, Lister said.

After those other transplants, the recipients immune system attacks the donor organ, he said.

Dodson was kept alive due to the intensive efforts of many people, Lister said.

Eventually, the initial reaction dies down, Lister said.

Hes totally normal at this point, Lister said of Dodson. I would say hes cured.

The donor matched Dodson in certain key genes that make the immune system work, Lister said.

The harvesting of donor stem cells occurs after the donor is given a growth factor that causes those stem cells to leave the bone marrow and enter the bloodstream, Lister said.

Blood stem cells can become any of the three types of blood cells, given the right conditions.

When injected into the recipient, they home to the marrow where theyre needed, according to Lister.

There they divide and repopulate, he said.

Anyone willing to make a bone marrow or stem cell donation can go to bethematch.org.

Its free to register, Dodson said. More ethnically diverse donors are needed, he added.

Last year, the web site helped facilitate 6,425 transplants, Dodson said.

You could change someones life forever, he said.

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UPMC nurse practitioner hailed 'healthcare hero' on live TV - Altoona Mirror

BrainStrom Cell Therapeutics Inc. (NASDAQ:BCLI) has announced an agreement with Catalent (NYSE:CTLT) for the manufacture of its autologous cellular therapy, NurOwn. BrainStorms NurOwn is being studied to treat amyotrophic lateral sclerosis (ALS), also known as motor neuron disease or Lou Gehrigs disease.

The autologous cellular therapy induces mesenchymal stem cells (MSC) to produce high levels of neurotrophic factors that promote neuroprotection and survival of neurons. The therapy targets disease pathways integral in neurodegenerative disorders. The FDA has granted NurOwn Fast Track designation for amyotrophic lateral sclerosis, and it has also received Orphan Drug Status from the EMA and FDA for ALS. Currently, BrainStorm is completing a 200-patient placebo-controlled, double-blind repeat-dosing NurOwn in third phase study in the US.

As part of the agreement, Catalent will transfer the manufacturing process to BrainStorm and offer future CGMP clinical supply of NurOwn from the 32,000 sq. ft. cell therapy manufacturing facility in Texas. After completing the clinical trials and ahead of possible approval of NurOwn, the companies will extend the agreement to include commercial supply from the facility.

BrainStors CEO, Chaim Lebovatis, said that they are proud to enter a partnership with Catalent to support the commercial supply of NurOwn. Lebovits said that there is an urgent need for a new treatment alternative for ALS patients. He added that if the current NurOwn clinical trials are successful, then the agreement with Catalent will be vital in accelerating access for ALS patients.

Manja Boerman, the President of Catalent Cell & Gene therapy, indicated that they have experience in cell therapy development, a capable state-of-the-art facility in Huston to meet manufacturing needs. He added that this will position the company to support BrainStorm in manufacturing its lead therapeutic candidate to treat ALS. Boerman said that they are looking forward to the partnership with BrainStorm and offering their stem cell therapy manufacturing expertise to optimize production and streamline NurOwns commercialization path.

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BrainStrom Cell Therapeutics (NASDAQ:BCLI) Enters Agreement With Catalent (NYSE:CTLT) For Manufacture Of Its NurOwn Cell Therapy - BP Journal

Womens health and cosmetic care is a combination that simply makes sense. After owning a successful ObGyn practice for more than a decade, Dr. Daisy Ayim felt something was missing from the gynecological and obstetric services she offered her patients. Upon listening to her patients wants and needs, Dr. Daisy Ayim decided to temporarily leave her successful practice to study cosmetic surgery. This decision required years of hard work and sacrifice. Thankfully, Dr. Ayim is no stranger to hard work.

Originally born in Cameroon, Dr. Ayim immigrated to America with her parents at the young age of 13. The family settled in Texas and Dr. Ayim immediately immersed herself in her studies with a dream of becoming a doctor. She attended Louisiana State University (Go Tigers!) and went to medical school at the University of Texas Medical Branch. She went on to complete her ObGyn residency at Howard University Hospital and faculty at the John Hopkins Hospital. Through this entire experience, Dr. Ayim never lost sight of her intrinsic desire to help people, especially if this meant making a positive impact on women. The path to gynecology and obstetrics was a natural fit for Dr. Ayims warm, gentle nature.

Today, Dr. Ayim has delivered over 3,000 babies and performed thousands of gynecologic and cosmetic surgeries at Ayim Aesthetic, a comprehensive cosmetic surgery and womens health practice that offers both surgical and non-surgical solutions, with an emphasis on feminine cosmetic surgery.

An office that offers obstetrics, gynecology, and cosmetics is a rarity, but to Dr. Ayim, It just makes sense! ObGyn and cosmetic surgery may seem very different, but in many ways, theyre integral, especially for women, and having experience in both is very beneficial.

Dr. Ayim and her team at Ayim Aesthetic offer a wide range of surgical and nonsurgical procedures including abdominoplasty (tummy tuck), liposuction, body lifts, mommy makeovers, scar revision, facetite, bodytite, fat transfer, and more. She also offers several skin services such as fillers, botox, chemical peels, PRP-platelet rich plasma, facetite, bodytite, and radiofrequency micro-needling, including the famed Morpheus8 treatment. Dr. Ayims feminine cosmetic offerings include stem cells with platelet rich plasma, liposuction, fat transfer, and more. In each unique procedure, Dr. Ayim and her team at Ayim Aesthetic guarantee custom care, while maintaining a high standard of excellence. When Dr. Ayim first founded her practice, she knew that she wanted it to be different from the cold and sterile environments of other gynecological offices shed worked in or visited as a client. From the luxurious leather seats to the lighting and the office staff, the entire experience speaks to Dr. Ayims high standards of care. Dr. Ayim brings innovation and the most up to date techniques and technology to each patient experience while never losing sight of the need for warm, personalized, and custom attention.

New and old patients of Dr. Ayim can expect to instantly feel at ease when they walk into her office. Dr. Ayims careful dedication to treatment plans, procedures, and aftercare ensure optimal results and satisfaction for each patient she works with. Whether a patient is preparing to give birth or wants to regain their confidence after children, Dr. Ayim is committed to empowering women through quality care, exceptional kindness, and elegant transformation.

To visit Ayim Aesthetic or schedule a consultation call, visit: https://www.drdaisyayim.com/cosmetic-surgeon-obgyn-houston.

Media ContactContact Person: Daisy Ayim MD FACOGEmail: Send EmailPhone: 713-640-5922Address:12606 West Houston Center Blvd, Suite 120 City: HoustonState: TXCountry: United StatesWebsite: https://www.drdaisyayim.com

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Dr. Daisy Ayim, Cosmetic Surgeon, ObGyn, Business Owner and Entrepreneur, Is Revolutionizing The Integration Of Women's Health And Cosmetic Care -...

Five Indian American researchers and one Bangladeshi-American have been named among the 2020 Directors New Innovator Award recipients by the National Institutes of Health.

Among the recipients are Anindita Basu, Subhamoy Dasgupta, Deeptankar DeMazumder, Siddhartha Jaiswal, Shruti Naik, and Mekhail Anwar, according to the NIH website.

Basu, of the University of Chicago, was selected for the project, Profiling Transcriptional Heterogeneity in Microbial Cells at Single Cell Resolution and High-Throughput Using Droplet Microfluidics.

The Indian American is an assistant professor in genetic medicine at the University of Chicago and leads a multi-disciplinary research group that uses genomics, microfluidics, imaging and nano/bio-materials to develop new tools to aid in diagnosis and treatment of disease.

Basu obtained a B.S. in physics and computer engineering at the University of Arkansas, Ph.D. in soft matter physics at University of Pennsylvania, followed by post-doctoral studies in applied physics, molecular biology and bioinformatics at Harvard University and Broad Institute.

Her lab applies high-throughput single-cell and single-nucleus RNA-seq to map cell types and their function in different organs and organisms, using Drop-seq and DroNc-seq that Basu co-invented during her post-doctoral work.

Dasgupta is with the Roswell Park Comprehensive Cancer Center and was named for his project, Decoding the Nuclear Metabolic Processes Regulating Gene Transcription.

Dasgupta is an assistant professor in the Department of Cell Stress Biology at Roswell Park Comprehensive Cancer Center. He earned his B.S. from Bangalore University and M.S. in biochemistry from Banaras Hindu University, India before receiving his Ph.D. in biomedical sciences from University of North Texas Health Science Center at Fort Worth, where, as a Department of Defense predoctoral fellow, he characterized the functions of a novel gene MIEN1 in tumor progression and metastasis.

He then joined the laboratory of Bert W. O'Malley, M.D. at Baylor College of Medicine, where he studied the functions of transcriptional coregulators in tumor cell adaptation and survival, as a Susan G. Komen postdoctoral fellow.

DeMazumder, of the University of Cincinnati College of Medicine, was chosen for the project, Eavesdropping on Heart-Brain Conversations During Sleep for Early Detection and Prevention of Fatal Cardiovascular Disease.

DeMazumder joined the University of Cincinnati in 2017 as assistant professor of medicine, director of the Artificial Intelligence Center of Excellence and a Clinical Cardiac Electrophysiologist after completing his doctorate at SUNY Stony Brook in Synaptic Electrophysiology, a medical degree at Medical College of Virginia-Virginia Commonwealth University, internship at Mount Sinai and residency at University of Virginia in Internal Medicine, and clinical and research fellowships at Johns Hopkins University.

His longstanding goals are to transform clinical observations into testable research hypotheses, translate basic research findings into medical advances, and evaluate personalized treatment protocols in rigorous clinical trials, while caring for patients with heart rhythm disorders and improving their quality of life.

Jaiswal, of Stanford University, was named for his project, Clonal Hematopoiesis in Human Aging and Disease.

Jaiswal is an investigator at Stanford University in the Department of Pathology, where his lab focuses on understanding the biology of the aging hematopoietic system.

As a post-doctoral fellow, he identified a common, pre-malignant state for blood cancers by reanalysis of large sequencing datasets.

This condition, termed "clonal hematopoiesis, is characterized by the presence of stem cell clones harboring certain somatic mutations, primarily in genes involved in epigenetic regulation of hematopoiesis.

Clonal hematopoiesis is prevalent in the aging population and increases the risk of not only blood cancer, but also cardiovascular disease and overall mortality. Understanding the biology of these mutations and how they contribute to the development of cancer and other age-related diseases is the current focus of work in the lab.

Naik, of New York University School of Medicine, was named for her project, Decoding Microbe-Epithelial Stem Cell Interactions in Health and Disease.

Naik is an assistant professor at New York University School of Medicine. She received her doctorate in Immunology from the University of Pennsylvania-National Institutes of Health Graduate Partnership Program.

There she discovered that normal bacteria living on our skin, known as the commensal microbiota, educate the immune system and help protect us from harmful pathogens.

As a Damon Runyon Fellow at the Rockefeller University, Naik found that epithelial stem cells can harbor a memory of inflammation which boosts their regenerative abilities and established a new paradigm in inflammatory memory, her bio states.

The Naik lab studies the dynamic interactions between immune cells, epithelial stem cells, and microbes with a focus on 3 major areas of research: Tissue regeneration and cancer, host-microbe interactions, and early in life immunity.

Anwar, of U.C. San Francisco, was named for his project, Implantable Nanophotonic Sensors forIn VivoImmunoresponse.

Anwar, whose father is from Bangladesh, is a physician-scientist at UCSF, where he is an associate professor in the Department of Radiation Oncology. Driven by the challenges his patients face when fighting cancer specifically addressing the vast heterogeneity in treatment response by identifying the optimal treatment to pair with each patients unique biology he leads a laboratory focused on developing integrated circuits (or computer chips) forin vivocancer sensing.

After completing his bachelors in physics at U.C. Berkeley, where he was awarded the University Medal, he received his medical degree at UCSF, and doctorate in electrical engineering and computer science from the Massachusetts Institute of Technology where his research focused on using micro-fabricated devices for biological detection.

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Five Indian American Researchers Named Among NIH 2020 New Innovator Awardees - India West

INTRODUCTION

Medulloblastoma (MB), the most common pediatric brain tumor, is considered an embryonal tumor of the cerebellum (16). Although the cellular origin of MB is unclear, it has been speculated that MB tumor cells arise from neuronal stem or progenitor cells during early life. On the basis of its molecular features, MB can be categorized into four subtypes: WNT (wingless) pathwayactivated, SHH (Sonic hedgehog)pathwayactivated, and the less well-characterized group 3 and group 4 (710). MB is well known for having very few genomic mutations compared with adult cancers and other pediatric cancers (6, 11). Recent studies have shown that different MB subtypes harbor distinct epigenetic signatures and undergo dynamic alterations in DNA methylation during tumor progression and clinical treatment (10). DNA hypomethylation is strongly associated with increased gene expression in MB, suggesting that DNA demethylation might play a pivotal role in MB pathogenesis (12). The Ten-eleven translocation family of dioxygenases plays a major role in DNA demethylation by catalyzing the oxidation of 5-methycytosine (5mC) to produce, in succession, 5-hydroxymethylation (5hmC), 5-formylcytosine, and 5-carboxycytosine (13). Among these oxidized 5mC derivatives, 5hmC is the predominant catalytic product and functions as an epigenetic mark to modulate chromatin accessibility and gene transcription (14). The diagnostic and prognostic value of 5hmC in circulating cell-free tumor DNA (ctDNA) or cancer tissues has been reported for several types of tumors (e.g., B cell lymphoma and colon cancer) (15, 16), but its value for pediatric brain tumors remains to be determined.

MB is currently diagnosed on the basis of clinical symptoms and radiographic findings, with final confirmation by histopathological examination. For group 3 and group 4 MBs, approximately 30% of patients show signs of metastasis at diagnosis (17). In addition to radiographic evaluation of detectable metastasis, lumbar puncture (LP) is often performed at diagnosis to complete the staging process, with the disseminated cases classified according to the Chang Staging System (i.e., M stage) (18). Routine magnetic resonance imagings (MRIs) are obtained during and after treatment to assess treatment response and to monitor recurrence. Repeated LPs are typically performed at the end of therapy and when clinically indicated. Recent advances in imaging-based diagnostic techniques have markedly improved the early detection and assessment of treatment outcomes (19). However, there remains a strong desire to have an independent method that can reliably monitor tumor treatment response and confidently detect early tumor recurrence, before anatomical or metabolic changes are evident by advanced imaging techniques [e.g., MRI, computed tomography, positron emission tomography, and single-photon emission computed tomography] (19, 20).

Liquid biopsy, which is based on the analysis of ctDNA, exosomes, or circulating tumor cells in plasma or other biological fluids, has emerged as a promising approach to aiding the timely detection, molecular profiling, and response monitoring of many solid tumors (21). However, because of the blood-brain barrier, plasma contains substantially lower amounts of ctDNA from brain tumors than from peripheral solid tumors. In contrast to plasma, cerebrospinal fluid (CSF) interacts more frequently with brain tumor cells in the central nervous system (CNS) and can serve as a substrate for liquid biopsy. It has been shown that the mutations in CSF ctDNA parallel the genetic alterations in the brain tumor and may serve as a reliable source to monitor brain tumor status (2224). However, whether CSF ctDNA modifications faithfully reflect brain tumor epigenetic landscapes remains underexplored. In the current study, we obtained DNA methylomes and hydroxymethylomes using whole-genome bisulfite sequencing (WGBS) and anticytosine-5-methylenesulfonate (anti-CMS) immunoprecipitation sequencing (CMS-IPseq) (25), respectively, for very small amounts of CSF ctDNA from pediatric patients with MB. We found a positive correlation between CSF samples and tumor tissues, suggesting that CSF ctDNA can be used as material to monitor changes in MB tumor DNA methylomes and hydroxymethylomes. Furthermore, by analyzing the DNA methylation dynamics in ctDNA purified from serial CSF samples in the same patients, the tumor-specific DNA methylation signatures occur before the positive cytology analysis, suggesting the high-sensitivity and potential high-clinic impact of our method to modulate the MB disease status. In addition, by correlating epigenetic changes in CSF ctDNA with the clinical outcomes for patients with MB, we identified DNA methylation markers of diagnostic and prognostic value detectable in CSF ctDNA to aid the management of MB.

To characterize the cell-free DNA in CSF, we performed the bioanalyzer analysis using the purified DNA from precentrifuged CSF samples (fig. S1A). We observed that the majority of DNA fragments ranged from 100 to 400 base pairs (bp) with the peak size at 200 bp, which is consistent with a previous report (26). This finding suggests that the majority of DNA from CSF in the analyzed samples is ctDNA. To profile the DNA methylation and hydroxymethylation patterns in MB ctDNA from CSF, we prepared sequencing libraries using these precentrifuged CSF samples with or without additional centrifugation after recovery from freezer (fig. S1, A and B, and table S1). After evaluating the conditions, we found that 200 l of CSF without an additional centrifugation yielded sufficient ctDNA that could be used to generate high-quality libraries suitable for sequencing (fig. S1C and table S1). Compared to a previous method (27), our optimized protocol, which uses random priming to construct the bisulfite library, required much less CSF as input (0.2 ml versus 1 ml). However, a low-input volume combined with the small-fragment sizes of ctDNA can result in a low ratio of uniquely mapped reads and, consequently, high cost. We therefore developed LiBis (28), a method that can markedly increase the ratio of uniquely mapped reads for bisulfite sequencing of low-input DNA (fig. S1D). We then collected matched MB (SHH) tumor and CSF samples from patients 1, 2, and 3 and MB (WNT) CSF samples from patient 4 (Fig. 1A) for integrative epigenomic analyses. To test whether CSF can be used to monitor tumor status following treatment and to predict recurrence, we also collected a total of eight MB CSF samples from patients 2, 3, and 4 during and after treatment (Fig. 1A and table S1). The CSF collected from patients with hydrocephalus (n = 4) and the CSF samples collected from patients with acute lymphoblastic leukemia (n = 2) were used as surrogate nontumor CSF controls, and normal cerebellum tissues (n = 2) were used as tissue controls (Fig. 1A). Overall, we obtained an average of 600 million reads covering 13 million CpG sites at least three times by WGBS analysis, with bimodal distribution of the DNA methylation ratios and without M bias after trimming of the first 10 bp along the read (fig. S1, E and F, and table S1). The average DNA methylation level was near 0.6 to 0.8, which was consistent with a previous study (12) (fig. S1G). In parallel, we collected an average of 23 million reads to yield an average of 85,000 5hmC-enriched regions using the CMS-IPseq method (table S1). The distribution patterns of ctDNA methylation and hydroxymethylation for metagenes were consistent with that of tumor tissues, as described in previous publications (14) (fig. S1H). In addition, we compared WGBS data of MB tissues obtained in this study with previously published WGBS data from MB tumors (12). We also observed a relatively high Pearson correlation coefficient (>0.5) between these two datasets regardless of MB subtypes (fig. S1I). Furthermore, 5hmC was enriched in common H3K27ac-enriched regions (9) among four subtypes in both ctDNA and MB tissues (fig. S1J), which was consistent with 5hmC distribution in other systems, including embryonic stem cells, T cells, and B cells (14). These data suggest that our optimized protocol yields DNA methylomes and hydroxymethylomes of high quality from CSF ctDNA.

(A) Schematic of the experimental design. Normal cerebellum tissue (n = 2), nonMB CSF samples (n = 6, four patients with hydrocephalus without symptoms of other diseases and two patients with acute lymphoblastic leukemia without brain metastasis), matched MB tumor tissue, and CSF sample pairs from patients with MB SHH (patients 1, 2, and 3) and CSF samples from patient 4 (WNT) were used in this study. (B) Pearson correlation analysis of the DNA methylation status of common CpG sites (covered at least 10 times) and common hydroxymethylated regions shared between CSF ctDNA samples and their matched MB tumors. (C) Pearson correlation analysis of the DNA methylation status of the CpG sites that are common between indicated CSF ctDNA samples and published MB tumor samples (n = 34). The minimal coverage of selected CpG sites was 5. (D) Pearson correlation analysis of the DNA methylation and hydroxymethylation at the indicated regulatory elements between CSF ctDNA and matched MB tumors. (E) Scatter plots showing the correlation of DNA methylation levels between CSF ctDNA and matched MB tumors within CpG island (CGI) regions (CpGs covered at least 10 times).

To further evaluate the data quality of WGBS data obtained in ctDNA in MB CSF, the Pearson correlation analysis shows that there is a relatively high Pearson correlation coefficient between matched MB CSF and tumor samples (average > 0.5), while the Pearson correlation between nontumor CSF samples and MB tumors are relatively low (average < 0.33) (Fig. 1B, top, and fig. S2, A and B). These findings suggest that CSF ctDNA can be used to faithfully elucidate DNA methylation profiles representative of MB tumors in situ. Similarly, the Pearson correlation of the DNA hydroxymethylation analysis between MB tumor and matched CSF ctDNA ranged from 0.4 to 0.8 (Fig. 1B, bottom). In parallel, to estimate the individual variations of these DNA epigenetic markers, we performed pairwise comparisons of the CSF ctDNA methylation and hydroxymethylation data among analyzed patients. We observed a significant positive correlation between the individuals, suggesting that DNA epigenetic markers might be relatively well conserved with low interpatient variation (fig. S2C).

Next, we compared DNA methylation and hydroxymethylation levels within the regulatory elements between MB tumor and matched MB CSF. We observed a relatively high Pearson correlation coefficient (average r = 0.7) between tumor and CSF within genic regions, including transcription start sites, exons, CpG islands (CGIs), and promoters (fig. S2D). A relatively low Pearson correlation coefficient (average r = 0.5) was found for repeat elements, including long interspersed nuclear elements (LINEs), short interspersed nuclear elements (SINEs), and long terminal repeats (LTRs) (Fig. 1D). Furthermore, the DNA methylation levels within CGIs were more strongly correlated between MB tumor tissue and MB CSF and were highly consistent among individuals (Fig. 1E, and fig. S2, E and F). These results suggest that DNA methylation status within the CGIs of CSF ctDNA could potentially serve as biomarkers to report the status of the original MB tumor.

To evaluate whether differences in the DNA methylation and hydroxymethylation between MB and normal cerebellum tissue were recapitulated in CSF ctDNA, we identified differentially methylated regions (DMRs) or differentially hydroxymethylated regions (DHMRs) by comparing normal cerebellum data, MB tumor data, and MB CSF data (Fig. 2, A and B) using MOABS (29). Consistent with a previous report (12), MB tumors displayed a global decrease in DNA methylation but increased DNA methylation at CGIs (fig. S3A). Next, we selected the DMRs or DHMRs that we identified as shared (i.e., common) between the normal cerebellum and the MB tumor and between the normal cerebellum and the MB CSF. In total, we obtained 17,898 and 1777 common hyper- and hypo-DMRs, respectively, and 39,602 and 20,707 common hyper- and hypo-DHMRs, respectively (Fig. 2, A and B). The average Pearson correlation coefficient of DNA methylation of CpGs in DMRs and DHMRs was >0.6 between the MB CSF and the MB tumor (fig. S3B). The methylation differences between the MB CSF and the normal cerebellum and between the MB tumor and the normal cerebellum were highly consistent, with Pearson correlation coefficients varying from 0.96 to 0.98 within DMRs (Fig. 2C). The hydroxymethylation differences within DHMRs were also very consistent (Fig. 2D). These data strongly suggest that ctDNAs from MB tumors are present in CSF and can be used to faithfully mirror the DNA methylation status of MB tumors in situ.

(A) Top: Venn diagrams of the number of hyper-DMRs (left) or hypo-DMRs (right) identified between cerebellum and MB tumor and between cerebellum and MB CSF. Bottom: Lists of transcription factor (TF) motifs that were enriched within shared hyper-DMRs (left) or hypo-DMRs (right). (B) The same analysis as described in (A) but for hydroxymethylation. (C and D) Scatter plots showing the correlation of differences in 5mC (C) or 5hmC (D) between the normal cerebellum and MB tumor and between cerebellum and MB CSF ctDNA. (E) The genome distributions of shared hyper-DMRs (red) and hypo-DMRs (blue) identified in (A) (left), shared hyper-DHMRs (red) and hypo-DHMRs (blue) identified in (B) (right). The y axes report the percentages of the DMRs or DHMRs relative to all DMRs or DHMRs, respectively. LINE, long interspersed nuclear element; SINE, short interspersed nuclear elements; LTR, long terminal repeat. (F) Multidimensional scaling (MDS) analysis of the 5hmC signals in the shared DHMRs identified in (B). (G) University of California, Santa Cruz (UCSC) genome browser view of 5hmC enrichment at the PRDM6 locus (chr5: 122,433,516 to 122,435,744) in cerebellum, MB tumor, and MB CSF ctDNA. The highlighted region exhibits increased 5hmC in both MB tumor and MB CSF samples.

To evaluate the function of the shared DMRs and DHMRs, we performed motif analysis and identified several neuronal function-associated transcription factor (TF) motifs that were enriched within DMRs and DHMRs, including Oligo2 (33, 38), Atoh1, and NeuroD1 (Fig. 2, A and B, bottom). Analysis using Genomic Regions Enrichment of Annotations Tool further revealed that these common DMRs and DHMRs were mainly enriched at genomic regions that are associated with genes important for cerebellar and CNS functions with particular enrichment in the MB tumor origin Purkinje cellgranule cell precursor cell signaling genes (fig. S3, C and D) (30, 31). Functional genome analysis further unveiled that, compared to hypo-DMRs, hyper-DMRs tend to occur more often at genic regions and distal regulatory regions marked by H3K27ac (Fig. 2E, left). In addition, the DHMRs displayed an enrichment pattern opposite that of the DMRs (Fig. 2E, right). For example, hypo-DHMRs were enriched to a greater degree than were hyper-DHMRs in genic regions (Fig. 2E). These data are consistent with the previously observed lower level of DNA methylation in repetitive regions and higher level of DNA methylation at genic regions in tumor cells.

It has been reported that DNA demethylation is closely associated with MB pathogenesis (12). 5hmC constitutes one of the most important intermediates during active DNA demethylation. We therefore performed multidimensional scaling (MDS) analysis using DHMRs between the normal cerebellum and MB tumors. Normal cerebellum tissues were clearly separated from MB tumor and MB CSF, whereas MB tumor and MB CSF samples were paired by person (Fig. 2F). Note that the tumor and CSF samples for patient 1 were closer to normal cerebellum tissue than to samples of other patients. We also noticed a relatively lower Pearson correlation coefficient of 5hmC analysis between CSF and tumor tissue in patient 1 compared with the two coefficients of other analyzed patients (Figs. 1B and 2B). It might be due to the clinical stage differences between these patients (table S2). However, our overall result indicates that 5hmC signatures obtained from CSF ctDNA can be used to detect MB tumor existence. For example, we observed a marked increase in 5hmC at the PRDM6 locus in both MB tumor and MB CSF compared with normal cerebellum (Fig. 2G). At this location, enhancer hijackingdriven activation of PRDM6 in MB has been reported previously (10). In summary, these analyses show that the identified DMRs and DHMRs are potentially associated with CNS function and that the dysregulation of DNA methylation and hydroxymethylation pathways might be culprits contribute to MB pathogenesis.

Next, we compared DNA methylation and hydroxymethylation differences within the shared DHMRs and DMRs, respectively. For brevity, we define characteristic DMRs (or DHMRs) as the DMRs (or DHMRs), common between normal cerebellum and MB tumor and between normal cerebellum and MB CSF. As sodium bisulfitebased DNA methylation analysis was unable to discriminate between 5hmC and 5mC (32), the identified DMRs might contain the changes of 5hmC. Moreover, since 5hmC is the catalytic product of 5mC, the identified DHMRs might also contain information regarding 5mC alterations. Therefore, we compared the DNA methylation within DHMRs and the genomic distribution of DMRs and DHMRs. We observed that more than half of the characteristic DHMRs (n = 16,017, 51.1% of all CpGs in hyper-DHMRs; n = 567, 56% of all CpGs in hypo-DHMRs) displayed less than 20% difference in DNA methylation ratios in both tumor and CSF compared to normal (fig. S4, A and B). This observation indicates that although the 5hmC signals in characteristic DHMRs are significantly different, more than half of the characteristic DHMRs are not characteristic DMRs, as they do not exhibit large WGBS signal differences in the tumor and CSF simultaneously. Detailed analysis of the WGBS data showed that the DNA methylation ratios of the CpGs in characteristic DHMRs were predominantly near 0.6 to 1.0 in the tumor tissue and CSF (fig. S4, C and D, dashed line). Only a small fraction of characteristic CpGs for hydroxymethylation, specifically, 27% for shared hyper-DHMRs (6.8% + 20.2%) and 10.1% for shared hypo-DHMRs (5.5% + 4.6%), displayed strong (>20%) DNA methylation changes in both tumors and CSF (fig. S4, A to D, solid line). Similarly, very few characteristic DMRs remained as characteristic DHMRs (figs. S4, E and F, and S5, A and B), mostly due to the sparsity of 5hmC. These findings suggest that characteristic DMRs and characteristic DHMRs mark both common and specific genomic regions and are complementary to each other. Both DNA methylation and hydroxymethylation analyses are required to yield a comprehensive picture of DNA modification dynamics in MB tumor and MB CSF.

There were 40,056 hyperdifferentially methylated cytosine (DMC) and 20,498 hypo-DMCs in the DMRs between the normal cerebellum and MB tumor. Among these 60,554 DMCs, 6598 CpG sites were differentially methylated in MB CSF in the same direction of change as in the MB tumor, that is, they paralleled each other, and thus formed shared DMRs between MB CSF and normal cerebellum and between MB tumor and normal cerebellum. We termed these 6598 sites as MB CSF signature CpGs (4253 hypermethylated and 2345 hypomethylated CpGs) in the context of DNA methylation of MB CSF (Fig. 3A). Since these three patients are SHH subtypes, MB CSF signature CpG defined that this way is an abbreviation for MB CSF (SHH) signature CpG. These CpGs are mostly scattered in the genome. When we merged adjacent CpGs if they are separated in less than 300 bp, these signature CpGs formed 705 regions with 2.35 CpGs per region, on average, and 4943 single CpGs. This result indicates that even under very strict criteria for MB CSF signature CpG selection, we observe that some signature CpGs share the same methylation dynamics while they are located in the same genomic locations. The functional genome annotation analysis showed that most of the 6598 CpGs were located in gene-rich regions. Around 50% of hypermethylated CpGs were located in MB tumorspecific H3K27ac-enriched regions (fig. S6A). Consistent with the analysis shown in Fig, 2A, the motifs of TFs that are important for neural function were enriched approximal within 100 bp of these CpGs [NeuroD1 (P = 1 1028), Olig2 (P = 1 1021), Atoh1 (P = 1 1013), Oct6 (P = 1 105), and Pax6 (P = 1 105)]. These data suggested that abnormal DNA methylation is frequently observed in H3K27ac-marked enhancers that are approximal to potential neuron-specific TF binding sites in MB. Next, we measured the DNA methylation of ctDNA purified from nontumor individuals (patients with hydrocephalus) as controls to further validate our results. Since the ctDNA is not detected in the CSF of healthy individuals, we then used the CSF samples from patients with hydrocephalus as surrogate nontumor controls in our study. Among these 6598 MB CSF signature CpGs, by requiring minimum sequencing depth 5, we detected 2027 shared CpGs among all the analyzed samples, including two normal cerebellum tissues, four nontumor CSF samples, three MB tumor tissue samples, and three MB CSF samples (fig. S6B). We next performed MDS analysis using the DNA methylation status of these 2027 common DMCs. We observed distinct separation between normal cerebellum, nontumor CSF, and MB samples (tumor tissue and CSF), whereas we clustered the MB tumor and MB CSF together (Fig. 3B). To further confirm this data, we analyzed the DNA methylation levels of these 2027 common DMCs by integrating with published WGBS datasets in MB tumors. We observed that the DNA methylation level in these CpGs could not only distinguish between MB tumor (CSF and tumor) and nontumor (tissue and CSF) samples but also be able to separate the subtypes of MB tumor (fig. S6C). For example, the DNA methylation levels at NEUROD1, STARD13, and NCOR2 loci were significantly increased in MB tumor tissue and CSF samples compared with the levels in nontumor samples, including cerebellum and CSF samples from patients with hydrocephalus (Fig. 3C and fig. S6D). These data strongly suggest that the signature CpGs and their DNA methylation in MB CSF consistently reflect MB tumor signatures and can be used as a potential CSF biomarker to indicate the presence of MB.

(A) Heatmap representation of DNA methylation levels at MB CSF signature CpGs (n = 6598). (B) MDS analysis of the DNA methylation levels at MB CSF signature CpGs detected in cerebellum (dark green), MB tumor (red), MB CSF (orange), and nontumor CSF (light green). (C) UCSC genome browser view of DNA methylation and hydroxymethylation levels at the NEUROD1 locus (chr2: 182,539,000 to 182,550,000) in the indicated samples. (D) t-distributed stochastic neighbor embedding (t-SNE) analysis of the DNA methylation levels of the common CpG sites between MB CSF signature CpGs and the published DNA methylation array data from approximately 600 patients with MB (8). WNT, purple; SHH, maroon; group 3 (G3), dark blue; group 4 (G4), light blue. (E) Pearson correlation analysis of DNA methylation status of the common CpGs between MB CSF signature CpGs and subtype-specific CpGs identified from public data (20) (n = 1047 CpGs). Top: The methylation status in MB tumor samples. Bottom: the methylation status in MB CSF samples. (F) Heatmap representation of the selected 49 subtype-specific CpGs (of 1047 CpG sites), which exhibited concordant DNA methylation status between the three SHH-subtype MB CSF and MB tumor samples (this study) and public MB tumors data.

To further test whether the signature CpGs could be used to characterize MB subtype, we analyzed the DNA methylation status of the MB CSF signature CpG sites using two public datasets. First, we studied the MB CSF signature CpG sites in the published Illumina HumanMethylation450 BeadChip data, which was obtained from approximately 600 MB patient tumor samples (8). Of the 6598 MB CSF signature CpGs, 4602 CpGs were covered by the array data. The DNA methylation status at these 4602 CpGs clearly identified the MB subtype of the 600 analyzed tumor samples (Fig. 3D). Second, we studied the MB CSF signature CpG sites in published WGBS data collected from pediatric patients with MB (12). As shown in fig. S6E, the four different MB subtypes displayed distinct DNA methylation patterns at the MB CSF signature CpG sites. To further obtain comprehensive MB subtypespecific DNA methylation signatures, we compared our results (Fig. 3A) with subtype-specific CpGs identified from published WGBS datasets (12) and identified 1047 MB subtypespecific CpG sites. By analyzing the DNA methylation levels within these sites in tumor and/or CSF samples collected from four patients with MB, we further confirmed that the DNA methylation status at these 1047 CpG sites could clearly reflect the tumor subtypes (Fig. 3E and fig. S6E). Next, we selected 49 CpGs (of the 1047 CpGs) displaying the most notable subtype-specific DNA methylation signatures in the SHH subtype. As shown in Fig. 3F, the DNA methylation levels at these 49 CpGs were consistent among the MB tumors and CSF in our own study, as well as with the published data from SHH MB tumors (12), but were markedly different from normal cerebellum and other MB tumor subtypes. Our results from the analysis with two large independent datasets converged to indicate that the DNA methylation patterns at MB CSF signature CpG sites can both reflect the presence of an MB tumor and be used to facilitate the identification of MB subtype, making it possible to determine the MB subtype from CSF collection at initial diagnosis and to further guide the treatment.

To further test whether the DNA methylation levels at the MB CSF signature CpG sites could be used to reflect the treatment response and tumor recurrence, we analyzed DNA methylation in CSF collected from two patients (2 and 3) at sequential time points (Fig. 4, A and B). For patient 2, CSF was collected at diagnosis, 10 months (during month 7 of treatment; Fig. 4A, top). We observed dynamic DNA methylation changes at the MB CSF signature CpG sites in CSF collected at different disease statuses (at diagnosis, during treatment, and before recurrence; Fig. 4A, bottom). Among 1106 of 6598 MB CSF signature CpGs, a total of 91 CpG sites (cluster 3) regained DNA methylation during treatment, suggesting that these CpGs can be used to assess treatment responses (Fig. 4A, bottom). We also observed that 88 CpG sites (cluster 4) and 227 CpG sites (clusters 5 and 10) showed a continuous increase and reduction in DNA methylation in the same patient regardless of treatment, suggesting treatment-independent epigenetic patterns associated with MB (Fig. 4A, bottom). For patient 3, CSF was collected at diagnosis, 6 months (start of treatment; Fig. 4B, top). Dynamic DNA methylation changes were also observed at the MB CSF signature CpG sites in CSF collected at different time points. Among 1336 of 6598 MB CSF signature CpGs, a total of 77 CpGs in cluster 6 showed an increase in DNA methylation levels after treatment, which indicates that these CpGs might be related to good treatment responses (Fig. 4B, bottom right). A total of 85 CpGs (cluster 14) exhibited decreased DNA methylation level (similar to normal cerebellum tissue) immediately after treatment. A total of 407 CpGs in clusters 4, 9, 10, and 11 maintained high DNA methylation level in all collected samples, which indicates that these CpGs might represent the malignant progress of tumors. We found that 61 overlapping CpGs, identified by comparing the 203 CpGs in clusters 2 and 5 in patient 3 and the 227 CpGs in clusters 5 and 10 in patient 2, displayed a continuous decrease in DNA methylation regardless of treatment (Fig. 4C). Ten CpGs were found to be overlapping between cluster 4 in patient 2 and clusters 4, 9, 10, and 11 in patient 3, which exhibit high DNA methylation levels in the MB group (tumors and CSFs; 0.8 to 1.0; Fig. 4, A and B) compared with that in normal cerebellums (<0.2). Considering that patients 2 and 3 received similar treatments within a comparable duration of time (table S2), these overlapping CpGs can be used as a confident CpG index to reflect the tumor status.

(A) Top: The timeline for serial CSF collections and CSF cytology results in patient 2. Arrows indicate the time points of CSF sample collection (red arrows, CSF samples used in this study). Bottom: Heatmap representation of DNA methylation status of MB CSF (SHH) signature CpGs in normal cerebellum tissues, MB tumor tissue, and CSF at diagnosis, during treatment. (B) Top: The timeline for serial CSF collections and CSF cytology results in patient 3. Bottom: Heatmap representation of DNA methylation levels of MB CSF (SHH) signature CpGs in normal cerebellum tissues, MB tumor tissue, and CSF at diagnosis and during treatment. (C) The Venn diagram representation of overlapped CpGs between clusters 5 and 10 (patient 2) and clusters 2 and 5 (patient 3) and between cluster 4 (patient 2) and clusters 4, 9, 10, and 11 (patient 3). (D) Top: The timeline for serial CSF collections and CSF cytology results in patient 4. Bottom: Heatmap representation of DNA methylation status of MB CSF (WNT) signature CpGs in normal cerebellum tissues, MB tumor tissue from patient 4, published MB (WNT) tumors, and CSF from patient 4 at diagnosis and after treatment.

In parallel, we also analyzed the DNA methylation in ctDNA purified from serial CSF samples obtained from patient 4 (WNT subtype). Consistent with our analysis, we observed a significant difference in DNA methylation between SHH and WNT tumor subtypes (fig. S7A). Since there is no matched MB tumor sample from patient 4, we compared public WGBS data from five WNT-subtype MB tumors (20) with the WGBS data from the CSF sample of patient 4 (collected at diagnosis; fig. S7B). Using the similar method for identification of MB CSF (SHH) signature CpGs, we identified 9373 MB CSF (WNT) signature CpGs that showed distinct DNA methylation levels in both WNT MB tumor and CSF compared with normal cerebellum (fig. S7C). A total of 146 CpGs were found to overlap between MB CSF (SHH) and MB CSF (WNT) signature CpGs, and the majority displayed higher DNA methylation compared with normal cerebellum (table S4 and fig. S7, D and E). We also measured the DNA methylation in ctDNA purified from serial CSF samples in patient 4 (at diagnosis, 19 months and 29 months after diagnosis without recurrence; Fig. 4D, top). Within MB CSF (WNT) signature CpGs (n = 9373), we observed 1632 CpGs exhibiting dynamic DNA methylation changes along the treatment (Fig. 4D, bottom). Specifically, DNA methylation levels of CpGs in cluster 9 dropped from 85 to 10% after treatment (both at 19th and 29th month after initial diagnosis), which was comparable to the level in normal cerebellum. For CpGs in cluster 3, their DNA methylation showed dynamic changes at 19th and 29th month (from 10 to 95%). For CpGs in clusters 1, 2, and 4, these CpGs exhibited high DNA methylation levels (>80%) in tumors, CSFs, and two surveillance samples, whereas CpGs in cluster 5 had a low DNA methylation level (<20%) (Fig. 4D, bottom). Notably, the cytology analysis results of most CSF samples in this study remained negative. However, we were able to detect and analyze DNA methylation in CSF ctDNA from these patients. Furthermore, we detected strong subtype-specific DNA methylation signatures at different disease stages in patients with MB, suggesting a high sensitivity and reliability of this method. These data clearly establish that the DNA methylation status of MB CSF signature CpG sites can be exploited to identify MB subtype and monitor disease progression (e.g., treatment response and recurrence).

To further test whether the DNA methylation of MB signature CpGs in CSF could be used as potential prognostic markers, we performed a univariate Cox proportional hazard analysis for the MB CSF (SHH) signature CpGs (Fig. 4A) and the information about overall survival (OS) from a previous study (8). We identified 224 probes that were significantly associated (P < 0.001) with the OS of patients with MB (table S3). For example, as shown in Fig. 5A, one CpG site (cg14582550; chr9: 97,786,878 to 97,786,879) located within the intron of C9orf3 displayed a marked increase in DNA methylation in MB samples (both tumor and CSF ctDNA) in our study, which was concordant with earlier reports (8, 12, 33) that used Illumina HumanMethylation450 BeadChip (Fig. 5, B and C). By associating the DNA methylation status at this CpG site with patient survival information, we found that patients with a high DNA methylation level (>0.8) at this CpG site showed significantly (P < 0.0001) lower survival rates compared with patients with a low DNA methylation level (0.8) at this site (Fig. 5D). We further examined the DNA methylation level of seven probes covering the gene body of C9orf3 (three probes up- and downstream of probe cg14582550, respectively) and observed consistent survival rates as using the single probe cg14582550 (fig. S7F). Next, we randomly selected 438 and 189 patients as training and validation data, respectively (8). By applying multivariate Cox regression analysis using MB signature CpGs on the training data, we selected the best linear model with the smallest root mean square error in the training set from models comprising all possible combinations of two to five CpG sites using a stepwise regression method. The best linear model is Y (survival score) = 2.343 + mCG/CG ratio of CpG#1 (cg27490391) * 3.528 + mCG/CG ratio of CpG#2 (cg27579805) * 1.598 + mCG/CG ratio of CpG#3(cg27638288) * (0.771). The probe cg27490391 located on the gene body of LHFP, probe cg27579805 located at the 3 untranslated region of TNRC6C, and probe cg27638288 located in nongenetic region. These three CpG sites displayed significantly increased DNA methylation in MB tumors compared with normal cerebellum (fig. S7G). We then calculated survival scores using this formula for each patient in the training dataset (n = 438). The patients could be clearly separated into low- and high-risk groups based on the medium survival score. The patients with high-survival scores had a significantly better outcomes than those with low-survival scores in both training and validation datasets (Fig. 5, E and F). In summary, our data clearly demonstrate that DNA methylation status at MB CSF signature CpG sites can be used as potential prognostic markers to predict the clinical outcomes of patients with MB.

(A) UCSC genome browser view showing DNA methylation and hydroxymethylation levels of CpGs (chr9: 97,786,878 to 97,786,879) located within the intron of C9orf3 for normal cerebellum, nontumor CSF, MB CSF ctDNA, and MB tumors, including data from this study and 34 public WGBS datasets (12). (B and C) Box plots representing the DNA methylation levels at the single CpG site highlighted in Fig. 4A, using previously published DNA methylation array data [B (8) and C (41)]. (D) Kaplan-Meier survival curves of patients with MB separated according to a methylation ratio cutoff value of 80% at the single CpG site highlighted in Fig. 4A. (E and F) Kalan-Meier curves and log-rank tests were used to visualize and compare the OS between low-risk and high-risk groups in the training cohort (n = 438 patients) (E) and the validation cohort (n = 189) (F) using the methylation ratios at the three CpGs in the model.

The detection of ctDNA from the plasma of patients with cancer was reported previously; however, it is not suitable for patients with brain tumor because the ctDNA from the brain tumor might be blocked by blood-brain barrier (34). CSF is in constant and intimate contact with brain malignancies and has been reported to contain ctDNA (35). CSF might therefore serve as a better source than plasma for obtaining ctDNA for real-time monitoring of disease progression and response to treatment (23). Until now, most CSF ctDNA analyses have been geared toward the detection of cancer-associated mutations (2224, 36). However, pediatric brain tumors have much lower frequencies of mutations compared to adult brain tumors (6), making the detection of tumor DNA via mutational analysis difficult. In contrast, alterations in epigenetic landscapes have been frequently observed in pediatric brain tumors (9, 12, 33, 37), making epigenetic markers a more ideal readout for diagnostic and prognostic purposes. We reason that epigenetic signatures inherent to the brain tumors in situ will be preserved in CSF ctDNA. Therefore, measuring the epigenetic signatures from CSF ctDNA could be a sensitive and accurate approach to monitoring brain tumor treatment response, progression, and relapse.

In this study, we profiled epigenetic markers, including DNA methylation and hydroxymethylation, in CSF ctDNA genome widely from pediatric patients with MB. We have shown that these two epigenetic markers can be detected in ctDNA extracted from MB CSF with an input volume as low as 200 l. Since our CSF samples were immediately subjected to hard spins after collection, it is less likely that the purified DNA in CSF is from genomic DNA (gDNA) in circulating tumor or nontumor cells in CSF. Note that the DNA purified from MB tumor tissue and CSF displayed similar epigenetic signatures in the same patients, suggesting that DNA purified from CSF in patients with MB according to our protocols is mainly derived from MB tumor. However, during the analysis, we encountered low genomic coverage or relatively low bisulfite conversion efficiency in some samples. We only recovered 16 M CpGs in the MB CSF sample collected from patient 3 after treatment, although we sequenced ~1.5 billion total reads in this sample. During the analysis, there are only 116 million uniquely mapped reads after duplication removal, suggesting that most reads are from the same genomic regions and the original ctDNA might have relatively low genomic coverage. Both samples were collected from patients after chemotherapy treatment (table S2). It is possible that the chemotherapy might introduce DNA damage and perturb bisulfite conversion. Further analysis is needed to clarify this point. We have excluded these samples in this analysis due to the low data quality. On the basis of these analyses, not all the CSF samples are suitable for using 200 l of CSF for DNA methylation and hydroxymethylation analysis. With samples that have low genomic coverage and possible DNA damage, it is most ideal to increase the input volume of CSF samples to avoid potential analysis bias. Regardless of these caveats, the ctDNA methylation and hydroxymethylation patterns match those of MB tumor tissues from the same patient, suggesting that CSF ctDNA can be used as material to monitor MB progression.

One point that needs to be noted is that the changes of DNA methylation level have been reported during aging (38). The MB samples used in this study had an age of <18 years old, and the nontumor CSF samples were from individuals with ages ranging from 32 to 66 years old (table S2). To test whether the DNA methylation changes within the MB signature CpGs were due to the age difference in Fig. 3B and fig. S6C, we monitored the DNA methylation level within these CpGs using published WGBS data from normal human brain tissues of ages ranging from 35 days to 55 years old (38). No differential DNA methylation was observed within these MB signature CpGs at different ages (fig. S7H), which rules out the possible influence of aging-associated DNA methylation changes at these CpG sites.

One limitation in our study is that the sample size is relatively small. In our analysis, we observed large intertumor heterogeneity based on DNA methylation analysis (Fig. 2F), suggesting that large sample size is preferred to obtain more reliable DNA methylation signatures. Nonetheless, even with the limited sample size, we were able to identify DNA methylation signature CpGs in CSF. We further validated our results using published datasets collected from more than 600 patients with MB, suggesting that our discovery could be widely applied to identify and classify patients with MB. In addition, the DNA methylation status at subsets of MB signature CpGs in CSF samples collected at different time points from the same patient reflected the tumor status during treatment and recurrence even in cytogenic negative samples, suggesting that our approach has superior sensitivity and high specificity. DNA methylation and hydroxymethylation at these CpG sites could be used as prognostic markers to stratify patients with MB into low- and high-risk groups. We did observe some variations in epigenetic markers in CSF ctDNA among patients with MB, which might be due to differences in sample collection times (e.g., before or after surgery and treatment) or the fact that the patients had MB belonging to different subgroups (22) or different stages. Further studies with a larger MB sample size could be used to refine the results from this study.

Overall, DNA methylation and hydroxymethylation signatures in CSF ctDNA can serve as valuable epigenetic markers to guide the clinical management of patients with MB. The epigenetic features detected in CSF ctDNA can be exploited for previously unidentified biomarker and prognostic marker development. Our method using extremely low input DNA to accurately profile DNA methylation and DNA hydroxymethylation genome widely in ctDNA represents a proof of concept for its use in other tumors beyond MB.

Signed informed consent was obtained from the patients or their legal guardians before sample acquisition in accordance with an institutional review boardapproved protocol. Freshly resected MB tumor specimens from three patients undergoing surgery at Texas Childrens Hospital were obtained for this study. Multiple CSF samples were collected during clinically indicated LPs. All samples were subjected to pathological diagnosis and were graded according to the World Health Organization system. Tumor tissues were snap-frozen in liquid nitrogen and preserved in a 80C freezer. CSF was processed using a standardized protocol, then divided into aliquots, and stored immediately in a 80C freezer.

Freshly collected CSF samples were centrifuged at 1000g for 10 min before frozen in 80C as described previously (36, 39). A total of 200 to 400 l of CSF recovered from freezer was either directly subjected to centrifugation at 1000g at 4C for 10 min before ctDNA purification or directly subjected to DNA purification without centrifugation. Cell-free DNA was purified from 200 to 400 l of CSF using the QIAamp Circulating Nucleic Acid Kit (QIAGEN) according to the manufacturers instructions. For MB tumor tissues, as much as 20 mg of tumor tissue was snap-frozen with liquid nitrogen and ground. DNA was then isolated using the AllPrep DNA/RNA Mini Kit (QIAGEN) according to the manufacturers protocol. The concentration of the isolated DNA was measured by a Qubit 4 Fluorometer with the Qubit dsDNA (double-stranded DNA) High-Sensitivity Assay Kit (Thermo Fisher Scientific).

WGBS analysis was used to measure the genome-wide DNA methylation profile. The ctDNA and tissue WGBS libraries were generated using the Pico Methyl-Seq Library Prep Kit (Zymo Research). Briefly, ctDNA was mixed with 0.1% unmethylated -bacteriophage DNA (w/w) (New England Biolabs), followed by sodium bisulfite conversion. The bisulfite-converted DNA was then annealed with random primers for initial amplification, followed by adaptor ligation and final amplification with Illumina TruSeq indices. Constructed libraries were run on a 2% agarose gel to assess size distribution, and the library concentration was measured by a Qubit 4 Fluorometer with the Qubit dsDNA High-Sensitivity Assay Kit. Normalized libraries were then pooled at an equimolar ratio and sequenced on a NextSeq 500 (Illumina) with a NextSeq 500/550 High Output Kit v2.5 (single-end reads, 75 cycles) according to the manufacturers protocols.

CMS-IPseq was performed as described previously with some modifications. Briefly, purified MB tumor gDNA was sonicated to the 200- to 400-bp size range using an M220 Focused-ultrasonicator (Covaris). The CSF ctDNA was directly treated with sodium bisulfite without sonication. The sheared gDNA and purified ctDNA were treated with sodium bisulfite using the EZ DNA Methylation-Lightning Kit (Zymo Research) with the manufacturers protocols to convert 5hmC to CMS. Next, CMS-containing DNA fragments were immunoprecipitated using a CMS-specific antiserum conjugated to Protein A/G Dynabeads. Enriched DNA fragments were purified using conventional phenol/chloroform/isomyl-alcohol extraction and then amplified with random primers, followed by adaptor ligation and final amplification with Illumina TruSeq index using the Pico Methyl-Seq Library Prep Kit (Zymo Research). DNA library sizes and concentrations were verified by Bioanalyzer. The DNA libraries were then sequenced in NextSeq 500 (Illumina) with the NextSeq 500/550 High Output Kit v2.5 (single-end reads, 75 cycles) following the manufacturers protocols.

For WGBS analysis, raw FASTQ files were mapped to the National Center for Biotechnology Information Human Reference Genome Build GRCh37 (hg19) using BSMAP (40) and LiBis (28). LiBis used a dynamic clipping method to rescue the unmapped reads. For each unmapped read, LiBis generated 40-bp (user defined) segments with a 5-bp (user defined) space (see workflow figure in https://github.com/Dangertrip/LiBis). One unmapped read became several 40-bp small fragments. Then, these small 40-bp fragments were remapped, and only the uniquely mapped reads were kept. Next, LiBis extended these uniquely mapped small fragments based on their mapping locations in the genome. The final step was to filter out the shorter extended fragments (<50 bp). The longer extended fragments (>50 bp) were counted as the highly confident rescued reads. The polymerase chain reaction duplicates were removed using Picard MarkDuplicates (http://broadinstitute.github.io/picard/). The MCALL module in MOABS was used to calculate the DNA methylation ratio and coverage for each CpG site. Differentially methylated CpGs and regions were identified using the MCOMP module considering variance among samples (--withVariance 1) in the MOABS software. Bisulfite conversion efficiencies were estimated using spike-in unmethylated -bacteriophage DNA. The output bedGraph files from MCALL include single-base resolution DNA methylation ratios, which were transformed to a bigWig file format. The bigWig files were uploaded to the University of California, Santa Cruz (UCSC) genome browser for visualization.

For CMS-IPseq analysis, we used the CMS-IP software to detect DHMRs between normal cerebellum samples and MB tumor or CSF samples (https://github.com/lijinbio/cmsip). Raw CMS-IPseq reads were aligned to hg19 using BSMAP (40). Uniquely mapped reads were retained for downstream analysis. Size factor estimation normalized the total WIG file sums of sample replicates. A CMS count table was tabulated for the 5hmC-enriched regions detected by MACS2. Adjusting for the estimated size factors, the normalized CMS count table was tested by the G test of goodness of fit. The G test examines whether the sums of counts fit the proportion of the numbers of replicates between two samples. CMS-IP calls the G.test() function in the R package RVAideMemoire. CMS-IP computes false discovery rate (FDR)adjusted q values of the P values in G test using the Benjamini and Hochberg procedure. To reduce the loss of statistical power caused by the FDR adjustment, independent filtering is applied to rule out low-count regions, where the filtering criterion measures the average normalized CMS counts across sample replicates. DHMRs were identified by a q < 0.05. To facilitate the visualization of 5hmC signals, bigWig files for read coverage were generated from the aligned BAM files and visualized in the UCSC genome browser.

The smoothed scatterplots (R package: geneplotter) used the common CpGs or common 5hmC-enriched regions between two samples as input. Pearson correlations coefficients were calculated using the R cor function. The R package ggplot2 was used to plot violin plots and box plots. Heatmaps were plotted using the R package heatmap3 (www.rdocumentation.org/packages/heatmap3/versions/1.1.6/topics/heatmap3) by taking the CpGs shared among all samples as input. t-distributed stochastic neighbor embedding (t-SNE) analysis was performed using the R package Rtsne (https://github.com/jkrijthe/Rtsne).

We downloaded the DNA methylation 450k array data and clinical data from dataset GSE65362 (>600 patients with MB). We randomly selected 438 and 189 patients as the training dataset and the validation dataset, respectively. OS was defined as the time from the patient diagnosis to MB tumorrelated death or last follow-up. To reduce noise, we first performed univariate Cox proportional hazard analysis in the training dataset to identify the CpGs significantly associated (P < 0.001) with OS. Among these CpGs, we only used those CpGs that were identified as candidate markers for prognostic evaluation both in DMC comparisons between normal cerebellum and MB tumors and DMC comparisons between normal cerebellum and MB CSF ctDNA. These candidate markers were then used in multivariate Cox regression analysis to construct linear models comprising all possible combinations of two to five markers. The best linear model was Y = 2.343 + mCG/CG ratio of cg27490391 * 3.528 + mCG/CG ratio of cg27579805 * 1.598 + mCG/CG ratio of cg27638288 * (0.771). We use the above formula to estimate a survival score for each patient. We then separated patients into two groups, survival good and survival bad, based on the median values of the survival scores. Next, the R package survival was used to draw Kaplan-Meier survival curves. The log rank test was used to assess the difference in OS between the two groups.

Acknowledgments: Funding: We are grateful to J. Shen, the MD Anderson Cancer Center Next-Generation Sequencing Core at Smithville (CPRIT RP120348 and RP170002), and the Texas A&M Institute of Biosciences and Technology Epigenetics Core. This work was supported by grants from the Cancer Prevention and Research Institute of Texas (RR140053 to Y.H., RP170660 to Y.Z., and RP180131 to D.S.), the NIH (R01HL134780 and R01HL146852 to Y.H. and R01GM112003 to Y.Z.), the Welch Foundation (BE-1913-20190330 to Y.Z.), the American Cancer Society (RSG-18-043-01-LIB to Y.H. and RSG-16-215-01-TBE to Y.Z.), and by start-up funds from the Texas A&M University (to Y.H. and D.S.). Author contributions: X.-N.L., Y.H., and D.S. directed and oversaw the project. Jia Li and D.S. performed comprehensive bioinformatics analyses, including data quality control, publicly available data collection, integration analysis, and identification of the CpGs potentially associated with patient outcome. M.L. optimized CSF ctDNA sequencing library preparation and performed high-throughput sequencing. S.Z. and X.-N.L. collected and identified CSF and tumor samples. L.Y.B., Y.E., R.H.D., P.J.A.D., and D.W.P. provided intellectual input. Y.H. and Y.Z. wrote the manuscript, and all authors participated in discussion, data interpretation, and manuscript editing. Competing interests: J.L., S.B.Z., Y.H., X.-N.L., and D.S. are co-inventors on a pending patent application related to this work filed by Texas A&M University. The other authors declare no other competing interests. Data and materials availability: Raw and processed data are available at the Gene Expression Omnibus database under accession number GSE142241. All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors.

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Reliable tumor detection by whole-genome methylation sequencing of cell-free DNA in cerebrospinal fluid of pediatric medulloblastoma - Science...

When Ralph Fisher, a Texas cattle rancher, set eyes on one of the world's first cloned calves in August 1999, he didn't care what the scientists said: He knew it was his old Brahman bull, Chance, born again. About a year earlier, veterinarians at Texas A&M extracted DNA from one of Chance's moles and used the sample to create a genetic double. Chance didn't live to meet his second self, but when the calf was born, Fisher christened him Second Chance, convinced he was the same animal.

Scientists cautioned Fisher that clones are more like twins than carbon copies: The two may act or even look different from one another. But as far as Fisher was concerned, Second Chance was Chance. Not only did they look identical from a certain distance, they behaved the same way as well. They ate with the same odd mannerisms; laid in the same spot in the yard. But in 2003, Second Chance attacked Fisher and tried to gore him with his horns. About 18 months later, the bull tossed Fisher into the air like an inconvenience and rammed him into the fence. Despite 80 stitches and a torn scrotum, Fisher resisted the idea that Second Chance was unlike his tame namesake, telling the radio program "This American Life" that "I forgive him, you know?"

In the two decades since Second Chance marked a genetic engineering milestone, cattle have secured a place on the front lines of biotechnology research. Today, scientists around the world are using cutting-edge technologies, from subcutaneous biosensors to specialized food supplements, in an effort to improve safety and efficiency within the $385 billion global cattle meat industry. Beyond boosting profits, their efforts are driven by an imminent climate crisis, in which cattle play a significant role, and growing concern for livestock welfare among consumers.

Gene editing stands out as the most revolutionary of these technologies. Although gene-edited cattle have yet to be granted approval for human consumption, researchers say tools like Crispr-Cas9 could let them improve on conventional breeding practices and create cows that are healthier, meatier, and less detrimental to the environment. Cows are also being given genes from the human immune system to create antibodies in the fight against Covid-19. (The genes of non-bovine livestock such as pigs and goats, meanwhile, have been hacked to grow transplantable human organs and produce cancer drugs in their milk.)

But some experts worry biotech cattle may never make it out of the barn. For one thing, there's the optics issue: Gene editing tends to grab headlines for its role in controversial research and biotech blunders. Crispr-Cas9 is often celebrated for its potential to alter the blueprint of life, but that enormous promise can become a liability in the hands of rogue and unscrupulous researchers, tempting regulatory agencies to toughen restrictions on the technology's use. And it's unclear how eager the public will be to buy beef from gene-edited animals. So the question isn't just if the technology will work in developing supercharged cattle, but whether consumers and regulators will support it.

* * *

Cattle are catalysts for climate change. Livestock account for an estimated 14.5 percent of greenhouse gas emissions from human activities, of which cattle are responsible for about two thirds, according to the United Nations' Food and Agriculture Organization (FAO). One simple way to address the issue is to eat less meat. But meat consumption is expected to increase along with global population and average income. A 2012 report by the FAO projected that meat production will increase by 76 percent by 2050, as beef consumption increases by 1.2 percent annually. And the United States is projected to set a record for beef production in 2021, according to the Department of Agriculture.

For Alison Van Eenennaam, an animal geneticist at the University of California, Davis, part of the answer is creating more efficient cattle that rely on fewer resources. According to Van Eenennaam, the number of dairy cows in the United States decreased from around 25 million in the 1940s to around 9 million in 2007, while milk production has increased by nearly 60 percent. Van Eenennaam credits this boost in productivity to conventional selective breeding.

"You don't need to be a rocket scientist or even a mathematician to figure out that the environmental footprint or the greenhouse gases associated with a glass of milk today is about one-third of that associated with a glass of milk in the 1940s," she says. "Anything you can do to accelerate the rate of conventional breeding is going to reduce the environmental footprint of a glass of milk or a pound of meat."

Modern gene-editing tools may fuel that acceleration. By making precise cuts to DNA, geneticists insert or remove naturally occurring genes associated with specific traits. Some experts insist that gene editing has the potential to spark a new food revolution.

Jon Oatley, a reproductive biologist at Washington State University, wants to use Crispr-Cas9 to fine tune the genetic code of rugged, disease-resistant, and heat-tolerant bulls that have been bred to thrive on the open range. By disabling a gene called NANOS2, he says he aims to "eliminate the capacity for a bull to make his own sperm," turning the recipient into a surrogate for sperm-producing stem cells from more productive prized stock. These surrogate sires, equipped with sperm from prize bulls, would then be released into range herds that are often genetically isolated and difficult to access, and the premium genes would then be transmitted to their offspring.

Furthermore, surrogate sires would enable ranchers to introduce desired traits without having to wrangle their herd into one place for artificial insemination, says Oatley. He envisions the gene-edited bulls serving herds in tropical regions like Brazil, the world's largest beef exporter and home to around 200 million of the approximately 1.5 billion head of cattle on Earth.

Brazil's herds are dominated by Nelore, a hardy breed that lacks the carcass and meat quality of breeds like Angus but can withstand high heat and humidity. Put an Angus bull on a tropical pasture and "he's probably going to last maybe a month before he succumbs to the environment," says Oatley, while a Nelore bull carrying Angus sperm would have no problem with the climate.

The goal, according to Oatley, is to introduce genes from beefier bulls into these less efficient herds, increasing their productivity and decreasing their overall impact on the environment. "We have shrinking resources," he says, and need new, innovative strategies for making those limited resources last.

Oatley has demonstrated his technique in mice but faces challenges with livestock. For starters, disabling NANOS2 does not definitively prevent the surrogate bull from producing some of its own sperm. And while Oatley has shown he can transplant sperm-producing cells into surrogate livestock, researchers have not yet published evidence showing that the surrogates produce enough quality sperm to support natural fertilization. "How many cells will you need to make this bull actually fertile?" asks Ina Dobrinski, a reproductive biologist at the University of Calgary who helped pioneer germ cell transplantation in large animals.

But Oatley's greatest challenge may be one shared with others in the bioengineered cattle industry: overcoming regulatory restrictions and societal suspicion. Surrogate sires would be classified as gene-edited animals by the Food and Drug Administration, meaning they'd face a rigorous approval process before their offspring could be sold for human consumption. But Oatley maintains that if his method is successful, the sperm itself would not be gene-edited, nor would the resulting offspring. The only gene-edited specimens would be the surrogate sires, which act like vessels in which the elite sperm travel.

Even so, says Dobrinski, "That's a very detailed difference and I'm not sure how that will work with regulatory and consumer acceptance."

In fact, American attitudes towards gene editing have been generally positive when the modification is in the interest of animal welfare. Many dairy farmers prefer hornless cows horns can inflict damage when wielded by 1,500-pound animals so they often burn them off in a painful process using corrosive chemicals and scalding irons. In a study published last year in the journal PLOS One, researchers found that "most Americans are willing to consume food products from cows genetically modified to be hornless."

Still, experts say several high-profile gene-editing failures in livestock and humans in recent years may lead consumers to consider new biotechnologies to be dangerous and unwieldy.

In 2014, a Minnesota startup called Recombinetics, a company with which Van Eenennaam's lab has collaborated, created a pair of cross-bred Holstein bulls using the gene-editing tool TALENs, a precursor to Crispr-Cas9, making cuts to the bovine DNA and altering the genes to prevent the bulls from growing horns. Holstein cattle, which almost always carry horned genes, are highly productive dairy cows, so using conventional breeding to introduce hornless genes from less productive breeds can compromise the Holstein's productivity. Gene editing offered a chance to introduce only the genes Recombinetics wanted. Their hope was to use this experiment to prove that milk from the bulls' female progeny was nutritionally equivalent to milk from non-edited stock. Such results could inform future efforts to make Holsteins hornless but no less productive.

The experiment seemed to work. In 2015, Buri and Spotigy were born. Over the next few years, the breakthrough received widespread media coverage, and when Buri's hornless descendant graced the cover of Wired magazine in April 2019, it did so as the ostensible face of the livestock industry's future.

But early last year, a bioinformatician at the FDA ran a test on Buri's genome and discovered an unexpected sliver of genetic code that didn't belong. Traces of bacterial DNA called a plasmid, which Recombinetics used to edit the bull's genome, had stayed behind in the editing process, carrying genes linked to antibiotic resistance in bacteria. After the agency published its findings, the media reaction was swift and fierce: "FDA finds a surprise in gene-edited cattle: antibiotic-resistant, non-bovine DNA," read one headline. "Part cow, part bacterium?" read another.

Recombinetics has since insisted that the leftover plasmid DNA was likely harmless and stressed that this sort of genetic slipup is not uncommon.

"Is there any risk with the plasmid? I would say there's none,'' says Tad Sonstegard, president and CEO of Acceligen, a Recombinetics subsidiary. "We eat plasmids all the time, and we're filled with microorganisms in our body that have plasmids." In hindsight, Sonstegard says his team's only mistake was not properly screening for the plasmid to begin with.

While the presence of antibiotic-resistant plasmid genes in beef probably does not pose a direct threat to consumers, according to Jennifer Kuzma, a professor of science and technology policy and co-director of the Genetic Engineering and Society Center at North Carolina State University, it does raise the possible risk of introducing antibiotic-resistant genes into the microflora of people's digestive systems. Although unlikely, organisms in the gut could integrate those genes into their own DNA and, as a result, proliferate antibiotic resistance, making it more difficult to fight off bacterial diseases.

"The lesson that I think is learned there is that science is never 100 percent certain, and that when you're doing a risk assessment, having some humility in your technology product is important, because you never know what you're going to discover further down the road," she says. In the case of Recombinetics. "I don't think there was any ill intent on the part of the researchers, but sometimes being very optimistic about your technology and enthusiastic about it causes you to have blinders on when it comes to risk assessment."

The FDA eventually clarified its results, insisting that the study was meant only to publicize the presence of the plasmid, not to suggest the bacterial DNA was necessarily dangerous. Nonetheless, the damage was done. As a result of the blunder,a plan was quashed forRecombinetics to raise an experimental herd in Brazil.

Backlash to the FDA study exposed a fundamental disagreement between the agency and livestock biotechnologists. Scientists like Van Eenennaam, who in 2017 received a $500,000 grant from the Department of Agriculture to study Buri's progeny, disagree with the FDA's strict regulatory approach to gene-edited animals. Typical GMOs are transgenic, meaning they have genes from multiple different species, but modern gene-editing techniques allow scientists to stay roughly within the confines of conventional breeding, adding and removing traits that naturally occur within the species. That said, gene editing is not yet free from errors and sometimes intended changes result in unintended alterations, notes Heather Lombardi, division director of animal bioengineering and cellular therapies at the FDA's Center for Veterinary Medicine. For that reason, the FDA remains cautious.

"There's a lot out there that I think is still unknown in terms of unintended consequences associated with using genome-editing technology," says Lombardi. "We're just trying to get an understanding of what the potential impact is, if any, on safety."

Bhanu Telugu, an animal scientist at the University of Maryland and president and chief science officer at the agriculture technology startup RenOVAte Biosciences, worries that biotech companies will migrate their experiments to countries with looser regulatory environments. Perhaps more pressingly, he says strict regulation requiring long and expensive approval processes may incentivize these companies to work only on traits that are most profitable, rather than those that may have the greatest benefit for livestock and society, such as animal well-being and the environment.

"What company would be willing to spend $20 million on potentially alleviating heat stress at this point?" he asks.

* * *

On a windy winter afternoon, Raluca Mateescu leaned against a fence post at the University of Florida's Beef Teaching Unit while a Brahman heifer sniffed inquisitively at the air and reached out its tongue in search of unseen food. Since 2017, Mateescu, an animal geneticist at the university, has been part of a team studying heat and humidity tolerance in breeds like Brahman and Brangus (a mix between Brahman and Angus cattle). Her aim is to identify the genetic markers that contribute to a breed's climate resilience, markers that might lead to more precise breeding and gene-editing practices.

"In the South,'' Mateescu says, heat and humidity are a major problem. "That poses a stress to the animals because they're selected for intense production to produce milk or grow fast and produce a lot of muscle and fat."

Like Nelore cattle in South America, Brahman are well-suited for tropical and subtropical climates, but their high tolerance for heat and humidity comes at the cost of lower meat quality than other breeds. Mateescu and her team have examined skin biopsies and found that relatively large sweat glands allow Brahman to better regulate their internal body temperature. With funding from the USDA's National Institute of Food and Agriculture, the researchers now plan to identify specific genetic markers that correlate with tolerance to tropical conditions.

"If we're selecting for animals that produce more without having a way to cool off, we're going to run into trouble," she says.

There are other avenues in biotechnology beyond gene editing that may help reduce the cattle industry's footprint. Although still early in their development, lab-cultured meats may someday undermine today's beef producers by offering consumers an affordable alternative to the conventionally grown product, without the animal welfare and environmental concerns that arise from eating beef harvested from a carcass.

Other biotech techniques hope to improve the beef industry without displacing it. In Switzerland, scientists at a startup called Mootral are experimenting with a garlic-based food supplement designed to alter the bovine digestive makeup to reduce the amount of methane they emit. Studies have shown the product to reduce methane emissions by about 20 percent in meat cattle, according to The New York Times.

In order to adhere to the Paris climate agreement, Mootral's owner, Thomas Hafner, believes demand will grow as governments require methane reductions from their livestock producers. "We are working from the assumption that down the line every cow will be regulated to be on a methane reducer," he told The New York Times.

Meanwhile, a farm science research institute in New Zealand, AgResearch, hopes to target methane production at its source by eliminating methanogens, the microbes thought to be responsible for producing the greenhouse gas in ruminants. The AgResearch team is attempting to develop a vaccine to alter the cattle gut's microbial composition, according to the BBC.

Genomic testing may also allow cattle producers to see what genes calves carry before they're born, according to Mateescu, enabling producers to make smarter breeding decisions and select for the most desirable traits, whether it be heat tolerance, disease resistance, or carcass weight.

Despite all these efforts, questions remain as to whether biotech can ever dramatically reduce the industry's emissions or afford humane treatment to captive animals in resource-intensive operations. To many of the industry's critics, including environmental and animal rights activists, the very nature of the practice of rearing livestock for human consumption erodes the noble goal of sustainable food production. Rather than revamp the industry, these critics suggest alternatives such as meat-free diets to fulfill our need for protein. Indeed, data suggests many young consumers are already incorporating plant-based meats into their meals.

Ultimately, though, climate change may be the most pressing issue facing the cattle industry, according to Telugu of the University of Maryland, which received a grant from the Bill and Melinda Gates Foundation to improve productivity and adaptability in African cattle. "We cannot breed our way out of this," he says.

* * *

Dyllan Furness is a Florida-based science and technology journalist. His work has appeared in Quartz, OneZero, and PBS, among other outlets.

This article was originally published on Undark. Read the original article.

See more here:
Biotechnology could change the cattle industry. Will it succeed? - Salon

Advantages of Umbilical Cord Stem Cells

Anyone can be treated since Mesenchymal Stem Cells (MSCs) are immune system privileged. No blood matchingnecessary.

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Ethical issues are avoided.

(All umbilical cords are donated by mothers who gave birth tohealthy, live babies)

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Harvesting process is painless.

(No need to collect stem cells through invasive procedures such as liposuction or bone marrow collection)

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Differentiation potential is broad.

(Stem cells an be integrated into any cell. IE: heart, skin, nerve, muscle, etc...)

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Self-renewal with rapid doubling time.

(Approx. 40 hours per cycle)

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BEST anti-inflammatory activity, immune modulating capacity and ability to stimulateregeneration.

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Can be administered multiple times in uniform dosages that contain high cell counts.

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Immunogenicity (allergic reaction) is low.

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Tumor growth has NOT been detected.

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Human Umbilical Cord Tissue (HUCT) contains an abundant supply of MSCs.

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HUCT MSCs proliferate/differentiate moreefficientlythan other types of stem cells and therefore considered to be more potent.

Continued here:
STEM CELLS | VitaDrip IV Therapy | Texas

Research Presented at 2020 AACR Virtual Annual Meeting

The Triple I/O Combination of Plinabulin, Anti-PD-1 and Radiation Achieved a 100 Percent Complete Response in Anti-PD-1 Non-responsive Animal Model

Triple I/O Combination to Be Administered to Patients Who Failed I/O in Second Half of 2020

NEW YORK, June 23, 2020 (GLOBE NEWSWIRE) -- BeyondSpring Inc. (the Company or BeyondSpring) (NASDAQ: BYSI), a global biopharmaceutical company focused on the development of innovative immuno-oncology (I/O) therapies, today announced new preclinical research findings that indicate BeyondSprings lead asset, Plinabulin, enhances immuno-radiotherapy for cancer patients. The results of this preclinical study was highlighted in a poster presentation titled, Plinabulin, a microtubule destabilizing agent, improves tumor control by enhancing dendritic cell maturation and CD8 T cell infiltration in combination with immunoradiotherapy, at this years American Association for Cancer Research (AACR) Virtual Annual Meeting on June 22, 2020.

Based on these preclinical findings, including a 100% complete response of the triple I/O combination of Plinabulin, anti-PD-1, and radiation in a PD-1 antibody non-responsive model, the compound is being advanced toward a Phase 1 clinical trial in patients who failed or progressed on PD-1 / PD-L1 antibody treatments. Principal investigator Steven H. Lin,M.D., Ph.D., associate professor of radiation oncology at The University of Texas MD Anderson Cancer Center, presented the research data.

The experiments from my lab demonstrated that Plinabulin treatment in murine cancer models leads to activation of antigen-presenting dendritic cells, said Dr. Lin. The combination therapy with Plinabulin, anti-PD-1 therapy and radiation therapy further activated the immune system, resulting in increased T-cell activation, which is associated with increased tumor regressions.

Additional data highlights include:

The above data presentation is available on the Posters page of the BeyondSprings website at: https://www.beyondspringpharma.com/conferences/list.aspx?lcid=3.

Peer-reviewed 2019 publications in Chem and Cell Reports demonstrated that Plinabulin is differentiated from all other tubulin-targeted agents through its binding site and kinetics and is among the most potent agents that induce dendritic cell maturation. Dendritic cells are key immune cell types in the activation of the immune system against cancer cells, but currently approved immuno-oncology agents, such as antibodies to PD-1, only take the brakes off of T-cells without activating antigen-presenting cells that stimulate T-cells to attack foreign proteins expressed by cancer cells.

We believe that the activation of dendritic cells is a key to unlocking the next boost to the efficacy of immuno-oncology agents, said Dr. James Tonra, BeyondSprings Chief Scientific Officer. Activated dendritic cells present foreign tumor antigens to T-cells to induce cancer-directed immune attacks. Thus, adding this critical step of dendritic cell activation in the immune cascade to the established effects of immune checkpoint inhibition therapies is expected to increase overall anti-cancer efficacy in the clinic. Our anti-cancer strategy was to activate dendritic cells and T-cells, in combination with checkpoint inhibition and to add onto the benefits of neoantigen generation and immune activation from radiotherapy, as Plinabulin serves as the key to reverse the tumor non-response to PD-1/PD-L1 antibodies. The data strongly indicates that this triple combination has enough potential to move into clinical testing to help patients who failed or had progressed on anti-PD-1/PD-L1 targeted therapy, a severely unmet medical need.

About BeyondSpringBeyondSpring is a global, clinical-stage biopharmaceutical company focused on the development of innovative immuno-oncology cancer therapies. BeyondSprings lead asset, first-in-class agent Plinabulin as an immune and stem cell modulator, is in a Phase 3 global clinical trial as a direct anticancer agent in the treatment of non-small cell lung cancer (NSCLC) and two Phase 3 clinical programs in the prevention of chemotherapy-induced neutropenia (CIN). BeyondSpring has strong R&D capabilities with a robust pipeline in addition to Plinabulin, including three immuno-oncology assets and a drug discovery platform using the ubiquitination degradation pathway. The Company also has a seasoned management team with many years of experience bringing drugs to the global market.

About PlinabulinPlinabulin, BeyondSprings lead asset, is a differentiated immune and stem cell modulator. Plinabulin is currently in late-stage clinical development to increase overall survival in cancer patients, as well as to alleviate chemotherapy-induced neutropenia (CIN). The durable anticancer benefits of Plinabulin have been associated with its effect as a potent antigen-presenting cell (APC) inducer (through dendritic cell maturation) and T-cell activation (Chem and Cell Reports, 2019). Plinabulins CIN data highlights the ability to boost the number of hematopoietic stem / progenitor cells (HSPCs), or lineage-/cKit+/Sca1+ (LSK) cells in mice. Effects on HSPCs could explain the ability of Plinabulin to not only treat CIN but also to reduce chemotherapy-induced thrombocytopenia and increase circulating CD34+ cells in patients.

Cautionary Note Regarding Forward-Looking StatementsThis press release includes forward-looking statements that are not historical facts. Words such as "will," "expect," "anticipate," "plan," "believe," "design," "may," "future," "estimate," "predict," "objective," "goal," or variations thereof and variations of such words and similar expressions are intended to identify such forward-looking statements. Forward-looking statements are based on BeyondSpring's current knowledge and its present beliefs and expectations regarding possible future events and are subject to risks, uncertainties and assumptions. Actual results and the timing of events could differ materially from those anticipated in these forward-looking statements as a result of several factors including, but not limited to, difficulties raising the anticipated amount needed to finance the Company's future operations on terms acceptable to the Company, if at all, unexpected results of clinical trials, delays or denial in regulatory approval process, results that do not meet our expectations regarding the potential safety, the ultimate efficacy or clinical utility of our product candidates, increased competition in the market, and other risks described in BeyondSprings most recent Form 20-F on file with the U.S. Securities and Exchange Commission. All forward-looking statements made herein speak only as of the date of this release and BeyondSpring undertakes no obligation to update publicly such forward-looking statements to reflect subsequent events or circumstances, except as otherwise required by law.

Media ContactsCaitlin Kasunich / Raquel ConaKCSA Strategic Communications212.896.1241 / 212.896.1276ckasunich@kcsa.com / rcona@kcsa.com

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New Preclinical Data Demonstrates Immune-Enhancing Effects of Triple I/O Combination Therapy with BeyondSpring's Plinabulin - BioSpace