Amazing Science

Parts of the human genome now available to study for the first time are important for understanding genetic diseases, human diversity, and evolution.

The first truly complete sequence of a human genome, covering each chromosome from end to end with no gaps and unprecedented accuracy, is now accessible through the UCSC Genome Browser and is described in six papers published today (March 31, 2022) in Science.

Since the first working draft of a human genome sequence was assembled at UC Santa Cruz in 2000, genomics research has led to enormous advances in our understanding of human biology and disease. Nevertheless, crucial regions accounting for some 8% of the human genome have remained hidden from scientists for over 20 years due to the limitations of DNA sequencing technologies.

Karen Miga, assistant professor of biomolecular engineering at UC Santa Cruz, and Adam Phillippy at the National Human Genome Research Institute (NHGRI) organized an international team of scientists—the Telomere-to-Telomere (T2T) Consortium—to fill in the missing pieces. Their efforts have now paid off.

Strong efforts have been placed on understanding the physiological roles and therapeutic potential of the proglucagon peptide hormones including glucagon, GLP-1 and GLP-2. However, little is known about the extent and magnitude of variability in the amino acid composition of the proglucagon precursor and its mature peptides. Scientists now identified 184 unique missense variants in the human proglucagon gene GCG obtained from exome and whole-genome sequencing of more than 450,000 individuals across diverse sub-populations. This provides an unprecedented source of population-wide genetic variation data on missense mutations and insights into the evolutionary constraint spectrum of proglucagon-derived peptides.

The researchers were able to show that the stereotypical peptides glucagon, GLP-1 and GLP-2 display fewer evolutionary alterations and are more likely to be functionally affected by genetic variation compared to the rest of the gene products. Elucidating the spectrum of genetic variations and estimating the impact of how a peptide variant may influence human physiology and pathophysiology through changes in ligand binding and/or receptor signaling, are vital and serve as the first important step in understanding variability in glucose homeostasis, amino acid metabolism, intestinal epithelial growth, bone strength, appetite regulation, and other key physiological parameters controlled by these hormones.

A study involving more than 5,000 COVID-19 patients in Houston finds that the virus that causes the disease is accumulating genetic mutations, one of which may have made it more contagious. According to the paper published in the peer-reviewed journal mBIO, that mutation, called D614G, is located in the spike protein that pries open our cells for viral entry. It’s the largest peer-reviewed study of SARS-CoV-2 genome sequences in one metropolitan region of the U.S. to date.

The paper shows “the virus is mutating due to a combination of neutral drift — which just means random genetic changes that don’t help or hurt the virus — and pressure from our immune systems,” said Ilya Finkelstein, associate professor of molecular biosciences at The University of Texas at Austin and co-author of the study. The study was carried out by scientists at Houston Methodist Hospital, UT Austin and elsewhere.

During the initial wave of the pandemic, 71% of the novel coronaviruses identified in patients in Houston had this mutation. When the second wave of the outbreak hit Houston during the summer, this variant had leaped to 99.9% prevalence. This mirrors a trend observed around the world. A study published in July based on more than 28,000 genome sequences found that variants carrying the D614G mutation became the globally dominant form of SARS-CoV-2 in about a month. SARS-CoV-2 is the coronavirus that causes COVID-19. So why did strains containing this mutation outcompete those that didn’t have it?

Perhaps they’re more contagious. A study of more than 25,000 genome sequences in the U.K. found that viruses with the mutation tended to transmit slightly faster than those without it and caused larger clusters of infections. Natural selection would favor strains of the virus that transmit more easily. But not all scientists are convinced. Some have suggested another explanation, called “founder’s effects.” In that scenario, the D614G mutation might have been more common in the first viruses to arrive in Europe and North America, essentially giving them a head start on other strains.

Like a scene out of "Invasion of the Body Snatchers," a virus infects a host and converts it into a factory for making more copies of itself. Now researchers have shown that a large group of viruses, including the influenza viruses and other serious pathogens, steal genetic signals from their hosts to expand their own genomes.

This finding is presented in a study published June 25th, 2020 in Cell. The cross-disciplinary collaborative study was led by researchers at the Global Health and Emerging Pathogens Institute at Icahn School of Medicine at Mount Sinai in New York, and at the MRC-University of Glasgow Centre for Virus Research in the UK.

The cross-disciplinary team of virologists looked at a large group of viruses known as segmented negative-strand RNA viruses (sNSVs), which include widespread and serious pathogens of humans, domesticated animals and plants, including the influenza viruses and Lassa virus (the cause of Lassa fever). They showed that, by stealing genetic signals from their hosts, viruses can produce a wealth of previously undetected proteins. The researchers labeled them as UFO (Upstream Frankenstein Open reading frame) proteins, as they are encoded by stitching together the host and viral sequences. There was no knowledge of the existence of these kinds of proteins prior to this study.

Research could be a crucial step in helping scientists develop approaches to predict severity of future coronavirus disease outbreaks.

A team of researchers from the National Library of Medicine (NLM), part of the National Institutes of Health, identified genomic features of SARS-CoV-2, the virus that causes COVID-19, and other high-fatality coronaviruses that distinguish them from other members of the coronavirus family. This research could be a crucial step in helping scientists develop approaches to predict, by genome analysis alone, the severity of future coronavirus disease outbreaks and detect animal coronaviruses that have the potential to infect humans. The findings were published this week in the Proceedings of the National Academy of Sciences(link is external).

COVID-19, an unprecedented public health emergency, has now claimed more than 380,000 lives worldwide. This crisis prompts an urgent need to understand the evolutionary history and genomic features that contribute to the rampant spread of SARS-CoV-2. “In this work, we set out to identify genomic features unique to those coronaviruses that cause severe disease in humans,” said Dr. Eugene Koonin, an NIH Distinguished Investigator in the intramural research program of NLM’s National Center for Biotechnology Information, and the lead author of the study. “We were able to identify several features that are not found in less virulent coronaviruses and that could be relevant for pathogenicity in humans. The actual demonstration of the relevance of these findings will come from direct experiments that are currently getting under way.”

Using integrated comparative genomics and machine learning techniques, the researchers compared the genome of the SARS-CoV-2 virus against the genomes of other members of the coronavirus family and identified protein features that are unique to SARS-CoV-2 and two other coronavirus strains with high fatality rates, SARS-CoV and MERS-CoV. The identified features correspond with the high fatality rate of these coronaviruses, as well as their ability to move from animal to human hosts.

These features include insertions of specific stretches of amino acids into two virus proteins, the nucleocapsid and the spike.

These features are found in all three high-fatality coronaviruses and their closest relatives that infect animals, such as bats, but not in four other human coronaviruses that cause non-fatal disease. In particular, the insertions in the spike protein are predicted, from protein structure analysis, to facilitate the recognition of the coronavirus receptors on human cells and the subsequent penetration of the virus into those cells. Finding these features in animal coronavirus isolates could predict the jump to humans and the severity of disease caused by such isolates.

The virus has mutated. But that doesn’t mean it’s getting deadlier.

At this point in the pandemic, coronavirus genomes with 10 or fewer mutations are common, and only a small number have over 20 mutations — which is still less than a tenth of a percent of the genome.

Over time, viruses can evolve into new strains — in other words, viral lineages that are significantly different from each other. Since January, researchers have sequenced many thousands of SARS-CoV-2 genomes and tracked all the mutations that have arisen. So far, they haven’t found compelling evidence that the mutations have had a significant change in how the virus affects us.

Comprehensive genomic characterization of tumours became a major goal of cancer researchers as soon as the first human genome had been sequenced in 2001. Since then, advances in sequencing technology and analytical tools have allowed this research field to flourish. In six papers1–6 in this issue of Nature, the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium presents the most comprehensive and ambitious meta-analysis of cancer genomes so far. Unlike previous efforts that focused largely on protein-coding regions of the cancer genome, PCAWG analyses whole genomes. Each article scrutinizes an important aspect of cancer genetics — together, their findings will be key to understanding the full genetic complexity of cancer.

Before discussing the impact of these analyses, it is crucial to highlight the massive amount of data and the complex organizational framework that underpin the PCAWG endeavor. The project involved an interdisciplinary group of scientists from 4 continents, with 744 affiliations between them, who had to overcome major technical, legal and ethical challenges to carry out distributed analyses while protecting patient data. Researchers were divided into 16 working groups, each focused on distinct facets of cancer genomics — assessing the recurrence of mutations, for instance, or inferring tumor evolution.

Altogether, the consortium performed integrative analyses of 38 tumor types. The group sequenced 2,658 whole-cancer genomes (Fig. 1), alongside matched samples of non-cancerous cells from the same individuals. These data were complemented by 1,188 transcriptomes — the sequences and abundances of RNA transcripts in a tumor.

Collecting DNA samples for human genetic studies can be an expensive, lengthy process that has often made it difficult to include diverse populations in studies of medical and health data. University of Michigan researchers and their colleagues believe they have found a way to harness the power of social media and its ubiquitous presence to recruit a large, diverse participant pool they hope will help provide quick, reliable data for genetic studies. Their study appears in the June 13, 2019 issue of The American Journal of Human Genetics.

“The ability to study very large groups of individuals is a key challenge in human genetics, which is using very rare genetic changes—each present in very few individuals—to understand human biology and health and provide leads for design of new medicines,” said senior author Gonçalo Abecasis, a professor at U-M’s School of Public Health.

Katharine Brieger, a doctoral student in public health and first author of the report, said that for studies to be relevant to a broader population, they need to include samples of a wide range of racial, ethnic and socioeconomic backgrounds. “Historically, genetic studies were largely made up of people who lived near university medical centers, inadvertently excluding people who lived in more remote areas or who didn’t have the time and money to travel,” she said. “Allowing remote participation with Genes for Good allows many of these people to participate in research for the first time.”

Researchers invited people to participate in the Genes for Good study through Facebook starting in January 2015. Requirements included that participants live in the United States, have a Facebook account and be at least 18. Most of the recruitment was done organically, with people finding the Genes for Good application through family and friends.

As of March 2019, about 117,000 people tried the app, 80,000 people had engaged with the study, 32,000 kits had been sent and 27,000 DNA samples collected. Genotypes for the first 20,232 participants were analyzed.

Polygenic risk scores represent a giant leap for gene-based diagnostic tests. Here is what they mean for predictive personalized medicine:

When researchers completed the first drafts of the human genome in the early 2000s, many expected that it would mark the start of a medical revolution. Geneticists started searching for the differences that might explain why one person develops diabetes or heart disease whereas another does not. The idea was simple: compare a group of people with the condition to a group without and look for differences in their DNA. The variations generally came in the form of DNA-letter swaps, known as single nucleotide polymorphisms, or SNPs. If people with a condition tended to have a T at a certain location whereas others had a C, that suggested that the SNP was associated in some way with the disease.

These genome-wide association studies — or GWASs, as they came to be known — became very popular. But after years of searching, scientists could still only explain a small bit of the inherited risk for common diseases. It turned out that most of these conditions were related to many more SNPs than scientists had first expected, says Ali Torkamani, a geneticist at the Scripps Research Institute, La Jolla, California.

Worse still, a majority of the variants conferred a very small risk — detectable only when surveying huge groups of people.“We didn’t have the sample size to really drive prediction as well as some people naively thought,” says Ewan Birney, director of the European Bioinformatics Institute in Hinxton, UK. By 2007, geneticists were fretting about something they called “missing heritability”. It was clear that many of these conditions had a genetic component, but GWASs clearly weren’t catching much of it.

Today, things are finally changing. With access to massive data sets, as well as advances in how data are analyzed, scientists are getting better at measuring those very small risks. A prime example is the technique geneticist Kathiresan used to generate his 6.6-million SNP score, which was published in August 20181. He and his team took data from a 2015 meta-analysis that combined 48 GWASs, consisting of 61,000 people with coronary artery disease and 120,000 controls2. They then tested their polygenic predictor on 290,000 people in the UK Biobank, finding that those scoring in the highest few percentiles had on average several times higher risk of developing the disease than did the rest of the population. Of the 23,000 people who received the highest scores, for example, 7% had coronary artery disease, compared with 2.7% of the remaining population. The group conducted similar analyses for four other disorders, including inflammatory bowel disease and breast cancer, each time identifying a group who scored in the top few percentiles and were at particularly high risk.

Understanding how people will react to polygenic scores is a high priority for researchers. Ripatti and his colleagues have given more than 7,000 individuals in Finland information about their likelihood of developing heart disease, based on both polygenic scores and conventional risk factors such as high blood pressure. Most of the respondents say that getting this information motivates them to make positive changes, says Ripatti. Preliminary results suggest that those with high genetic risk are the most likely to take actions such as losing weight or stopping smoking.

In nearby Estonia, researchers are in the process of genotyping 100,000 individuals, adding to the 50,000 the country has already sampled. And unlike many other biobanks, participants in the Estonian project can sign up to receive feedback. Among the results being returned to them are polygenic risk scores for type 2 diabetes and cardiovascular disease, says Lili Milani, a geneticist at the Estonian Genome Center at the University of Tartu, Estonia. Similar to the Finnish work, participants are shown graphs of how lifestyle changes could reduce or increase their risk. And, says Milani, initial indications are that people are glad for the advice.

For now, people are receiving their scores from genetic counsellors. But Milani is working with the Estonian government to work out how to integrate genomic data into the health-care system, so that it can be used every day by doctors. The country ultimately aims to genotype anyone who’s interested, right up to its entire population of 1.3 million, Milani says. “The goal is to build something so great that all doctors will want to recommend it and all of the population will want it.”

The cancer patients saw their tumors disappear after the treatment, and have been cancer-free for two years.

A total of 12 patients have completed treatment with dostarlimab and have undergone at least 6 months of follow-up. All 12 patients (100%; 95% confidence interval, 74 to 100) had a clinical complete response, with no evidence of tumor on magnetic resonance imaging, 18F-fluorodeoxyglucose–positron-emission tomography, endoscopic evaluation, digital rectal examination, or biopsy. At the time of this report, no patients had received chemoradiotherapy or undergone surgery, and no cases of progression or recurrence had been reported during follow-up (range, 6 to 25 months). No adverse events of grade 3 or higher have been reported.

CONCLUSIONS

Mismatch repair–deficient, locally advanced rectal cancer was highly sensitive to single-agent PD-1 blockade. Longer follow-up is needed to assess the duration of response. (Funded by the Simon and Eve Colin Foundation and others; ClinicalTrials.gov number, NCT04165772. opens in new tab.)

UK Biobank offers easy access to genomic database for researchers around the world

In the largest single release of whole genomes ever, the UK Biobank (UKBB) this week unveiled to scientists the entire genomes of 200,000 people who are part of a long-term British health study.

The trove of genomes, each linked to anonymized medical information, will allow biomedical scientists to scour the full 3 billion base pairs of human DNA for insights into the interplay of genes and health that could not be gleaned from partial sequences or scans of genome markers. “It is thrilling to see the release of this long-awaited resource,” says Stephen Glatt, a psychiatric geneticist at the State University of New York Upstate Medical University.

Other biobanks have also begun to compile vast numbers of whole genomes, 100,000 or more in some cases (see table, below). But UKBB stands out because it offers easy access to the genomic information, according to some of the more than 20,000 researchers in 90 countries who have signed up to use the data.

“In terms of availability and data quality, [UKBB] surpasses all others,” says physician and statistician Omar Yaxmehen Bello-Chavolla of the National Institute for Geriatrics in Mexico City.

Biobanks

A number of efforts are releasing many thousands of whole genomes, with varying degrees of access, to accelerate biomedical research.

Having enrolled 500,000 middle-age and elderly participants of mostly European ancestry from 2006 to 2010, UKBB is one of the largest genetics research databases in the world. It proved its worth even before releasing whole genomes. Studies of specific DNA markers that vary among participants have revealed hundreds of new disease risk genes. Since 2019 researchers have also been probing participants’ exomes, the 2% of the whole genome sequence (WGS) that encodes proteins; the exomes from nearly all participants became available in the past 2 months. Exome studies are yielding risk genes that are very rare and can’t be found with genotyping data.

But whole genomes will make it possible to explore the influence of noncoding DNA, which controls when genes are turned off or on, and of gene rearrangements, as well as missing, repeated, or extra stretches of DNA in genes. Such changes play a role in diseases such as Huntington disease.

CRISPR has sparked a renaissance in genome editing. Now, next-generation CRISPR technologies let scientists modify the genome more efficiently and precisely than before. Such tools could one day serve as therapeutics, but many challenges remain.

Most drugs are small molecules that can be packaged into a pill. Genome editors are large, complicated molecules – so scientists can’t just stuff them into a pill for people to swallow, or inject them into people’s bodies. They have to find other ways to get the molecules into patients’ cells. One method relies on viruses, says Guangping Gao, a gene therapy researcher at the University of Massachusetts Medical School and president of the American Society of Gene and Cell Therapy. Scientists could potentially package genome editors into small viruses like adeno-associated viruses, for example. These viruses, which have already seen clinical use in several FDA-approved drugs, could then infect patients’ cells and dump their payloads.

It could be that scientists will need to develop entirely different delivery systems. Researchers are currently experimenting with lipid nanoparticles and using electric fields to coax genome editors into cells that can then be transplanted into patients. Delivery remains a major hurdle, Gao says, but he’s still excited about genome editors’ potential. “Gene therapy is now in its golden age,” he says. And genome editors “open even more avenues for treating disease.”

A chance mutation that led to spinal defects in a zebrafish has opened a little window into our own fishy past. Rising fifth-year Duke graduate student Brianna Peskin, who started the project during her first-year rotation in Michel Bagnat's cell biology lab and "kinda kept coming back to it," was merely trying to figure out why this one mutation led to developmental issues in a zebrafish's spine.

What she found is that embryos of the mutant fish have a single-letter change in their DNA that alters the way they build the bones and other structures that make up their spine, leaving them with a shorter body and a tortured looking spine that contains clefts dividing their vertebrae in half.

The mutant fish are named spondo, short for spondylos which is Greek for spine, and also a reference to dispondyly, a condition where each vertebra has two bony arches not one. But that's not the end of the story. When Bagnat's research colleague Matthew Harris of Harvard Medical School showed some pictures of the mutant fish spine to a colleague in fish paleontology, Gloria Arratia at the University of Kansas, she immediately spotted that the mutants look a lot like fossil specimens of ancestral fish whose style of spine has gone out of fashion in most living fishes.

"And then they both got really excited because they were noticing these similarities between ancestral fossil specimens and our mutant," Peskin said. The tiny mutation showed that both recipes for spine development are still to be found in the fish genome.

In the bony fish, known as teleosts, building the spine relies on a tube-like structure running the length of the developing embryo called the notochord. The notochord sets up the patterns that lead to articulated bones and cartilage in the developing spine by sending chemical signals that attract different molecules and cell types to different regions -- bone parts here, cartilage parts there.

Human embryos start with a notochord too, but it doesn't pattern the bony vertebrae the way it does in teleosts; it ends up building the cartilage pucks between the bones, the intervertebral discs. The gene that is mutated in spondo fish is unique to teleosts and the mutant fish's notochord doesn't set up the patterning the way it does in other fish. Rather, its patterning reverts to an ancestral form. So, this tiny difference in DNA may be where land animals like us parted company with our fish ancestors a very, very, very long time ago.

Humans are not the only species facing a potential threat from SARS-CoV-2, the novel coronavirus that causes COVID-19, according to a new study from the University of California, Davis.

An international team of scientists used genomic analysis to compare the main cellular receptor for the virus in humans -- angiotensin converting enzyme-2, or ACE2 -- in 410 different species of vertebrates, including birds, fish, amphibians, reptiles and mammals.

The virus SARS coronavirus 2 (SARS-CoV-2) is the known cause of coronavirus disease 2019 (COVID-19). The "spike" or S protein facilitates viral entry into host cells.

Now a group of researchers from Seoul National University in South Korea, University of Cambridge in UK, and Lehigh University in USA, have worked together to produce the first open-source all-atom models of a full-length S protein. The researchers say this is of particular importance because the S protein plays a central role in viral entry into cells, making it a main target for vaccine and antiviral drug development.

The details can be found in a paper , "Developing a Fully-glycosylated Full-length SARS-CoV-2 Spike Protein Model in a Viral Membrane" just published online in The Journal of Physical Chemistry B.

This video demo illustrates how to build this membrane system from their SARS-CoV-2 S protein models. The model-building program is open access and can be found from the home page of CHARMM-GUI by clicking on the COVID-19 Archive link , or by clicking the archive link in the header, then the COVID-19 Proteins link in the left sidebar.

COVID-19 Symptoms Swayed By Genetics

More info from WIRED Magazine

Some people experience Covid-19 as nothing more than a mild cold, and others exhibit no symptoms at all. Then there are the thousands who sicken and, often, die. Scientists are working hard to understand the underlying reasons for such huge discrepancies in symptoms and outcomes. No one knows the answer yet. One theory: It is locked deep in our genetic makeup.

Researchers at Washington University School of Medicine in St. Louis have used induced pluripotent stem cells produced from the skin of a patient with a rare, genetic form of insulin-dependent diabetes, transformed the stem cells into insulin-producing cells, used the CRISPR gene-editing tool to correct a defect that caused the diabetes, and implanted the cells into mice to reverse diabetes in the animals.

Using induced pluripotent stem cells produced from the skin of a patient with a rare, genetic form of insulin-dependent diabetes called Wolfram syndrome, researchers transformed the human stem cells into insulin-producing cells and used the gene-editing tool CRISPR-Cas9 to correct a genetic defect that had caused the syndrome. They then implanted the cells into lab mice and cured the unrelenting diabetes in those mice.

The findings, from researchers at Washington University School of Medicine in St. Louis, suggest the CRISPR-Cas9 technique may hold promise as a treatment for diabetes, particularly the forms caused by a single gene mutation, and it also may be useful one day in some patients with the more common forms of diabetes, such as type 1 and type 2. The study is published online April 22 in the journal Science Translational Medicine.

Patients with Wolfram syndrome develop diabetes during childhood or adolescence and quickly require insulin-replacement therapy, requiring insulin injections multiple times each day. Most go on to develop problems with vision and balance, as well as other issues, and in many patients, the syndrome contributes to an early death.

"This is the first time CRISPR has been used to fix a patient's diabetes-causing genetic defect and successfully reverse diabetes," said co-senior investigator Jeffrey R. Millman, PhD, an assistant professor of medicine and of biomedical engineering at Washington University. "For this study, we used cells from a patient with Wolfram syndrome because, conceptually, we knew it would be easier to correct a defect caused by a single gene. But we see this as a stepping stone toward applying gene therapy to a broader population of patients with diabetes."

A new gene therapy appears to serve as a functional cure for the most common type of hemophilia, early clinical trial results indicate.

Patients who received the one-time intravenous therapy continue to have a more than 90 percent decrease in bleeding events two to three years after their initial treatment, researchers reported Jan. 1, 2020 in the New England Journal of Medicine.

The therapy fixes a broken gene in liver cells that causes production of flawed factor VIII, a protein that plays a key role in blood clotting. People with this genetic mutation have hemophilia A, the most common type of this bleeding disorder. Hemophilia A accounts for 8 out of 10 cases of hemophilia, researchers said.

Hemophilia A patients must inject themselves with factor VIII every other day to prevent bleeding, said lead researcher John Pasi, a professor at Barts and The London School of Medicine and Dentistry in England. "There's been a massive reduction in bleeding in the patients, and none of them any longer need to regularly treat themselves with factor VIII to prevent bleeding," Pasi said of participants in the phase 1/phase 2 clinical trial. "That huge treatment burden of having to give yourself an intravenous injection every other day has gone away."

The therapy uses a virus to carry the DNA sequence for a functional factor VIII gene into liver cells, he said. "It infects liver cells and transfers into those cells the factor VIII gene," Pasi said. "Liver cells make factor VIII and then secrete it, and it passes into the circulation."

Seven initial participants in the study have a 96 percent decrease in bleeding events three years out, researchers report. Another six who joined later had a 92 percent decrease in bleeding by the end of year two.

"At three years, the patients who were treated at a higher dose were expressing functional levels of factor VIII -- somewhat lower than they were at their peak, but they're still at really good levels that are hugely effective in protecting the patients against bleeding," Pasi said.

A team led by researchers at St. Jude Children's Research Hospital has conducted an multi-faceted integrated analysis of rhabdomyosarcoma (RMS) samples, a relatively rare but deadly childhood cancer.  The strategy involved transcriptomic, epigenomic, proteomic, and phospho-proteomic data analysis, leading the authors of the study to conclude that a number of deregulated pathways could be addressed therapeutically. Based on further preclinical testing, the researchers also found the WEE1 kinase to be a promising target for treating high-risk RMS.

The study, which is part of the St. Jude-Washington University Pediatric Cancer Genomic Project and was led by senior author Michael Dyer, chair of the Department of Developmental Neurobiology at St. Jude's, was recently published in Cancer Cell.

"This research offers a template for exploring the origins and vulnerabilities of solid tumors by looking not only at somatic mutations, but also at epigenetic changes and ultimately differences in how those changes are manifest in protein expression and activity," Dyer said in a statement, adding that it "also highlights how preclinical models and extensive preclinical testing can help prioritize and streamline drug development."

Rhabdomyosarcoma is a relatively rare childhood solid tumor that involves muscle and soft tissue and affects about 350 patients in the US each year. While the cure rate is 75 percent for patients with localized tumors, survival is only 30 percent for patient with metastatic disease and just 17 percent for those with recurring disease. Survival numbers have not improved much in the last 15 years. The majority of RMS cases are embryonal (ERMS), while most others are of the alveolar (ARMS) type.

For their study, the researchers focused on 17 so-called orthotopic patient-derived xenografts (O-PDX) of pediatric solid tumors that had previously been studied at the genomic level, as well as on primary human myoblasts, myotubes, and fetal skeletal muscle samples. Specifically, they performed whole-genome bisulfite sequencing, RNA sequencing, and chromatin immunoprecipitation and sequencing (ChIP-seq).

In addition, they used 10-plex isobaric labeling mass spectrometry to quantify the proteome and phospho-proteome of 12 O-PDXs and several human myoblasts and myotubes in replicated experiments. In total, they analyzed more than 16,500 human proteins and almost 63,000 phosphorylation events on about 7,200 proteins.

They then analyzed the data across multiple platforms, using two approaches. In one, they looked at differentially expressed proteins and mRNAs in tumors and myoblasts and performed co-expression clustering of those genes and proteins that were conserved across the two platforms. For the other, they integrated transcriptomic, epigenomic, proteomic, and phospho-proteomic data with order statistics. Their analyses showed that the RAS pathway, the unfolded protein response pathway, and the G2/M-mitotic spindle checkpoint pathway were the most affected pathways in the RMS samples.

Through extensive preclinical testing, which involved screening more than 1,700 drug-tumor combinations, they found that AZD1775, which inhibits the WEE1 enzyme in the G2/M pathway, shows promise as a treatment for high-risk RMS. As a result, the Children's Oncology Group has expanded a multicenter phase I/II clinical trial of AZD1775 and the drug irinotecan to include high-risk rhabdomyosarcoma patients, according to St. Jude.