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An unprecedented amount of research has been focused solely on understanding the novel coronavirus that has taken nearly 150,000 lives across the globe. And while scientists have gotten to know some of the most intimate details of the virus called SARS-CoV-2, one question has evaded any definitive answers Where did the virus come from?

Live Science contacted several experts, and the reality, they said, is that we may never know where this deadly coronavirus originated. Among the theories circulating: That SARS-CoV-2 arose naturally, after passing from bats to a secondary animal and then to humans; that it was deliberately engineered and then accidentally released by humans; or that researchers were studying a naturally-occurring virus that subsequently escaped from a high-security biolab, the Wuhan Institute of Virology (WIV) in China. The head of the lab at WIV, for her part, has emphatically denied any link to the institute.

Just today (April 18), the vice director of WIV Zhiming Yuan CGTN, the Chinese state broadcaster, said "there is no way this virus came from us," NBC News reported. "We have a strict regulatory regime and code of conduct of research, so we are confident."

Furthermore, the notion that SARS-CoV-2 was genetically engineered is pure conspiracy, experts told Live Science, but it's still impossible to rule out the notion that Chinese scientists were studying a naturally-occurring coronavirus that subsequently "escaped" from the lab. To prove any of these theories takes transparent data and information, which is reportedly not happening in China, scientists say. Several experts have said to Live Science and other media outlets have reported that the likeliest scenario is that SARS-CoV-2 is naturally occurring.

Related: 13 coronavirus myths busted by science

"Based on no data, but simply [a] likely scenario is that the virus went from bats to some mammalian species, currently unknown despite speculation, [and] spilled over to humans," said Gerald Keusch, associate director of the Boston University National Emerging Infectious Diseases Laboratories. This spillover event may have happened before the virus found its way into a live animal market, "which then acted as an amplifying setting with many more infections that subsequently spread and the rest is history," Keusch said. "The timeline is fuzzy and I don't think we have real data to say when these things began, in large part because the data are being held back from inspection," Keusch told Live Science.

The SARS-CoV-2 virus is most closely related to coronaviruses found in certain populations of horseshoe bats that live about 1,000 miles (1,600 kilometers) away in Yunnan province, China. The first known outbreak of SARS-CoV-2 in humans occurred in Wuhan and initially was traced to a wet seafood market (which sold live fish and other animals), though some of the earliest cases have no link to that market, according to research published Feb. 15 in the journal The Lancet.

Related: 11 (sometimes) deadly diseases that hopped across species

What's more, despite several proposed candidates, from snakes to pangolins to dogs, researchers have failed to find a clear "intermediate host" an animal that would have served as a springboard for SARS-CoV-2 to jump from bats to humans. And if horseshoe bats were the primary host, how did the bat virus hop from its natural reservoir in a subtropical region to the bustling city of Wuhan hundreds of miles away?

These questions have led some people to look elsewhere in the hunt for the virus's origin, and some have focused on the Wuhan Institute of Virology (WIV).

In 2015, WIV became China's first lab to reach the highest level of bioresearch safety, or BSL-4, meaning the lab could host research on the world's most dangerous pathogens, such as Ebola and Marburg viruses. (SARS-CoV-2 would require a BSL-3 or higher, according to the Centers for Disease Control and Prevention.) Labs like these must follow strict safety guidelines that include filtering air, treating water and waste before they exit, and requiring lab personnel to shower and change their clothes before and after entering the facility, Nature News reported in 2017.

These types of labs do spur concerns among some scientists who worry about the risks involved and the potential impact on public health if anything were to go wrong, Nature News reported.

Related: The 12 deadliest viruses on Earth

WIV was not immune to those concerns. In 2018, after scientist diplomats from the U.S. embassy in Beijing visited the WIV, they were so concerned by the lack of safety and management at the lab that the diplomats sent two official warnings back to the U.S. One of the official cables, obtained by The Washington Post, suggested that the lab's work on bat coronaviruses with the potential for human transmission could risk causing a new SARS-like pandemic, Post columnist Josh Rogin wrote.

"During interactions with scientists at the WIV laboratory, they noted the new lab has a serious shortage of appropriately trained technicians and investigators needed to safely operate this high-containment laboratory," the officials said in their cable dated to Jan. 19, 2018.

When reports of the coronavirus first popped up in China, the U.S. Deputy National Security Advisor Matthew Pottinger reportedly suspected a potential link to China labs. In mid-January, according to a New York Times report, Pottinger asked intelligence agencies like the C.I.A., particularly individuals with expertise on Asia and weapons of mass destruction, to investigate this idea. They came up empty-handed, the Times reported.

Meanwhile, the lab at the center of these speculations had long been sounding the alarm about the risk of the SARS-like coronaviruses they studied to spawn a pandemic.

The head of the lab's bat-coronavirus research, Shi Zhengli, published research on Nov. 30, 2017 in the journal PLOS Pathogens that traced the SARS coronavirus pandemic in 2003 to a single population of horseshoe bats in a remote cave in Yunnan province. The researchers also noted that other SARS-like coronaviruses discovered in that cave used the ACE2 receptor to infect cells and could "replicate efficiently in primary human airway cells," they wrote. (Both SARS and SARS-CoV-2 use the ACE2 receptor as the entry point into cells.)

Zhengli and her colleagues stressed the importance of monitoring and studying the SARS coronaviruses to help prevent another pandemic.

"Thus, we propose that monitoring of SARS-CoV evolution at this and other sites should continue, as well as examination of human behavioral risk for infection and serological surveys of people, to determine if spillover is already occurring at these sites and to design intervention strategies to avoid future disease emergence," they wrote.

Related: 20 of the worst epidemics and pandemics in history

The WIV lab, along with researchers in the U.S. and Switzerland, showed in 2015 the scary-good capability of bat coronaviruses to thrive in human cells. In that paper, which was published in 2015 in the journal Nature Medicine, they described how they had created a chimeric SARS-like virus out of the surface spike protein of a coronavirus found in horseshoe bats, called SHC014, and the backbone of a SARS virus that could be grown in mice. The idea was to look at the potential of coronaviruses circulating in bat populations to infect humans. In a lab dish, the chimeric coronavirus could infect and replicate in primary human airway cells; the virus also was able to infect lung cells in mice.

That study was met with some pushback from researchers who considered the risk of that kind of research to outweigh the benefits. Simon Wain-Hobson, a virologist at the Pasteur Institute in Paris, was one of those scientists. Wain-Hobson emphasized the fact that this chimeric virus "grows remarkably well" in human cells, adding that "If the virus escaped, nobody could predict the trajectory," Nature News reported.

None of this can show the provenance of SARS-CoV-2.

But scientists can start to rule out an idea that the pandemic-causing coronavirus was engineered in that lab or further created as a bioweapon. Researchers say the overwhelming evidence indicates this is a natural-borne virus that emerged from an animal host, likely a bat, and was not engineered by humans.

Related: 28 devastating infectious diseases

"This origin story is not currently supported at all by the available data," said Adam Lauring, an associate professor of microbiology, immunology and infectious diseases at the University of Michigan Medical School. Lauring pointed to a study published March 17 in the journal Nature Medicine, which provided evidence against the idea that the virus was engineered in a lab.

In that Nature medicine study one of the strongest rebukes of this idea Kristian Andersen, an associate professor of immunology and microbiology at Scripps Research, and his colleagues analyzed the genome sequences of SARS-CoV-2 and coronaviruses in animals. They found that a key part of SARS-CoV-2, the spike protein that the virus uses to attach to ACE2 receptors on the outsides of human cells, would almost certainly have emerged in nature and not as a lab creation.

"This analysis of coronavirus genome sequences from patients and from various animals suggests that the virus likely arose in an animal host and then may have undergone further changes once it transmitted and circulated in people," Lauring told Live Science.

That may rule out deliberate genetic engineering, but what about other scenarios that point to bats as the natural hosts, but WIV as the source of the outbreak?

Although researchers will likely continue to sample and sequence coronaviruses in bats to determine the origin of SARS-CoV-2, "you can't answer this question through genomics alone," said Dr. Alex Greninger, an assistant professor in the Department of Laboratory Medicine and an assistant director of the Clinical Virology Laboratory at the University of Washington Medical Center. That's because it's impossible to definitively tell whether SARS-CoV-2 emerged from a lab or from nature based on genetics alone. For this reason, it's really important to know which coronaviruses were being studied at WIV. "It really comes down to what was in the lab," Greninger told Live Science.

However, Lauring said that based on the Nature Medicine paper, "the SARS-CoV-2 virus has some key differences in specific genes relative to previously identified coronaviruses the ones a laboratory would be working with. This constellation of changes makes it unlikely that it is the result of a laboratory 'escape,'" he said.

As for what viruses were being studied at WIV, Zhengli says she did a thorough investigation. When she first was alerted to the viral outbreak in Wuhan on the night of Dec. 30, 2019, Zhengli immediately put her lab to work sequencing the genomes of SARS-CoV-2 from infected patients and comparing the results with records of coronavirus experiments in her lab. She also looked for any mishandling of viral material used in any experiments, Scientific American reported. She didn't find any match between the viruses her team was working with from bat caves and those found in infected patients. "That really took a load off my mind," she told Scientific American. "I had not slept a wink for days."

At the beginning of February, Zhengli sent a note over WeChat to reassure her friends that there was no link, saying "I swear with my life, [the virus] has nothing to do with the lab," the South China Morning Post reported Feb. 6. Zhengli and another colleague, Peng Zhou, did not reply to a Live Science email requesting comment.

The Wuhan lab does work with the closest known relative of SARS-CoV-2, which is a bat coronavirus called RaTG13, evolutionary virologist Edward Holmes, of the Charles Perkins Center and the Marie Bashir Institute for Infectious Diseases and Biosecurity at the University of Sydney, said in a statement from the Australian Media Center. But, he added, "the level of genome sequence divergence between SARS-CoV-2 and RaTG13 is equivalent to an average of 50 years (and at least 20 years) of evolutionary change." (That means that in the wild, it would take about 50 years for these viruses to evolve to be as different as they are.)

Though no scientists have come forth with even a speck of evidence that humans knowingly manipulated a virus using some sort of genetic engineering, a researcher at Flinders University in South Australia lays out another scenario that involves human intervention. Bat coronaviruses can be cultured in lab dishes with cells that have the human ACE2 receptor; over time, the virus will gain adaptations that let it efficiently bind to those receptors. Along the way, that virus would pick up random genetic mutations that pop up but don't do anything noticeable, said Nikolai Petrovsky, in the College of Medicine and Public Health at Flinders.

"The result of these experiments is a virus that is highly virulent in humans but is sufficiently different that it no longer resembles the original bat virus," Petrovsky said in a statement from the Australian Media Center. "Because the mutations are acquired randomly by selection, there is no signature of a human gene jockey, but this is clearly a virus still created by human intervention."

If that virus infected a staff member and that person then traveled to the nearby seafood market, the virus could have spread from there, he said. Or, he added, an "inappropriate disposal of waste from the facility" could have infected humans directly or from a susceptible intermediary, such as a stray cat.

Though we may never get a definitive answer, at least in the near-term, some say it doesn't matter.

"No matter the origin, evolution in nature and spillover to humans, accidental release from a lab, or deliberate release or genetic manipulation of a pathogen in the lab the way you develop countermeasures is the same," Keusch told Live Science. "Since one can never say 100% for anything, I think we always need to be aware of all possibilities in order to contravene. But the response to develop what is needed to respond, control and eliminate the outbreak remains the same."

Live Science senior writer Rachael Rettner contributed to this report.

Originally published on Live Science.

Read more:
Wuhan lab says there's no way coronavirus originated there. Here's the science. - Livescience.com

The novel coronavirus likely originated in bats, but the pathogen may have then hopped into dogs before infecting humans, a new study suggests.

But not everyone agrees with that hypothesis. One expert told Live Science that "there are a lot of weaknesses" in the study and that the data don't support the study's conclusions.

Before the new coronavirus SARS-CoV-2 made the jump to humans, two other coronaviruses, SARS-CoV and MERS-CoV, evolved in bats and passed through other animals on their way to people. SARS-CoV passed through civets and MERS-CoV through camels, and the molecular structure of SARS-CoV-2 suggests that the virus also passed through an intermediate animal, but scientists don't yet know which one.

In February, authors of a preliminary study published to the preprint database bioRxiv suggested that pangolins may bridge the gap between bats and humans, since SARS-CoV-2 and related coronaviruses that infect pangolins sport similar spike proteins a structure on the surface of the virus that allows it to infect cells. But other scientists argued that, despite their spike proteins, pangolin coronaviruses bear many differences to SARS-CoV-2 that make pangolins unlikely to be the source of infection, The New York Times reported.

With the mystery unresolved, biology professor Xuhua Xia of the University of Ottawa in Canada launched his own investigation into how the coronavirus passed from bats to people. His analysis, published April 14 in the journal Molecular Biology and Evolution, offered a new solution: dogs.

Xia reached his conclusion by scanning the genetic code of SARS-CoV-2 and other coronaviruses for a specific feature known as a CpG site, a sequence of genetic code in which the compound cytosine (C) is followed by the compound guanine (G). The human immune system sees CpG sites as a red flag, signaling that an invasive virus is present. A human protein called zinc finger antiviral protein (ZAP) latches onto the CpG sites on the viral genetic code and recruits help to break down the pathogen, according to UniProt, an online protein database. The theory follows that, the fewer CpG sites, the less vulnerable a virus will be to ZAP.

Related: 10 deadly diseases that hopped across species

Xia found that SARS-CoV-2 carries fewer CpG sites than the other known coronaviruses that first evolved in animals, including SARS-CoV and MERS-CoV. In addition, the closest known relative of SARS-CoV-2, the bat coronavirus RaTG13, contains fewer CpG sites than related bat coronaviruses, according to the analysis. "This suggests that SARS-CoV-2 may have evolved in a new host (or new host tissue) with high ZAP expression," which would place evolutionary pressure on the virus to shed CpG sites, Xia wrote.

Essentially, in order to survive and reproduce, a pathogen like SARS-CoV-2 needs to be able to evade the hosts immune fighters, and in this case it would mean getting rid of CpG sites that could alert ZAP proteins to the virus.

Unfortunately, little data exists on exactly how much ZAP appears in different animal tissues, Xia told Live Science. So he worked backwards, looking for animal coronaviruses with low CpG levels. He found a coronavirus that primarily infects the canine intestine, and thus inferred that the dog gut might contain adequate ZAP levels to drive viral evolution in this way.

"Only canids seem to have the tissue generating low-CpG CoVs during my study," Xia said. If a precursor to SARS-CoV-2 breached the canine intestine, then this would have "resulted in rapid evolution of the virus" to lose CpG sites and become better equipped to infect humans, he wrote in the paper. Beyond the low CpG levels, the paper did not note other genetic similarities between SARS-CoV-2 and the dog coronavirus, but suggested that the canine gut might provide the right environment for such viruses to evolve.

But why the dog intestine? Some research suggests that ZAP mRNA, which contains instructions to build the protein, appears in both the dog lung and colon but that higher concentrations accumulate in the lungs, Xia said. It may be that a glut of ZAP in the lungs guards the organ from coronaviruses, while the lower concentrations of ZAP in the colon leave the gut open to severe infection, though there are reasons to be cautious in coming to this conclusion, Xia said.

But does this hypothesis make sense?

"I think the data do not support these conclusions," Pleuni Pennings, an assistant professor of ecology and evolution at San Francisco State University, who was not involved in the study, told Live Science in an email. Pennings, whose research group has examined the CpG levels of many viruses, pointed out several weaknesses in the study's logic.

In a 2018 study published in the journal PLOS Genetics, Pennings surveyed CpG levels in the HIV virus and investigated how the pathogen evolves within individual people. She then led a similar study of several other viruses including Dengue fever virus, influenza, and hepatitis B and C to learn how often these bugs lose or gain CpG sites through mutations. Her group found that, in general, mutations that add CpG sites tend to be found in viral samples taken from people less often than mutations that remove CpG sites from the genome.

CpG-creating mutations may be costly to viruses in that they alert the body to infection, so over time, evolutionary forces minimize their appearance, Pennings said. That said, many viruses still carry CpG sites, so the mutations may carry some benefit "even if it comes with a slight cost," she added. So SARS-CoV-2 is not unusual in that way.

"There are many viruses with lower [CpG] values than SARS-CoV-2," Pennings said. "When you look at all viruses, the [CpG] value is not strange at all," she said.

Xia did find that SARS-CoV-2 contains fewer CpG sites than other animal-borne coronaviruses, and assuming that finding is correct, then it raises the question of why that came to be, she added.

But even if there is an evolutionary reason to explain why SARS-CoV-2 lost CpG sites, that evolutionary reason may not give the virus a special advantage for infecting humans, Pennings said.

In his paper, Xia noted that studies have "shown an association between decreased CpG in viral RNA genomes and increased virulence," meaning low-CpG viruses appear associated with more severe infection. However, although evolution favors mutations that delete CpG sites, and there's a general trend tying fewer CpG sites to more severe infection, "it doesnt mean that viruses with low numbers of CpG sites are necessarily more virulent," Pennings said. For example, the BK virus contains very few CpG sites and resides in the kidneys of an estimated 60% to 80% of adults, but typically only triggers symptoms in immunosuppressed people, she noted. (The virus was named the initials of the first person it was isolated from.)

If the CpG levels present in SARS-CoV-2 are somehow related to disease severity, "then this would provide an efficient way for vaccine development," Xia said. In this hypothetical scenario, scientists could eliminate CpG sites from the coronavirus genome in a lab dish, thereby weakening the bug to the point that it could safely be incorporated into a vaccine. But as of yet, no correlation has been drawn between CpG and the relative severity of SARS-CoV-2 infections.

Several pangolin coronaviruses included in Xia's study also contained few CpG sites, on par with SARS-CoV-2 and the bat virus RaTG13. Given other genetic differences between human and pangolin coronaviruses, however, the ancestor shared between this low-CpG pangolin coronavirus and SARS-CoV-2 would likely have existed over 130 years ago, Xia said. "We expect a SARS-CoV-2 progenitor to be much more recent," he said.

But did dogs serve as an intermittent host for the coronavirus? At this point, there's little evidence to suggest so.

Originally published on Live Science.

Here is the original post:
New study suggests COVID-19 hopped from dogs to humans. Here's why you should be skeptical. - Live Science

The University of Washington School of Medicine will study pharmacogenetics in patients with COVID-19.

It will work with Washington, D.C.-based Vanda Pharmaceuticals to collect whole-genome sequencing data from more than 1,000 patients with coronavirus infection. The two will sequence the viral genomes to explore host susceptibility, clinical outcomes of whole-genome sequencing, host-virus interactions, and disease severity.

"We believe this collaboration will help answer critical questions and hopefully outcomes in the fight against COVID-19," Alex Greninger, assistant director of the virology division at the UW School of Medicine, said in a statement.

Financial and other details of the collaboration were not disclosed.

The collaboration with UW's virology lab will be part of a larger program from Vanda, dubbed Calypso, to study the role of human genetic variation in SARS-CoV-2 infection and COVID-19 disease progression.

"The study has the potential to provide new insights into virus-host interactions that could lead to more effective public health strategies and the design and development of vaccines and therapeutics," Sandra Smieszek, head of genetics at Vanda, said in a statement. "With the vast amount of data we expect to collect, the team will aim to discern the factors associated with severity and other critical, clinical characteristics of the infected individuals."

Vanda on Wednesday also announced it was working with Northwell Health's research arm to conduct a clinical trial of a drug to treat severe pneumonia in COVID-19 patients.

This story first appeared in our sister publication, Genomeweb.

Go here to read the rest:
University of Washington to study COVID-19 pharmacogenetics - ModernHealthcare.com

Gene Therapy R&D and Revenue Forecasts 2020-2030

Retroviruses, Lentiviruses, Adenoviruses, Adeno Associated Virus, Herpes Simplex Virus, Poxvirus, Vaccinia Virus, Naked/Plasmid Vectors, Gene Gun, Electroporation, Lipofection, Cancer, Rare Diseases, Cardiovascular Disorders, Ophthalmologic Conditions, Infectious Disease, Neurological Disorders, Diabetes Mellitus

LONDON, April 17, 2020 /PRNewswire/ -- The gene therapy market is projected to grow at a CAGR of 32% in the first half of the forecast period. In 2019, the cancer treatment submarket accounted for 55.8% of the gene therapy drug market. Visiongain estimated that gene therapy for rare diseases will be the driver for market growth in the first half of the forecast period.

How this report will benefit youRead on to discover how you can exploit the future business opportunities emerging in this sector.

In this brand-new 215-page report you will receive 157 charts all unavailable elsewhere.

The 215-page Visiongain report provides clear detailed insight into the gene therapy market. Discover the key drivers and challenges affecting the market.

By ordering and reading our brand-new report today you stay better informed and ready to act.

To request sample pages from this report please contact Sara Peerun at sara.peerun@visiongain.com or refer to our website: https://www.visiongain.com/report/gene-therapy-rd-and-revenue-forecasts-2020-2030/#download_sampe_div

Report Scope

Gene Therapy market forecasts from2020-2030

This report assesses the approved gene therapy products in the market and gives revenue to 2030

Provides qualitative analysis and forecast of the submarket by indication for the period 2020-2030: Cancer Cardiovascular disorders Rare diseases Ophthalmological diseases Infectious Diseases Neurological Disorders Diabetes Mellitus Other therapeutic uses

Profiles leading companies that will be important in the development of the gene therapy market. For each company, developments and outlooks are discussed and companies covered in this chapter include: UniQure Biogen Bluebird Bio Spark Therapeutics Applied Genetics Technologies Corporation Oxford Biomedica GenSight Biologics & Other Companies

Assesses the outlook for the leading gene treatment R&D pipeline for 2019 and discusses technological progress and potential. Profiles appear for gene therapy drug candidates, with revenue forecasts for four leading agents: Collategene (AMG0001, AnGes MG/Vical) BC-819 (BioCancell) BC-821 BioCancell SPK-CHM Spark Therapeutics SPK-FIX Spark Therapeutics/Pfizer SPK-TPP1- Spark Therapeutics Lenti-D (Bluebird Bio) LentiGlobin (Bluebird Bio) VM202-DPN ViroMed

Provides qualitative analysis of trends that will affect the gene therapies market, from the perspective of pharmaceutical companies, during the period 2020 to 2030. SWOT analysis is provided and an overview of regulation of the gene therapy market by leading region given.

Our study discusses factors that influence the market including these: Translation of research into marketable products modifying human DNA gene transfer for therapeutic use, altering the nuclear genome Genomic editing technology and other supporting components Collaborations to develop and launch gene-based products acquisitions and licensing deals Supporting technologies for human genetic modification, gene replacement and targeted drug delivery Gene therapies for ophthalmologic diseases next-generation medicines Regulations in the United States, the European Union and Japan overcoming technological and medical challenges to pass clinical trials.

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To request a report overview of this report please contact Sara Peerun at sara.peerun@visiongain.com or refer to our website: https://www.visiongain.com/report/gene-therapy-rd-and-revenue-forecasts-2020-2030/

Did you know that we also offer a report add-on service? Email sara.peerun@visiongain.comto discuss any customized research needs you may have.

Companies covered in the report include:

4DMT (4D Molecular Therapeutics)AbeonaAGTC (Applied Genetics Technologies Corporation)AMT (Amsterdam Molecular Therapeutics) AnGes MGAsklepios BioPharmaAstraZenecaAudentes TherapeuticsAvalanche BiotechBayer HealthcareBeijing Northland Biotech CoBenda PharmaceuticalBenitec BiopharmaBioCancellBiogenBiogen IdecBluebird BioBMS (Bristol-Myers Squibb)Broad Institute/Whitehead InstituteCelgeneCell Therapy CatapultCellectisChiesi Farmaceutici Clearside BiomedicalConvergence PharmaceuticalsDaiichi Sankyo Dimension TherapeuticsEditas MedicineFondazione TelethonFrancis Crick Institute Genable Technologies LtdGenethonGenSight BiologicsGenVecGoogleGSK (GlaxoSmithKline)Henry Ford Health SystemHSCI (Human Stem Cells Institute)HSR-TIGET (San Raffaele Telethon Institute for Gene Therapy), ImaginAbImmune Design Corp InoCardInovioIntellia TherapeuticsInvetechKite PharmaKolon GroupKolon Life ScienceLysogeneMitsubishi Tanabe Pharma Corporation NeuralgeneNightstaRxNorthwestern Memorial HospitalNovartisOXB (Oxford Biomedica)PfizerPNP TherapeuticsPrecision Genome Engineering Inc aka PregenenProNaiProtek GroupRaffaele HospitalREGENX BiosciencesRenova TherapeuticsRocheRoszdravnadzorSangamo BiosciencesSanofiSarepta TherapeuticsShanghai Sunway BiotechShenzhen SiBiono GeneTechSotex Pharm Firm Spark TherapeuticsSynerGene TherapeuticsTakara BioTAP BiosystemsThermo Fisher ScientificTissueGeneToolGenUC BerkeleyUC San Francisco uniQureUS Business Innovation Network Vertex PharmaceuticalsVical IncorporatedViroMedVM BiopharmaVoyage Therapeutics

List of Organisation Mentioned ASCO (American Society of Clinical Oncology)ASI (Agency for Strategic Initiatives) CAT (Committee for Advanced Therapies) CBER (Center for Biologics Evaluation and Research)CHMP (Committee for Medicinal Products for Human Use)CHOP (The Children's Hospital of Philadelphia)DCGI (Drugs Controller General of India)DHHS (Department of Health and Human Services)EMA (European Medicines Agency)FDA (US Food and Drug Administration)INSERM (Institut National de la Sant et de la Recherche Mdicale) IRB (Institutional Review Boards) MFDS (Korean Ministry of Food and Drug Safety) MHLW (Ministry of Health, Labour, and Welfare)MHRA (Medicines and Healthcare Products Regulatory Agency)Ministry of Health Commission NHS (National Health Service)NICE (the National Institute for Health and Care Excellence)NIH (National Institutes of Health) OHRP (Office for Human Research Protections)PMDA (Pharmaceuticals and Medical Devices Agency) RCGM (Review Committee of Genetic Manipulation) Russian Ministry of Healthcare and Social DevelopmentSFDA (State Food and Drug Administration of China) SMC (Scottish Medicines Consortium) The Fund for Promotion of Small Innovative Enterprises in Science and TechnologyThe IGI (Innovative Genomics Initiative)The Innovative Genomics Initiative The Walter and Eliza Hall Institute The Wellcome Trust Sanger Institute WFH (World Federation of Hemophilia)WHO (World Health Organization)

To see a report overview please e-mail Sara Peerun on sara.peerun@visiongain.com

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SOURCE Visiongain

Original post:
Visiongain Report: The Gene Therapy Market is Projected to Grow at a CAGR of 32% in the First Half of the Forecast Period - Yahoo Finance

WASHINGTON, April 15, 2020 /PRNewswire/ --Vanda Pharmaceuticals Inc. (Vanda) (Nasdaq: VNDA) today announced the initiation of the CALYPSO program to study the role that human genetic variations play in SARS-CoV-2 ("COVID-19") infection and disease progression. As a part of the CALYPSO program, Vanda will collaborate with University of Washington School of Medicine and its Virology Lab on a pharmacogenetics study in patients with COVID-19. The study will focus on the sequencing of the genome of individual patients, as well as the COVID-19 virus, and the identification of genetic factors that correlate with disease progression and outcomes.

In support of this study, Vanda and UW Medicine plan to collect Whole-Genome Sequencing ("WGS") data from over 1,000 patients with COVID-19 infection, and perform Viral Genome Sequencing, which should enable Vanda and the UW Medicine Virology Lab to explore host susceptibility, associations of WGS with clinical outcomes and severity of disease, as well as host-virus interactions. The study is scheduled to begin enrollment in the coming weeks and will be open to patients in hospitals and clinics around the United States.

"We look forward to the advancement of our program and the opportunity to work with and leverage the expertise of UW Medicine to expand our understanding of the COVID-19 infection mechanism," said Mihael H. Polymeropoulos, M.D., President and Chief Executive Officer of Vanda.

"The study has the potential to provide new insights into virushost interactions that could lead to more effective public health strategies and the design and development of vaccines and therapeutics," said Sandra P. Smieszek, Ph.D., Head of Genetics at Vanda. "With the vast amount of data we expect to collect, the team will aim to discern the factors associated with severity and other critical, clinical characteristics of the infected individuals."

"By leveraging our sequencing expertise and capabilities in collaboration with Vanda, we will be able to provide the necessary insight for potentially life-saving solutions for patients," said Alex Greninger M.D., Ph.D., M.S., M.Phil., Assistant Professor, Laboratory Medicine, Assistant Director, Virology Division at the University of Washington School of Medicine. "We believe this collaboration will help answer critical questions and hopefully outcomes in the fight against COVID-19."

"We are grateful to collaborate with Vanda as we try to find better ways to care for people currently suffering from COVID-19, and as we develop plans for the next phase of the national response," said Keith R. Jerome, M.D., Ph.D., Head of Virology Division at the University of Washington School of Medicine. "The approach of combining host and viral genomics to identify the most promising treatments may serve as a model for future efforts around the world. This unique agreement positions UW Medicine and Vanda for potentially changing the course of the COVID-19 pandemic."

"This is the type of collaboration we need to bring solutions to patients suffering in this time of crisis," said Dr. Greninger. "We look forward to getting this important work underway."

About Vanda Pharmaceuticals Inc.

Vanda is a leading global biopharmaceutical company focused on the development and commercialization of innovative therapies to address high unmet medical needs and improve the lives of patients. For more on Vanda Pharmaceuticals Inc., please visit http://www.vandapharma.com and follow us on Vanda's Twitter and LinkedIn.

About UW Virology

The UW Virology is one of nine divisions comprising the Department of Laboratory Medicine at the University of Washington School of Medicine. The UW Medicine Virology Clinical Laboratories perform diagnostic testing for a full range of human pathogens including respiratory viruses, herpes group viruses, HIV, hepatitis, and enteric viruses, and was one of the earliest providers of COVID-19 testing. The Division provides the highest quality patient care and serves as a model of excellence for clinical laboratories across the nation. Its UW Virology Lab is also recognized as a worldwide leader in virology research. UW Medicine Virology's research programs integrate the latest in computational, laboratory, and clinical research methods to advance the understanding of infectious diseases. Many past and current faculty members in the Virology Division have received prestigious awards recognizing their scientific achievements.

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Vanda Contact:

AJ Jones IIChief Corporate Affairs and Communications OfficerVanda Pharmaceuticals Inc.202-734-3400

pr@vandapharma.com

UW Medicine Contact:

Susan GreggDirector, Media Relations 206-616-6730

sghanson@uw.edu

CAUTIONARY NOTE REGARDING FORWARD LOOKING STATEMENTS

Various statements in this release are "forward-looking statements" under the securities laws. These forward-looking statements include, without limitation, statements regarding the design, enrollment and anticipated findings of the CALYPSO program, the promotion of more effective public health strategies and the design and development of vaccines and therapeutics. Forward-looking statements are based upon current expectations that involve risks, changes in circumstances, assumptions and uncertainties. Important factors that could cause actual results to differ materially from those reflected in Vanda's forward-looking statements include, among others: Vanda's ability to enroll patients for, and successfully conduct, the study described in this press release; the ability of Vanda, either alone or with its partners, to process the data collected and subsequently develop effective vaccines or therapeutics; the ability to obtain FDA approval of any such vaccines or therapeutics; and other factors that are set forth in the "Risk Factors" and "Management's Discussion and Analysis of Financial Condition and Results of Operations" sections of Vanda's annual report on Form 10-K for the fiscal year ended December 31, 2019, which is on file with the SEC and available on the SEC's website at http://www.sec.gov. Additional factors may be set forth in those sections of Vanda's annual report on Form 10-Q for the fiscal quarter ended March 31, 2020, to be filed with the SEC in the second quarter of 2020. In addition to the risks described above and in Vanda's annual report on Form 10-K and quarterly reports on Form 10-Q, other unknown or unpredictable factors also could affect Vanda's results. There can be no assurance that the actual results or developments anticipated by Vanda will be realized or, even if substantially realized, that they will have the expected consequences to, or effects on, Vanda. Therefore, no assurance can be given that the outcomes stated in such forward-looking statements and estimates will be achieved. All written and verbal forward-looking statements attributable to Vanda or any person acting on its behalf are expressly qualified in their entirety by the cautionary statements contained or referred to herein. Vanda cautions investors not to rely too heavily on the forward-looking statements Vanda makes or that are made on its behalf. The information in this release is provided only as of the date of this release, and Vanda undertakes no obligation, and specifically declines any obligation, to update or revise publicly any forward-looking statements, whether as a result of new information, future events or otherwise.

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INTRODUCTION

Interplanetary space is populated by densely ionizing particle radiation not naturally present on Earth (1). Life on Earth has evolved under the protection of a geomagnetic field, which deflects high-charge, high-energy (HZE) ions; however, the constant flux of HZE ions in deep space is essentially impossible to shield, making astronaut exposures inevitable (2).

In the absence of human epidemiological data for exposures to HZE radiation, uncertainties surround the cancer risk estimates for space flight crews that venture beyond low Earth orbit. The current NASA space radiation cancer risk model is built largely upon epidemiological data from the survivors of the Hiroshima and Nagasaki atomic bombings, a cohort of individuals exposed predominantly to -rays (35), a form of photon radiation. One key assumption in this NASA model is that the spectra of tumor types, and their biologic behaviors, will be similar for individuals exposed to ionizing radiation, whether particle or photon. However, notable physical differences exist between ionizing photon and particle radiation, and these physical differences translate to unique ionization and damage patterns at the molecular, cellular, and tissue levels. HZE ion exposures produce spatially clustered DNA double-strand breaks, along with other DNA lesions in close proximity to break sites (6). In contrast, -rays produce sparse ionization events that are random in spatial distribution and less likely to have additional DNA lesions immediately adjacent to the break sites. Other assumptions in the model are that radiogenic tumors are no more lethal than their sporadic counterparts and that females are at greater risk for radiogenic cancers than males (7).

In assessing cancer risks to astronauts, the premise that HZE ion exposures increase the risk for the same types of tumors that arise in human populations exposed to -rays is supported by the few animal studies of HZE ion carcinogenesis conducted to date (8). These studies, conducted on genetically homogeneous animals, have demonstrated that tumor types arising in HZE ionirradiated animals are the same as those that occur spontaneously in these animals or following exposure to photon radiation (8). However, all previous data are from either inbred mice (9, 10) or rats (11), F1 hybrid mice (12, 13), or rat stocks with limited genetic heterogeneity (11, 1416), and the tumor types that arise in inbred rodents are determined, in very large part, by their genetic background. Therefore, the spectrum of tumors that might arise in a genetically diverse population exposed to HZE ions is unknown.

With the emergence of multiparent outbreeding strategies that produce highly recombinant mouse populations with allelic variants from multiple founder strains (1719), it is possible to model the effects of population diversity in carcinogenesis studies by minimizing the overwhelming effects of genetic background and increasing the phenotypic repertoire available within a test population. These populations also allow for high-precision genetic mapping (18, 20). Quantitative trait locus (QTL) mapping is a powerful forward-genetics approach that allows for unbiased testing of genetic variants that may influence gene-environment interactions for radiation effects (21, 22). Highly recombinant populations were constructed for the purpose of mapping complex traits, and QTL can often be resolved to megabase resolution (1820). In addition, complete sequence information can be used on genotyped individuals by imputing the substantial genomic resources available for the founder strains.

Studying tumors that arise in irradiated, genetically diverse mouse populations presents a unique opportunity to test key assumptions of the NASA risk model, particularly whether HZE ions induce the same tumors by the same mechanisms as -rays. If so, the current practice of extrapolating human epidemiological data from individuals exposed to -rays to astronauts exposed to HZE ions would be a valid approach for risk calculation in the space radiation environment.

To study the effects of HZE ion irradiation in a genetically heterogeneous population, 1850 HS/Npt stock mice (23) of both sexes were genotyped for 77,808 single-nucleotide polymorphism (SNPs) and exposed to (i) 0.4 gray (Gy) of 28Si ions (240 MeV/n) [linear energy transfer (LET), 80 keV/m; = 0.031 particles/m2] or (ii) 56Fe ions (600 MeV/n) (LET, 181 keV/m; = 0.014 particles/m2), (iii) 3 Gy of 137Cs -rays, or (iv) sham irradiation. We chose 56Fe ions because of their high abundance in galactic cosmic radiation (GCR) and because their high charge (Z = +26) makes them particularly damaging (24). The 28Si ions were selected because their LET more closely approximates the dose average LET of secondary fragments generated by GCR penetrating an aluminum spacecraft hull (25). The mice were monitored daily until they reached 800 days of age or became moribund. Comprehensive necropsies were performed on each mouse and involved all organ systems. Each detected lesion was characterized histologically by a board-certified veterinary pathologist. Tumors were the predominant cause of morbidity and mortality for both HZE ionirradiated (n = 622) and -rayirradiated (n = 615) populations as well as for the population of unirradiated mice (n = 613). Overall life span was significantly reduced for irradiated populations (Fig. 1A), which can be attributed to the increased incidence and decreased median survival for radiation-induced tumors. For irradiated mice, populations exposed to 0.4-Gy HZE ions had increased survival times compared to mice exposed to 3.0 Gy of -rays (Fig. 1A). Although these doses seem disparate, their selection is based on preliminary dose-response studies (26), which reveal that 0.4 Gy of HZE ions and 3.0-Gy -rays are each maximally tumorigenic.

Overall survival for HS/Npt mice, plotted as Kaplan-Meier survival, is presented for each exposure group (A). The incidence of specific tumor histotypes (B) and median survival times for these tumors (C) are plotted for each exposure group, which demonstrates that certain tumor types occur at an increased frequency following exposures to radiation of specific qualities and survival times in irradiated mice are decreased for some tumor types. The incidence of specific tumor histotypes within HS/Npt families is plotted for unirradiated (D), -rayirradiated (E), and HZE ionirradiated families (F) and demonstrates that specific tumor types often occur at very high incidence within some families and not at all in others, indicating heritability of tumor susceptibility. Furthermore, adjacent families are more closely related, and tumor incidences, for example, family 23 and adjacent families, have a high incidence of B cell lymphoma. The 47 HS/Npt families are arranged along the x axis (D to F).

A wide variety of tumor diagnoses [82 distinct tumor histotypes (table S1)] were observed in HS/Npt mice. Although most of these tumor types were rare, 18 histotypes were observed at incidences greater than 1%. Overall, the spectra of tumor histotypes produced in genetically diverse populations exposed to HZE ions and -rays were similar (Fig. 1B). Furthermore, tumor types induced by radiation were generally similar to those arising spontaneously in HS/Npt mice; however, radiation-exposed populations demonstrated decreased median survival times associated with tumor development (Fig. 1C and figs. S7 to S22) and increased incidences for specific tumor types, such as leukemias and Harderian gland adenocarcinomas, following radiation (Fig. 1B). The structure of the HS/Npt population can be divided into families that consist of mice more closely related to one another. Many tumor histotypes show high incidences within some families but are absent or rare in others (Fig. 1, D to F), which is consistent with genetic susceptibility to certain tumor types. Furthermore, certain tumorsparticularly lymphomas, pulmonary adenocarcinomas, hepatocellular carcinomas, Harderian gland tumors, and myeloid leukemiasdemonstrate a periodicity in tumor incidence (Fig. 1, D to F) where adjacent families often display similar incidences, which could be predicted on the basis of the circular breeding design used to generate HS/Npt, in which adjacent families are more related to one another than families further removed.

Although the tumor spectra are similar for each irradiated population, the different radiation qualities demonstrate varied efficiencies for producing specific tumor histotypes. -rayirradiated mice were at greater risk for myeloid leukemia, T cell lymphoma, pituitary tumors, and ovarian granulosa cell tumors than unirradiated mice; HZE ionirradiated mice demonstrated an intermediate susceptibility to these histotypes (Fig. 1B). For Harderian gland tumors, thyroid tumors, hepatocellular carcinomas, and sarcomas, HZE ion and -rayirradiated mice were at a similarly and significantly increased risk compared to unirradiated controls (fig. S7 to S22).

NASA permissible exposure limits for radiation limit the number of days an astronaut can spend in space based on modeled cancer risk. These limits are different for men and women (27) due primarily to epidemiological data that indicate that women are at greater risk for radiogenic cancers than men due to their longer life spans and susceptibility to specific cancer types, such as lung, ovarian, and breast carcinomas. Female HS/Npt mice have longer life spans than males (P = 2.7 106, log-rank test), with unirradiated females living 43 days longer (686.1 days), on average, than males (643.2 days) (fig. S1A). In contrast, no survival difference is observed between -rayirradiated females and males (P = 0.51) or HZE ionirradiated females and males (P = 0.06), indicating that female HS/Npt mice are more susceptible to radiation-induced morbidities and mortalities than males (fig. S1, B and C). Irradiated female mice had increased incidences of (i) ovarian tumors, (ii) mammary tumors, (iii) central nervous system tumors (pituitary adenomas, choroid plexus tumors, and ependymomas), (iv) diffuse large B cell and lymphoblastic B cell lymphomas, (v) osteosarcomas, and (vi) leiomyosarcomas (fig. S1D). Female mice were at lower risk for radiogenic lung cancer (fig. S1D and table S1), which is a major contributor to limiting flight time for female astronauts. Modeling risk by sex in humans has been confounded by different smoking rates between men and women in the atomic bomb survivor cohort (28).

To determine whether the genetic variants that increase tumor susceptibility following -ray irradiation also increase tumor susceptibility following HZE ion irradiation, genome-wide association mapping was performed for 18 tumor types in which there was an incidence of greater than 1%. Genomes were reconstructed for each mouse using a probabilistic model to predict founder haplotypes from high-density genotype data (18). Reconstructed genomes represent the unique accumulation of meiotic events for each individual and form a scaffold for the imputation of known sequencing information from the eight parental inbred strains. Polygenic covariance among related individuals is of significant concern in multiparent crosses and was corrected for during QTL mapping with a kinship term (18, 29). Mapping was performed for each phenotype using both a generalized linear mixed-effects model and proportional hazards regression model with the aforementioned kinship to adjust for polygenic covariance between related mice. To determine the significance thresholds for a model in which no QTL is present, the phenotypes were permuted, the regression model was run, and the maximum statistic was retained from each permutation (30). The 95% significance threshold was minimally variable between phenotypes with a mean threshold of log(P) > 5.8, and this value was used to identify significant associations. This is consistent with the estimated 0.05 Bonferroni genome-wide corrected threshold of log(P) > 6.0, which is considered overly conservative for QTL mapping (30).

At least one QTL was identified for 13 of the 18 tumor phenotypes examined. For tumor incidence, 35 QTL were identified with an average confidence interval of 3.4 Mb (table S2). For QTL at the 95% confidence threshold, effect sizes average 3.7% of the phenotypic variance with a range of 0.75 to 7.46%. For most of the tumors, the genetic architecture was complex with multiple QTL individually explaining a small proportion of the total variance. Although loci with moderate effects on the phenotype were most common, 11 large effect QTL were observed for seven tumor histotypes, with effect sizes greater than 5% (table S2).

To determine potential effects of genetic variants on tumor latency following irradiation, mapping was also performed using proportional hazards regression model (table S3) and 38 QTL were identified for 12 tumor types. QTL associated with tumor survival times mirrored those identified for tumor incidence, indicating that the genetic variants that control susceptibility to radiation-induced tumors also determine latencies.

Neoplasia is a binomially distributed trait, and therefore, the power to detect significant associations is primarily dependent on tumor incidence and QTL effect size. This leads to important considerations for the ultimate goal of this analysis, which is to determine similarities between QTL for specific neoplasms in populations exposed to different qualities of radiation. For some tumor types, a significant peak was observed in one exposure group with a suggestive peak present at the same locus in the alternative exposure group. We speculate that the reason certain radiation qualities produce only suggestive QTL for certain tumor phenotypes is likely due to decreased mapping power as a result of the variation in incidence between groups. In these cases, if the peak was more significant when combining radiation groups, the QTL was considered significant for all irradiated animals regardless of radiation quality.

Thyroid tumors are a well-known radiation-induced entity for both humans and mice; however, relatively little is known about genetic variants that increase susceptibility to this disease in mice. In HS/Npt mice, spontaneous thyroid adenomas occurred at relatively low frequencies and had a uniformly late onset, with tumors occurring between 700 and 800 days of age (Fig. 2A). In contrast, thyroid tumors arising in HZE ion or -rayexposed mice occur with significantly earlier onsets, with tumors arising as early as 250 days of age (Fig. 2A).

Thyroid follicular adenoma Kaplan-Meier survival estimate (A) along with genome-wide association plots for thyroid adenoma in HZE ionirradiated, -rayirradiated, HZE ion and -rayirradiated, and unirradiated mice (B) and an expanded plot for chromosome 2 (C), which contains the most significant association locus; gray lines indicate 95% (upper line) and 90% confidence (lower line) for log10(P values). Genome-wide association results reveal significant results in HZE ion and -rayirradiated mice that are further bolstered by combining the groups. The top panel of (D) shows strains that contribute the reference allele for the SNPs highlighted in red in the middle panel, indicated by vertical lines (D); the C57BL/6J strain contributes an allele that differs significantly from the other seven strains. The middle panel shows the log10(P value) of each SNP in the interval (D); the most significant SNPs are highlighted in red, and the bottom panel lists genes within the QTL interval. Genes that contain splice site, missense, or stop-related SNPs are colored red (D). Resample model averaging was performed within chromosome 2 to compare the distribution of peak log10(P values) for each exposure group (E); there is broad overlap for HZE- and -rayirradiated mice, and grouping all irradiated mice together further narrows the distribution of peak log10(P values). Mbp, megabase pair.

Association mapping reveals a significant 3.4-Mb interval on chromosome 2 for HZE ionexposed animals (Fig. 2, B and C). The same locus is identified in the -rayirradiated population if the significance threshold is decreased to a level at which 30% of identified QTL will be false positives. Combining both irradiated populations markedly increases the significance of the QTL identified on chromosome 2. The QTL interval (119 to 125 Mb) contains 39,179 SNPs (Sanger Mouse Genomes, REL-1505) and 142 genes (Ensembl version 85) (Fig. 2D). Within the QTL region, the C57BL/6J parental strain contains an introgression from the Mus musculus musculus genome (31); we found that HS/Npt mice carrying the C57BL/6J haplotype at the QTL have increased thyroid tumor incidence regardless of whether they are exposed to HZE ions or -rays.

To further explore the possibility that the QTL identified on chromosome 2 controls susceptibility following -ray and HZE ion exposures, we used a nonparametric resample model averaging procedure (32) across the entire chromosome to identify genomic loci that consistently reappear in resampled populations. Briefly, genome scans are repeated for each new dataset created, in which some individuals may be sampled more than once and some not at all (32). Resample model averaging consistently identifies the same locus for all groups of mice, regardless of radiation exposure (Fig. 2E). Furthermore, the resample model averaging procedure identifies the same locus for tumors arising spontaneously (Fig. 2E). Data from this tumor phenotype indicate that the same inheritable genetic variants contribute to an individuals risk of developing thyroid cancer, regardless of radiation exposure.

Acute myeloid leukemia (AML) is another common radiation-induced tumor in both mice and humans (33, 34). In concordance with previous studies conducted with inbred mice (26), -ray exposures in HS/Npt mice are more efficient at inducing AML than HZE ion exposures. In our -irradiated mice, 15.6% (96 of 615) developed AML compared to 2.9% (18 of 622) of those exposed to HZE ions and 1.6% (10 of 613) of unirradiated mice. AML median survival times were similar for all groups (Fig. 3A). Association mapping revealed a significant QTL for the -irradiated population on chromosome 2 that reached the 95% confidence threshold (Fig. 3, B and C), but no QTL was observed for the HZE ionexposed population, in which the incidence of AML was much lower. However, when grouping HZE ion and -rayirradiated mice together, the same QTL was significantly bolstered (Fig. 3B). If the susceptibility alleles identified at this locus were only contributing to disease following -ray irradiation and were, therefore, randomly distributed among the affected mice in the HZE ionexposed group, then we would expect the log10(P values) to decrease when combining -irradiated mice; however, the log10(P value) for this locus significantly increases when repeating the mapping procedure included all irradiated mice.

(A) Kaplan-Meier plots for myeloid leukemia demonstrate similar median survival estimates for myeloid leukemia between groups. (B) Genome-wide association procedures identify a narrow QTL on chromosome 2; two gray lines indicate 95% (upper line) and 90% confidence (lower line) for log10(P values). Expanded mapping results are depicted in (C) along with contributing strains for the reference allele. The A/J, AKR/J, C57BL/6J, DBA/2J, and LP/J strains contribute alleles that differ from the other strains, indicated by vertical lines in the top panel (C). The middle panel shows the log10(P value) of each SNP in the interval. The most significant SNPs are highlighted in red. The bottom panel shows the genes in the QTL interval. Genes that contain splice site, missense, or stop-related SNPs are indicated in red. Copy number results for Spi1 and Asxl1 in splenic samples from mice diagnosed with myeloid leukemia are plotted by exposure group (D).

Radiation-induced AML is a well-characterized disease in mice (10, 35, 36) and is most commonly the result of a radiation-induced minimally deleted region on chromosome 2 containing the PU.1 gene (current murine nomenclature, Spi1) and a recurrent point mutation that inactivates the remaining Spi1 allele (37). Figure 3C depicts mouse chromosome 2 with the positions of the QTL identified in our irradiated mice and the Spi1 gene. To test the hypothesis that AMLs occurring in HZE ionexposed animals will contain the same molecular aberrations know to occur in AML arising in -rayexposed mice, the copy number for Spi1 was investigated in leukemia samples to assess for deletions. As expected, most of the leukemias occurring in -rayexposed mice had a deletion in one copy of Spi1. In contrast, Spi1 deletions in spontaneously occurring AML were less common (Fig. 3D). Similar to -rayirradiated mice, leukemias that developed in mice exposed to HZE ions, although fewer in number, also have an increased incidence of Spi1 deletion. This finding indicates that AML arises by similar molecular mechanisms following exposures to HZE ions or -rays.

Because the QTL identified on chromosome 2 is approximately 60 Mb from the commonly deleted region containing Spi1 and because radiation-induced deletions can be notoriously large, we considered the possibility that the identified QTL was also deleted in these leukemias, resulting in loss of one copy of the QTL region. To test this hypothesis, we determined the copy number for a gene located at distal to the QTL support interval, Asxl1. As expected, we found that Asxl1 was not deleted in any sample in which Spi1 was not deleted; however, in 69% of cases with a Spi1 deletion, Asxl1and presumably the entire QTL regionwas also deleted (Fig. 3D). This demonstrates that most of the radiation-induced AML cases arose from progenitor cells haploinsufficient for the entire QTL region.

HZE ion and, to a lesser extent, -ray irradiation were particularly effective in inducing Harderian gland tumors at the doses used in this study, which was expected on the basis of extensive published radiation quality data on these tumors (8, 38). In the HZE ionirradiated group, Harderian gland tumors were observed in 22.7% (221 of 622) of mice and 3.2% (20 of 622) were malignant. In the -irradiated group, 15.3% (94 of 615) of mice developed Harderian gland tumors and 2.7% (17 of 615) were malignant. In contrast, spontaneous Harderian gland tumors occurred in only 4.1% (25 of 613) of unirradiated mice and 0.7% (4 of 613) were malignant. Despite the differences in tumor incidences following irradiation, median survival times for Harderian gland adenocarcinoma were similar for all groups (HZE ion, 582 days; -ray, 571 days; and unirradiated mice, 571 days).

Two QTL were observed for Harderian gland adenocarcinomas in HZE ionirradiated mice, one on chromosome 4 and another on chromosome 9 (Fig. 4A). The 1.7-Mb interval identified on chromosome 4 (Fig. 4B) is similar to previously discussed QTL regions in that combining both irradiated populations markedly increases the significance of this locus, which suggests that this QTL is associated with Harderian gland adenocarcinoma susceptibility in both HZE ion and -rayirradiated mice. In contrast, a 2.3-Mb QTL interval on chromosome 9 is observed only in HZE ionirradiated mice, and the locus is absent when combining all irradiated mice and repeating the mapping procedure (Fig. 4C). To further evaluate these QTL, resample model averaging was performed within chromosomes 4 and 9 to determine the distribution of peak log10(P values) along each chromosome. For chromosome 4, there is substantial spatial overlap identified in peak log10(P value) associations in the HZE ionexposed population and the -rayirradiated population, and the HZE ion and -rayirradiated population yields the most consistent identification of the QTL region (Fig. 4D). In contrast, although nearly all identified peak log10(P values) were identified in the 2.3-Mb QTL interval on chromosome 9 for HZE ionirradiated mice, the distributions of peak log10(P values) for other exposure groups do not substantially overlap and are widely distributed along the chromosome (Fig. 4E). The resample model averaging results indicate that while the chromosome 4 QTL contributes to susceptibility to Harderian gland adenocarcinomas in both HZE ion and -rayirradiated populations, the QTL identified on chromosome 9 appears to only be involved in Harderian adenocarcinoma susceptibility following HZE ion exposures.

Genome-wide association plots for Harderian gland adenocarcinoma (A) for HZE ionirradiated, -rayirradiated, HZE ion and -rayirradiated, and unirradiated mice; two gray lines indicate 95% (upper line) and 90% confidence (lower line) for log10(P values). Chromosome 4, which is expanded in (B), reveals a significant QTL associated with HZE ion irradiation, which is further increased significantly when grouping all irradiated mice (HZE ion and -ray irradiated) together, which indicated that the genetic variants in this location are important for Harderian gland adenocarcinoma following exposures to either HZE ion or -ray irradiation. In contrast, chromosome 9, which is expanded in (C), reveals a significant QTL associated only with HZE ion irradiation; this locus is absent when grouping all irradiated mice (HZE ion and -ray irradiated) together, which suggests that the allele(s) present in this region may only play a role for HZE ioninduced tumors. Resample model averaging was performed within chromosomes containing significant QTL. There is significant spatial overlap identified on chromosome 4 for peak log10(P value) associations in the HZE ionexposed population, the -rayirradiated population, and the HZE ion and -rayirradiated population that demonstrates the most consistent identification of the QTL region (D). In contrast, although nearly all identified peak log10(P values) were identified in the chromosome 9 QTL interval for HZE ion irradiated mice, the peak log10(P values) for other exposure groups are widely distributed along the chromosome (E).

In addition to looking for similarities between individual, selected QTL for HZE ion and -rayexposed populations, we also sought a more holistic method in which entire genome-wide association results could be compared between groups in an unsupervised process. We used hierarchical clustering to create cluster dendrograms using entire genome-wide scans for a given phenotype. By considering results from genome-wide associations, rather than individualized peaks observed within genome-wide associations, we submit for comparison not only highly significant QTL regions but also the numerous loci detected with lower confidence.

Unsupervised hierarchical clustering of genome scans creates significant clustering events that often occur for the same histotype regardless of radiation exposure (Fig. 5A). Multiple tumor histotypesincluding mammary adenocarcinoma, thyroid adenoma, and hepatocellular carcinomacluster by histotype, regardless of radiation exposure. To demonstrate and validate the methodology of QTL clustering, genome-wide scans for coat colors in each treatment group are evaluated and coat color genome-wide scans cluster together, as expected (Fig. 5B). These results further support the hypothesis that host genetic factors are highly important in determining risk of radiation carcinogenesis, whether following HZE ion or -ray exposures.

(A) Unsupervised hierarchical clustering of genome-wide association scans for tumor phenotypes reveals that the most significant clustering events often occur for the same histotype regardless of radiation exposure; these include mammary adenocarcinoma, thyroid adenoma, and hepatocellular carcinoma. (B) As expected, clustering genome scans for coat color demonstrates the expected results: that genome scans cluster together despite exposure group. The green line represents the 99% confidence level of the most significant dendrogram heights by permutations (log10 values permuted with genetic markers) to determine a distribution of dendrogram heights under the null hypothesis that no associations exist (C), demonstrating that the observed clusters are highly unlikely to occur randomly.

Permissible exposure limits for astronauts are based on the risk of death from cancer rather than cancer development, and the incidence to mortality conversion used in the risk calculation uses spontaneously occurring cancers in the U.S. population. Thus, there is an assumption that radiogenic tumors are no more lethal than spontaneous tumors. To determine whether tumors that arise following HZE ion exposure are more malignant than their counterparts arising in unirradiated or -rayirradiated mice, metastatic disease was characterized for each group. Pulmonary metastases were consistently observed in cases of hepatocellular carcinoma, Harderian gland adenocarcinoma, osteosarcoma, and ovarian granulosa cell tumor. Metastases were no more frequent in irradiated animals than in controls, and there was no significant difference in metastatic incidence between HZE ionirradiated mice and -rayirradiated mice (fig. S5A), and pulmonary metastatic density is similar between groups (fig. S5, B to D).

Tumor latency following irradiation was compared between exposure groups using survival statistics. Differences in tumor latency in this context indicate a decrease in time for tumor initiation or promotion. Since radiation is efficient at both initiation and promotion, decreased latencies are expected for irradiated population. Tumor progression is not evaluated, and our results therefore do not demonstrate whether tumors arising in irradiated individuals are more likely to progress rapidly than those arising spontaneously. As expected, tumors arising in both HZE ion and -rayirradiated mice show significantly decreased latencies in comparison to the unirradiated population (fig. S7 to S22). However, HZE ions did not further decrease latencies when compared to -rayirradiated mice.

Carcinogenesis as a result of space radiation exposure is considered the primary impediment to human space exploration (2). Compared to forms of radiation found naturally on Earth, including x-rays, -rays, and particles, HZE ions in space are much more difficult to shield (2) and have a distinct ionization pattern that aligns along dense track structures, resulting in clustered damage to chromatin (6). Because HZE ions, a highly penetrating component of GCRs, are not amenable to shielding (28, 29), exposure risks are inherent to manned missions in interplanetary space, but estimating the risk associated with this unique form of particle radiation is complicated by the essential lack of data for human exposures (28). As a substitute, human exposure data from other forms of ionizing radiation, primarily -ray (35) photon radiation, are used in cancer risk models with the assumption that photon and particle radiation have qualitatively comparable biological effects.

Animal models are a vital component in determining the validity of the extrapolation of human terrestrial radiation exposure data to exposures that will occur in astronauts in the space radiation environment. To date, carcinogenesis studies designed to evaluate the effects of HZE ions have used rodents with limited genetic heterogeneity (916). The advantage of removing genetic variability in animal models is the consequent decrease in phenotypic variability, which allows for fewer individuals to detect potential environmental effects on phenotype; the disadvantage is that strain-specific responses in genetically identical populations are significant and can obscure the variability that one might expect in a diverse population, such as humans. By using a genetically diverse population with a wide range of tumor susceptibilities, the spectra of tumors that occur following exposures to particle and photon radiation can be compared. The results of this study indicate that the spectrum of tumor histotypes observed in a genetically diverse population exposed to particle radiation is not unique to that observed in a population exposed to photon radiation or to the tumor spectrum observed in an unirradiated population. Despite the similarities observed in tumor spectra following radiation exposures, the radiation qualities and doses used for this study have unique efficiencies at producing specific tumor types, and while this work demonstrates that the underlying genetics of susceptibility can be similar for tumorigenesis following both high- and low-LET radiation, further work is necessary to define risks for specific tumor histotypes based on exposures.

This study uses a highly recombinant mouse population (HS/Npt stock) that is genetically diverse and designed for genome mapping (1921, 23), a forward-genetics approach that allows for an unbiased search of the entire genome for genetic associations. In contrast, genetically engineered mouse models rely on a reverse-genetics approach in which a given gene is first altered and the resulting phenotypes are then characterized. Studies using forward-genetics are most informative in populations that contain abundant genetic and phenotypic diversity. HS/Npt mice are a multiparent cross derived from eight inbred strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6J, DBA/2J, and LP/J); each individual contains a unique mosaic of founder haplotypes and a high degree of heterozygosity, and recombination events become increasingly dense with each generation. Our population of HS/Npt mice was obtained from generation 71 of circular outbreeding. Creating these populations is not trivial and has been a central goal of communities involved in genetics research over the past few decades, resulting in the creation of rodent populations ideal for genome mapping (1820, 3942).

Genome mapping allows the discovery of QTL associated with susceptibility to complex traits, such as radiogenic cancers; this approach is uniquely suited to comparing inheritable risk factors for cancers following exposures to unique carcinogens, such as particle and photon radiation. In broader terms, this work demonstrates the utility of highly recombinant mouse models created for genetic mapping in carcinogenesis studies, an application that has not been previously attempted. Mapping QTL in carcinogenesis studies provides inherent challenges due to the structure of binomial data, potential confounding causes of death following irradiation and aging, the fundamental stochastic nature of radiation tumorigenesis, and incomplete penetrance of potential allelic variants. Despite these challenges, we were able to map QTL for 13 neoplastic subtypes and many of these identified loci are previously unidentified.

At the doses used in this study, HZE ions appear to be less effective than -rays in inducing precursor T cell lymphoblastic lymphoma (pre-T LL) and ovarian tubulostromal adenomas and granulosa cell tumors. This may be due to a combination of dose inhomogeneity in HZE ionirradiated tissues and the major role cell killing plays in the etiology of these specific tumors. pre-T LL can be prevented by transplanting irradiated mice with unirradiated syngeneic bone marrow cells or by shielding some of their bone marrow during irradiation (43, 44). The underlying mechanism by which unirradiated bone marrow cells suppress lymphomagenesis may involve a cell competition process by which older T cell progenitors resident in the thymus are normally replaced by fresh progenitors that immigrate from the bone marrow. Radiation kills these fresh bone marrow cells or reduces their fitness, which, in turn, prolongs the time that older T cell progenitors already in the thymus survive and self-renew. This, along with the increased proliferative cycles of the older T cell progenitors needed to maintain production of mature T cells, results in a corresponding increase in the oncogenic mutations that they accumulate and a concomitant increase in lymphomagenesis (45). Replenishing dead or damaged bone marrow cells by transplantation or preventing their damage through shielding suppresses lymphomagenesis.

At the 3-Gy dose of -rays used in this study, all of the bone marrow cells are uniformly irradiated. This is not the case for HZE particle radiation. The average diameter of a murine bone marrow cell nucleus is around 6 m (46). At the fluence of HZE ions used in this study, the probability that a 6-m-diameter nucleus will be traversed by a 28Si ion and a 56Fe particle is 0.88 and 0.40, respectively. On the basis of a Poisson distribution, the probabilities of a nucleus not being traversed at all are 0.41 and 0.67 for 28Si and 56Fe irradiation, respectively. Thus, many of the T cell progenitors in the bone marrow are not irradiated (although they receive a small dose from -rays). These cells should exert a protective effect similar to transplanting unirradiated bone marrow cells or shielding some of the bone marrow during irradiation, rendering HZE ions less efficient for lymphomagenesis. Given that most of the pre-T LL in the HZE ionirradiated group are likely spontaneous, it is expected that they cluster more closely to spontaneous pre-T LL than to -rayinduced pre-T LL.

The mechanism leading to murine tumors of ovarian surface epithelium origin is well understood. Loss of primordial follicle oocytes by radiation-induced apoptosis results in a decrease in estrogen production, which, in turn, leads to elevated levels of follicle-stimulating hormone (FSH) and luteinizing hormone (LH) in the circulation. FSH and LH drive proliferation of ovarian surface epithelium cells (47). Ovarian tumors can be induced in some animal models by artificially manipulating levels of these hormones (4749). Irradiated mice can be protected from tubulostromal adenomas and granulosa cell tumors by shielding one ovary during irradiation or by transplanting the mice with an unirradiated ovary (50, 51); these interventions protect some oocytes and thereby maintain proper regulation of FSH and LH levels.

Assuming that the target cells are primordial follicle oocytes with a diameter of 12 m, the probabilities of no traversals are 0.2 for 56Fe and 0.03 for 28Si at the 0.4-Gy dose used here. The probabilities for one or fewer traversals are 0.52 for 56Fe and 0.14 for 28Si. Whether a sufficient number of follicles survive at 0.4 Gy to account for the observed ovarian tumor sparing is unknown. Mishra and colleagues (52) observed a dose-dependent decrease in primordial stage follicles in C57BL/6 mice 8 weeks after irradiation with 56Fe ions (600 MeV/n). Sixteen percent of the follicles survived at the 0.3-Gy dose, and normal levels of serum FSH and LH were present; at 0.5 Gy, only 1% of the follicles survived and an increase in serum FSH was observed. Caution is needed in using Mishras results in interpreting our own since we used mice with different genetic backgrounds and the FSH and LH levels in the 0.3 Gyirradiated mice may increase relative to unirradiated controls if time points beyond 8 weeks are assayed. In any event, microdosimetric effects should be incorporated into any risk model for tumors in which cell killing plays a prominent role.

The location of the chromosome 2 QTL in a region frequently deleted in radiogenic AMLs may be happenstance, but there are scenarios in which its chromosomal location would be crucial to its function. One possibility is that the polymorphism increases the frequency of AML-associated chromosome 2 deletions in irradiated hematopoietic cells by controlling the spatial confirmation of the chromosome such that the proximal and distal deletion breakpoints are in close proximity to one another (46). This type of proximity mechanism has been evoked to explain recurrent chromosomal rearrangements seen in radiation-induced papillary thyroid carcinoma and some spontaneous cancers (53, 54). In this scenario, the QTL could be a structural polymorphism (e.g., segmental duplication or interstitial telomeric sequence), which would affect chromosomal conformation, yielding a different conformation in susceptible mouse strains than resistant strains. Structural polymorphisms are easily missed in the assembly of the strain-specific genomic sequences used for mapping studies, so we would be unaware of its existence. A second possibility is that the polymorphism is in a gene needed for myeloid progenitor cell survival. Mouse strains resistant to myeloid leukemia would have a hypomorphic allele of this gene. If one copy is lost (i.e., through radiation-induced deletion), then the remaining copy would be insufficient for cell survival. Thus, in mouse strains resistant to radiogenic AML, a chromosome 2 deletion, which is the first step in radiation leukemogenesis, is a lethal event and leukemogenesis is thereby halted. Susceptible strains would have a fully functional allele of the gene, so that if one copy is deleted, the remaining copy maintains cell viability, allowing further leukemogenic events to occur (46). A caveat to both the chromosome conformation and haploinsufficiency scenarios is that the chromosome 2 deletions mapped in radiogenic AMLs from the F1 progeny of AML-susceptible CBA/H mice and AML-resistant C57BL/6 mice do not occur preferentially in the CBA/H origin chromosome (55). However, in that study, only 10 tumors were informative. In addition, susceptibility to radiogenic AML is multigenic, so it is possible that the difference in susceptibility between the CBA/H and C57BL/6 strains is not due to the chromosome 2 QTL.

HZE ions seem particularly effective in inducing Harderian gland tumors at the doses used in this study. This result was expected on the basis of extensive published radiation quality data on these tumors (8, 38). The mechanism responsible for higher tumorigenic efficacy of HZE ions relative to -rays is unknown; however, we have identified a QTL associated with Harderian gland adenocarcinoma following HZE ion exposures that does not appear to lend susceptibility to the same tumor following -ray exposures (Fig. 4C). Furthermore, HZE ioninduced Harderian gland adenomas and adenocarcinomas cluster away from spontaneous and -rayinduced Harderian gland tumors (Fig. 5), indicating non-overlap of some of the susceptibility loci. There are data that suggest that HZE ion irradiation has an effect on tumor promotion that -ray irradiation lacks. The observation is that pituitary isografts, which result in elevated levels of pituitary hormones, enhance the induction of Harderian gland tumors and decrease their latency in mice irradiated with -rays or fission neutrons but do not increase tumor prevalence in mice irradiated with 56Fe ions (600 MeV/n) (12). This would explain the high relative biological effectiveness (RBE) for 56Fe ions. It would also render QTLs that act in the promotion of -ray and spontaneous tumors irrelevant to HZE ioninduced tumors.

The use of unsupervised clustering on genome-wide association results is a novel approach to search for shared tumorigenic mechanisms between radiogenic and spontaneous tumors or between tumors induced by different radiation qualities. Potentially, the results could be used to inform risk modeling. For example, using the 99% confidence interval as a cutoff, thyroid adenomas, pituitary tumors, osteosarcomas, B cell lymphoblastic leukemia, mammary tumors, and hepatocellular carcinomas cluster by histotypes regardless of whether they arose in HZE ionirradiated or -rayirradiated mice. Of these, the incidences of thyroid tumors, pituitary tumors, and osteosarcomas are significantly increased following exposures to either HZE ions or -rays. Taking pituitary adenoma as an example, these findings suggest that it would be reasonable to extrapolate the risk of HZE ioninduced pituitary adenoma as a multiple of -rayinduced pituitary adenoma risk (i.e., using a relative risk model). Because there were too few spontaneous pituitary adenomas to position them on the dendrogram, we cannot determine whether the risk of HZE ioninduced pituitary adenoma could reasonably be modeled on the basis of the incidence of the spontaneous tumor. Another pattern of association is observed for Harderian gland adenoma and follicular B cell lymphoma in which, at the 99% confidence interval, spontaneous tumors cluster with -rayinduced tumors but not with HZE ioninduced tumors. There are a number of ways that this could occur. Three possibilities are as follows: (i) HZE ions act through a tumorigenic mechanism different from that of spontaneous and -rayinduced tumors. (2) HZE ions bypass the need for one or more of the genetically controlled steps required for spontaneous and -rayinduced tumors, and (iii) there are multiple pathways to tumor formation, and HZE ion irradiation forces tumorigenesis through only one (or a subset) of them. Harderian gland tumors may fall into the second possibility. As described earlier, observations on mice receiving pituitary isografts before irradiation suggest that HZE ions may have Harderian gland tumor promotion effects that -rays lack. If so, the QTL controlling those effects would be inconsequential in the tumorigenesis of HZE ioninduced Harderian gland tumors, and those tumors would cluster away from their spontaneous and -rayinduced counterparts. Whether a relative risk model, an absolute risk model, or a combination of the two would be most appropriate in Harderian gland tumor risk calculations would depend on which of the above possibilities is most accurate.

NASA seeks to limit the risk of exposure-induced death (REID) from radiogenic cancer to below 3% (56). For multiple missions aboard the International Space Station (flown in solar minimum conditions), the model projects that males will exceed permissible exposure limits at 24 months and females, at 18 months; women are considered at greater risk for radiogenic cancers than men because of longer life spans and increased susceptibility to specific cancer types, including lung, ovarian, and breast carcinomas. Because the 3% REID is derived from the upper 95% confidence interval for the risk estimate (57), decreasing the uncertainty for space radiationinduced cancers can significantly increase the flight time allowed for astronauts. The 95% confidence interval surrounding the risk estimates not only primarily reflects uncertainties in our understanding of HZE ions but also includes uncertainties surrounding dose-rate effects, transfer of risk between human populations, space dosimetry, and errors in the existing human epidemiology data. Concerning sex predilections, our results also demonstrate a sex difference in carcinogenesis risk, where female mice are at greater risk for radiogenic cancers than males, following either HZE ion or -ray exposures. These results are consistent with the current NASA model to calculate cancer risk from space radiation exposures (5).

Whether genotypic assays of radiosensitivity can improve the precision of risk assessment in humans will depend on a number of factors. One is the extent to which heritable sequence variants determine cancer risk from HZE ion exposures. HZE ion radiation exposures result in more complex molecular lesions that are less amenable to repair (58). Thus, it could be argued that sequence variants that result in subtle differences in DNA repair and damage response pathways would have a lesser impact on HZE ion radiation carcinogenesis. However, this work demonstrates that genetic susceptibility does indeed have a significant role in tumorigenesis following HZE ion exposures. Personalized approaches to cancer risk assessments may eventually allow for greater reductions in uncertainties when generating space radiation cancer risk estimates (28).

There are limitations to a mouse carcinogenesis study comparing acute -ray and HZE ion exposures. First, for cost efficiency and logistics reasons, a single dose was used for each radiation quality: 3.0 Gy for -ray exposures and 0.4 Gy for HZE ion exposures. Preliminary studies have demonstrated that these doses produce the maximum tumor incidence in inbred strains (24). Because tumor susceptibility and association mapping were the primary goals of this study, doses were chosen with the goal of generating the greatest tumor incidences and, therefore, the greatest power to detect significant QTL. However, caution must be taken when comparing the two single-dose groups, as it is impossible to untangle dose responses in such a study. An additional benefit of the selected doses is that 0.4 Gy of HZE ions represents a realistic dose, received over 20 to 30 months, for a flight crew traveling to Mars. Second, the applicability of these findings to human populations is limited, as rodents serve only as models of carcinogenesis.

The results presented here indicate that host genetic factors dictate risk for tumor development following radiation exposures, regardless of radiation quality. Therefore, at a population level, risks can be extrapolated from terrestrial exposures to the space radiation environment and at an individual level, and humans harboring susceptibility alleles for radiation-induced tumors developed on Earth are also likely at increased risk in space.

Male and female HS/Npt mice (n = 1850) were generated from breeding pairs obtained from Oregon Health and Sciences University (Portland, OR). The mice were group-housed (five mice of the same sex per cage) in a climate-controlled facility at 70F (21.1C) with free access to food (Teklad global rodent diet 2918) and sterile water and a 12-hour light cycle. Mice were shipped to Brookhaven National Laboratories (Upton, NY) where they were exposed to accelerator-produced HZE ions at the NASA Space Radiation Laboratory at 7 to 12 weeks of age. HS/Npt stock mice of both sexes were exposed to 0.4 Gy of 28Si ions (240 MeV/n) (n = 308) or 56Fe ions (600 MeV/n) (n = 314), 3 Gy of 137Cs -rays (n = 615), or sham irradiated (n = 622). Following irradiation exposure or sham irradiations, mice were returned to Colorado State University (Fort Collins, CO) and monitored twice daily for the duration of the study. The mice were evaluated for cancer development until they reached 800 days of age or became moribund. All animal procedures were approved by the Colorado State University Institutional Animal Use and Care Committee.

This study uses a highly recombinant mouse population (HS/Npt stock) that is genetically diverse and designed for genome mapping (1921, 23). HS/Npt mice are a multiparent cross derived from eight inbred strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6J, DBA/2J, and LP/J); each individual contains a unique mosaic of founder haplotypes and a high degree of heterozygosity, and recombination events become increasingly dense with each generation. Our population of HS/Npt mice was obtained from generation 71 of circular outbreeding.

DNA was isolated from tail biopsies taken from each mouse at 9 to 10 weeks of age. DNA was extracted and purified (QIAGEN, catalog no. 69506) according to the manufacturers instructions. GeneSeek (Lincoln, NE) performed genotyping assays using the Mega Mouse Universal Genotyping Array (MegaMUGA) (59) for a total of 1878 mice (including 28 inbred mice representing the founder strains). The MegaMUGA is built on the Illumina Infinium platform and consists of 77,808 single-nucleotide polymorphic markers that are distributed throughout the genome with an average spacing of 33 kb.

The heterogeneous stock mice are descendants of eight inbred founder strains. For each mouse, allele calls from the MegaMUGA array were used to calculate descent probabilities using a hidden Markov model (HMM), in which the hidden states were the founder strains and the observed data were the genotypes. The HMM generates probabilistic estimates of the diplotype state(s) for each marker locus and produces a unique founder haplotype mosaic for each mouse (18).

For this lifetime carcinogenesis study, all disease states were interpreted within the context of a systematic pathologic evaluation directed by board-certified veterinary pathologists (E.F.E. and D.A.K.). Structured necropsy and tissue collection protocols were followed for each mouse and involved photodocumentation of all gross lesions, collection of frozen tumor material, and preservation of tumor material in RNAlater. All tissues were grossly evaluated for all mice. To evaluate brain tissues and Harderian glands, craniums were decalcified for 48 hours in Formical-4 (StatLab, McKinney, TX 75069, product 1214) and five coronal sections of the skull were reviewed for each mouse. All gross lesions were evaluated microscopically and fixed in 10% neutral-buffered formalin and paraffin-embedded, and 5-m sections were stained with hematoxylin and eosin (H&E) and evaluated by a veterinary pathologist. For mice with solid tumors, all lung fields were examined histologically to detect the presence or absence of micrometastases. Tumor nomenclature was based on consensus statements produced by the Society of Toxicologic Pathology for mouse tumors (www.toxpath.org/inhand.asp). Representative histologic images routinely stained with H&E are presented in figs. S2 (A to E) and S3 (A and B).

Tissue microarrays were constructed to immunophenotype and subcategorize lymphoid neoplasms, which were the most commonly diagnosed tumors in irradiated and unirradiated HS/Npt mice. Identification of tissue sampling regions was performed by a veterinary pathologist. For each case, duplicate cores were taken from multiple anatomic locations (lymph nodes, spleen, thymus, etc.). Thirteen tissue microarrays were created, each of which contained six cores of control tissue at one corner of the array (haired skin, spleen, thymus, or liver); these control tissues were present in a unique combination and allowed for (i) orientation of the resulting sections, (ii) verification that the slide matched the block, and (iii) positive controls for immunohistochemistry. Figure S3D illustrates one tissue microarray as well as the resulting immunohistochemistry results for one thymic lymphoma (fig. S3E) and a core containing normal spleen (fig. S3F). Immunohistochemistry for T cell identification was performed using a rabbit monoclonal, anti-CD3 (SP7) antibody obtained from Abcam (ab16669; 1:300). Immunohistochemistry for B cell identification was performed using two rabbit monoclonal antibodies: an anti-CD45 antibody (ab10558; 1:1000) and an anti-PAX5 antibody (ab140341; 1:50). All immunohistochemistry was performed on a Leica BOND-MAX autostainer with the Leica BOND Polymer Refine Red Detection system (Leica DS9390, Newcastle Upon Tyne, UK). In addition to defining the immunophenotype, lymphomas were characterized according to the Mouse Model of Human Cancer Consortiums Bethesda protocols (60). For these protocols, anatomic location is important for the final diagnosis, and therefore, lymph node involvement was used from necropsy reports when necessary. Additional features included cell size, nuclear size, chromatic organization, and mitotic figure frequency, and the presence or absence of a leukemic phase was defined by bone marrow involvement within the sternum or femur. The most common lymphoma subtypes (fig. S4A) were evaluated for survival (fig. S4B), and pre-T LL typically presented with early-onset and large thymic masses.

Droplet digital polymerase chain reaction (ddPCR) was performed on cases of AML to assess deletion status via copy number variation for two genes: Spi1 and Asxl1. These genes are both located on chromosome 2 at base pair locations 91,082,390 to 91,115,756 for Spi1 and 153,345,845 to 153,404,007 for Asxl1. To establish a reference for normal diploid copy number in each AML sample, the copy number of H2afx was also determined. H2afx is located on chromosome 9, and deletions in this region have not been reported in murine AML. Bio-Rad PrimePCR probes were used for all assays as follows: Asxl1 ddPCR probe (dMmuCPE5100268), Spi1 ddPCR probe (dMmuCPE5094900), and H2afx ddPCR probe (dMmuCPE5104287). Ratios were created between the test gene and the reference gene (Spi1:H2afx and Asxl1:H2afx) to determine copy number with the assumption that the reference gene would not be deleted or amplified. Ideally, ratios of 1:1 represent equal copy numbers for both the test gene and the reference gene, and ratios of 1:2 represent a deletion in one copy of the test gene. However, since the tumor samples contained neoplastic cells as well as stromal cells and other cells, the ideal 1:2 ratio was not commonly observed. This is because stromal cells, which occur at unknown proportions in each tumor and which should not have chromosomal deletions, artificially increase ratios for tumor samples in which a deletion is indeed present. To account for stromal cell contamination, a cutoff ratio of 3:4 was established. Tumor samples with ratios below 3:4 were considered to have a deletion in one copy of the test gene.

For cases in which a solid tumor was identified, a standard section containing all lung lobes was processed and evaluated histologically. In cases where pulmonary metastases were observed, whole-slide scanning was performed at 200 magnification using an Olympus VS120-S5 and the OlyVIA software suite (www.olympusamerica.com/) to generate images for quantification of metastatic density (fig. S5). An analysis software, ImageJ (https://imagej.nih.gov/ij/), was used to quantify the total area of normal lung and the total area of metastatic foci (fig. S5). Metastatic density is reported as a percentage of the total metastasis area divided by the total lung area.

Association mapping was performed using a mixed-effects regression model with sex and cohort as fixed effects and a random-effects term to adjust for relatedness between mice by computing a matrix of expected allele sharing of founder haplotypes for each pair of mice (22). Three statistical models were fit to account for the wide range of trait distributions in this study. A generalized linear regression model was fit for binomial distributions, such as neoplasia. Cox regression analysis was incorporated to model time-to-event distributions to evaluate genetic contributions to tumor latency. Following genome-wide association analyses, resample model averaging methods were used to identify QTL that are consistently reproduced within subsamples of the mapping population.

Thresholds were determined using a permutation procedure in which the genotypes were fixed and the phenotype values were rearranged randomly within each sex. The distribution of the maximum negative log(P value) of association under the null hypothesis that no associations exist (null model) was determined for each genome scan with permuted data. One thousand permutations were performed for each phenotype in each radiation exposure group, simulating effects arising from covariates, the linkage disequilibrium structure of the genome, and effects due to phenotype distribution. A threshold was defined as an estimate of the genome-wide significance for which a type I statistical error will occur at a given frequency (29). Confidence intervals for each QTL were determined by nonparametric resample model averaging procedures using bootstrap aggregation with replacement. In this procedure, the mapping population is sampled to create a new dataset in which some individuals may be omitted and some may appear multiple times (30), and the locus with peak significance is recorded. Resampling is repeated 200 times for each phenotype to determine a 95% confidence interval for a given QTL. Effect sizes were calculated using the Tjur method for association mapping with logistic regression and pseudo-R2 for mapping with Cox proportional hazard regression. Statistical significance for each model was assessed using a permutation strategy to randomize genotypes via resampling without replacement and maintaining covariates. Permutation analysis was performed (1000 tests) for each trait and exposure group to generate estimations of genome-wide significance thresholds. As genome scans with hundreds of thousands of imputed SNPs are computationally intensive, parallel computing was essential and accomplished using spot instances of resizable Elastic Compute Cloud hosting resources.

Comparisons were made between whole-genome scans using Pearson correlations as a similarity measure with clustering based on average linkage. Significance of clustering results was estimated with 10,000 random permutations of the dataset (log10 values permuted with genetic markers) to determine a distribution of dendrogram heights under the null hypothesis that no associations exist. Each permutated dataset simulates a null distribution of the maximally significant clustering based on a randomly assorted set of P values for each genomic locus.

Bootstrap aggregation is a resample model averaging procedure that has been demonstrated to produce highly accurate estimates of QTL in structured populations (32). The procedure is relatively simple: for a genome-wide association study (GWAS) of n individuals, a sampling of n draws is obtained, with replacement, from the observed individuals to form a new dataset in which some individuals are omitted and some appear multiple times. For each new dataset created this way, an estimate of the QTL location is calculated. This process is repeated many times and is the basis for determining a confidence interval for a given result. The use of bootstrap procedures is commonly used this way to estimate QTL support intervals in experimental crosses; however, this statistical method can potentially be applied to other areas of QTL research, including comparative QTL mapping.

When an identical QTL is observed for two distinct traits, one explanation is that a single gene is involved for two distinct biologic processes, also known as pleiotropy. This was sometimes assumed in early mouse QTL studies that resulted in coincident loci for distinct traits. Another possibility, however, is that two distinct genetic variants are present in close proximity, each independently contributing to the two phenotypes. Because the two hypothetical genetic variants happen to be in close proximity, they are difficult to distinguish in low-resolution mapping studies. Using resample model averaging in highly recombinant mice is proposed to best differentiate precise locations of the QTL; if the same markers were repeatedly identified, then the case for pleiotropy was strengthened. For comparative QTL mapping in tumorigenesis studies, nonparametric resample model averaging could similarly be leveraged to identify whether the same QTL renders an individual susceptible to distinct environmental carcinogens. One significant advantage to using bootstrap procedures to detect potential coincident loci is that comparisons can be made between groups based on the identification of a highly significant QTL identified in only one exposure group (e.g., at a false-positive rate of 1 per 20 scans). This QTL may be present in the alternative exposure group, but at lower confidence (e.g., at a false-positive rate of 1 per 10 scans), and therefore discarded in a typical GWAS. A diagrammatic representation of the comparative QTL bootstrap procedure is presented in fig. S6. Because the resultant genetic positions derived from bootstrapping are composed of the most significant locus for each resampling regardless of the significance level for the mapping procedure, comparisons can be drawn between QTL that might have been discarded on the basis of the stringent statistical demands of an assay involving hundreds of thousands of independent tests. Using this procedure on thyroid tumors demonstrates that the same loci are consistently identified whether exposed to particle or photon irradiation (Fig. 2E). Using the comparative QTL procedure described, it can be determined whether an individuals cancer risk from one carcinogen will be predictive of that individuals cancer risk to another carcinogen. The application of this procedure is well illustrated by the space radiation problem, where much is known about -ray exposures and little is known about space radiation exposures.

In addition to looking for similarities between individual selected QTL for HZE ion and -rayexposed populations, we also sought a more holistic method in which entire genome scans could be compared between groups in an unsupervised process. By using entire genome scans, we submit for comparison not only highly significant regions but also the numerous loci detected with lower confidence. To determine similarity of genetic association profiles for all phenotypes and to detect possible coincident QTL, clustering procedures were used to compare genome-wide association scans between different radiation exposure groups. To demonstrate and validate the methodology of QTL clustering, genome-wide scans for coat colors in each treatment group are evaluated (Fig. 5B). As expected, genome-wide scans for coat color are unaffected by radiation exposures, and therefore, clustering is based entirely on coat phenotype rather than radiation exposure group. Using the same procedure for neoplasia indicates that tumor types often clustered together as well, regardless of radiation exposure (Fig. 5A). Genome scans for thyroid tumors and mammary adenocarcinomas in radiation-exposed groups and all hepatocellular carcinoma genome scans cluster together. This finding supports the hypothesis that host genetic factors are more important in determining neoplasm incidence than radiation exposure type. Unlike other statistic procedures, such as regression models, clustering lacks a response variable and is not routinely performed as a formal hypothesis test. Therefore, determining the significance of a clustering result can be problematic, as no consensus method exists for cluster validation. Permutation analysis provides the distribution of clustering results that will randomly occur from a given dataset; this can then be used as a baseline from which to determine a significance level on a given dendrogram tree [green line in Fig. 5 (A to C)]. While the overall validity of a given cluster can be accomplished by cluster permutation analysis, no method is identified to estimate the number of clusters that should be present in a dataset. Furthermore, methods to determine the significance of specific subset of objects clustering together do not exist; in such cases, the permutation threshold is likely overly stringent.

Excerpt from:
Genomic mapping in outbred mice reveals overlap in genetic susceptibility for HZE ion and -rayinduced tumors - Science Advances

NEW YORK and BASEL, Switzerland, April 15, 2020 (GLOBE NEWSWIRE) -- Axovant Gene Therapies Ltd., a clinical-stage company developing innovative gene therapies for neurological diseases, today announced its collaboration with Invitae, a leading medical genetics company, in the Detect Lysosomal Storage Diseases (Detect) program to facilitate faster diagnoses for children with lysosomal storage disorders (LSDs), including GM1 gangliosidosis and GM2 gangliosidosis, also known as Tay-Sachs/Sandhoff disease. Invitae offers genetic testing and counseling at no charge to patients suspected of having an LSD.

Axovant is committed to developing novel gene therapies for those living with rapidly progressive neurodegenerative diseases. We are hopeful that our collaboration with Invitae will provide families with easier access to genetic testing and bring us one step closer to identifying patients who may benefit from potential therapies, said Parag Meswani, PharmD., Axovants SVP of Commercial Strategy & Operations. Our AXO-AAV-GM1 clinical program targeting GM1 gangliosidosis is currently enrolling at the National Institutes of Health, and we are seeking IND clearance for the AXO-AAV-GM2 clinical trial targeting Tay-Sachs and Sandhoff diseases. Early intervention is ideal with potentially disease-modifying genetic therapies, and our diagnostics partnership with Invitae should allow us to identify and enroll children at even earlier stages of disease progression.

LSDs are progressive, multi-system, inherited metabolic diseases associated with premature death, and genetic testing is a crucial first step to arriving at a diagnosis. LSDs are misdiagnosed or undiagnosed in the majority of patients. The Detect program includes a specific LSD testing panel of 53 genes designed to provide patients and families accurate information quickly to preserve valuable treatment time.

Genetic testing can expedite an accurate diagnosis, facilitate earlier interventions, allow genetic counseling of family members, and support clinical research for LSDs such as GM1 and GM2 gangliosidosis, said Robert Nussbaum, M.D., chief medical officer of Invitae. Were pleased Axovant has joined the Detect program to help offer no-charge, sponsored genetic testing for those patients suspected of having the disease.

Research has shown no-charge testing programs with large well-designed panels help increase utilization of genetic testing, which can shorten the time to diagnosis by as much as 2 years in some conditions. Accurate diagnoses enable clinicians to focus on providing disease-specific care sooner, helping reduce costs and improve outcomes.

Additional details, as well as terms and conditions of the program, can be found at https://www.invitae.com/en/detectLSDs/.

About Axovant Gene Therapies

Axovant Gene Therapies is a clinical-stage gene therapy company focused on developing a pipeline of innovative product candidates for debilitating neurodegenerative diseases. Our current pipeline of gene therapy candidates targets GM1 gangliosidosis, GM2 gangliosidosis (including Tay-Sachs disease and Sandhoff disease), and Parkinsons disease. Axovant is focused on accelerating product candidates into and through clinical trials with a team of experts in gene therapy development and through external partnerships with leading gene therapy organizations. For more information, visit http://www.axovant.com.

About Invitae

Invitae Corporation (NYSE: NVTA) is a leading medical genetics company, whose mission is to bring comprehensive genetic information into mainstream medicine to improve healthcare for billions of people. Invitae's goal is to aggregate the world's genetic tests into a single service with higher quality, faster turnaround time, and lower prices. For more information, visit the company's website atinvitae.com.

Forward-Looking Statements

This press release contains forward-looking statements for the purposes of the safe harbor provisions under The Private Securities Litigation Reform Act of 1995 and other federal securities laws. The use of words such as "may," "might," "will," "would," "should," "expect," "believe," "estimate," and other similar expressions are intended to identify forward-looking statements. For example, all statements Axovant makes regarding costs associated with its operating activities are forward-looking. All forward-looking statements are based on estimates and assumptions by Axovants management that, although Axovant believes to be reasonable, are inherently uncertain. All forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from those that Axovant expected. Such risks and uncertainties include, among others, the initiation and conduct of preclinical studies and clinical trials; the availability of data from clinical trials; the expectations for regulatory submissions and approvals; the continued development of its gene therapy product candidates and platforms; Axovants scientific approach and general development progress; and the availability or commercial potential of Axovants product candidates. These statements are also subject to a number of material risks and uncertainties that are described in Axovants most recent Quarterly Report on Form 10-Q filed with the Securities and Exchange Commission on February 10, 2020, as updated by its subsequent filings with the Securities and Exchange Commission. Any forward-looking statement speaks only as of the date on which it was made. Axovant undertakes no obligation to publicly update or revise any forward-looking statement, whether as a result of new information, future events or otherwise.

Media Contact:

Parag MeswaniAxovant Gene Therapies(212) 547-2523investors@axovant.commedia@axovant.com

Link:
Axovant Announces Partnership with Invitae to Increase Access to Genetic Testing and Accelerate Diagnoses of GM1 and GM2 Gangliosidosis -...

Throughout history, the nations colleges and universities have set the foundation for innovation and social change. Weve uncovered the secrets of DNA. Weve unleashed bioengineering. We have harnessed intellectual power to create new technologyoften through the partnerships between land grant colleges and local industries and agriculturebringing the latest science to where it was needed. And we have done it all while demanding intellectual rigor and a sharp focus on the common good for society.

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Institutions of higher education, large and small, can and do play a significant role in serving our country and our world at this critical moment in history. But our work starts at home. Whats required is a community approach, as local areas are impacted in distinct ways while this crisis unfolds.

I learned the power of community response to overwhelming challenges at the American University of Nigeria. I served there as president when Boko Haram began to surge near the campus and federal assistance was nowhere to be found. The university brought the community together and kept the terrorist group at bay and fed refugees.

Drawing on that experience, when I arrived at Dickinson three years ago, I immediately began to gather with community members to identify their most pressing issues and to connect them with college resources. What started out as a dozen people has now grown to more than 50 representing nearly every sectornonprofits, school districts, health care, government and business. We are meeting remotely in the age of COVID-19, but the relationships we have built have allowed us to respond quickly in a coordinated manner to the communitys growing needs.

Working with Carlisle Borough, the Chamber of Commerce and Community CARES partnered to convert the Stuart Community Center into a shelter for the homeless. UPMC Carlisle anticipated a potential need for housing and shelter for its exhausted medical workers; Dickinson stepped up and agreed to make space available in our vacated residence halls. Local businesses needed an online presence to offer goods and services, but lacked the know-how; Dickinson students are developing e-commerce websites for those businesses. Our organic farm is supplying much-needed fresh produce for the community.

Colleges areand should beat the epicenter of community responses to COVID. They can and should be the assembly point for community action. Its imperative that colleges start building or strengthening relationships with leaders in their communities now, to help in recovery and before the next crisis or disaster occurs.

When students return to class, they will return to communities that have changed in myriad ways. The old ideas, approaches and leadership simply wont do. Our students and young people are the ones we will need to help us with the necessary reconstruction. Those students will rely on the knowledge and problem-solving skills our institutions of higher learning should be providing.

In these difficult times, the country must demand much of its colleges and universities. Communities must know that we are in the trenches with you, and that we are all of us prepared to do more. When students return to our campuses we should work together to build a program of national service. This is how we will rebuild America and prepare the next generation for more unprecedented challenges.

Margee M. Ensign is president of Dickinson College, in Carlisle. Previously, Ensign served as president of the American University of Nigeria, where she developed aid and relief programs for hundreds of thousands of internally displaced people fleeing Boko Haram.

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