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• Multimodal immunogenomic biomarker analysis of tumors from pediatric patients enrolled to a phase 1-2 study of single-agent atezolizumab

  We report herein an extensive exploratory biomarker analysis of refractory tumors taken from pediatric patients prior to receiving atezolizumab monotherapy in the phase 1-2 iMATRIX-atezolizumab trial (NCT02541604). A high percentage of CD8+ T cells and elevated protein levels of programmed cell death ligand 1 (PD-L1) were associated with progression-free survival (PFS). T-cell receptor (TCR) sequencing revealed that diverse infiltrating TCR repertoire at baseline was prognostic. We found no associations between panel-based tumor mutation burden (TMB) or specific genetic aberrations with PFS in this study. Through a pan-cancer gene co-expression network analysis, we developed a novel tumor-agnostic Pediatric Cytotoxicity and Antigen Presentation (PedCAP) signature that was associated with improved PFS in the iMATRIX-atezo study. Our study highlights features of immune response in pediatric cancers when treated with immune checkpoint inhibitors and provides a multi-biomarker pediatric immunogram framework to guide prospective clinical trials in pediatric cancers.

  Study EGAS00001006004

• Resolving the immune landscape of human prostate at a single cell level in health and cancer

  The prostate gland produces prostatic fluid, high in zinc and citrate and essential for the maintenance of spermatozoa. Prostate cancer is a common condition with limited treatment efficacy in castration-resistant metastatic disease, including with immune checkpoint inhibitors. We used single-cell RNA-sequencing to perform an unbiased assessment of the cellular landscape of human prostate and identified a previously unappreciated subset of tumour-enriched androgen receptor-negative luminal epithelial cells, with increased expression of cancer-associated genes. We also found a variety of innate and adaptive immune cells in normal prostate that were transcriptionally perturbed in prostate cancer. An exception was a unique, prostate-specific, zinc transporter-expressing macrophage population (MAC-MT), that contributed to tissue zinc accumulation in homeostasis, but showed enhanced inflammatory gene expression in tumours, including T cell-recruiting chemokines. Remarkably, enrichment of the MAC-MT signature in cancer biopsies was associated with improved disease-free survival, suggesting beneficial anti-tumour functions.

  Study EGAS00001005787

• A longitudinal single-cell atlas of treatment response in pediatric AML

  Pediatric acute myeloid leukemia (pAML) is a disease characterized by heterogeneous cellular composition, driver alterations and prognosis. Characterization of this heterogeneity and how it affects treatment response remains relatively understudied in pediatric patients. We therefore used single-cell RNA sequencing and single-cell ATAC sequencing to profile 684,031 diagnosis, remission and relapse cells from 28 patients representing different pAML subtypes. Analysis revealed that at diagnosis, cellular compositions differed between distinct subgroups. Upon relapse, cellular hierarchies transitioned towards a more primitive state regardless of subtype. These primitive cells were distinct compared to cells at diagnosis, having underrepresentation of transcriptional programs involved in myeloid differentiation while programs commonly found in other lineages were overrepresented. In a subset of patients, this appeared to accompany the appearance of a B-lymphoid-like hierarchy. Together, our data reveal the emergence of apparent subtype-specific plasticity upon treatment and inform on potential novel therapeutic angles to target these cell populations.

  Study EGAS00001007323

• Childhood Cancer Survivor Study (CCSS)

  Background and Rationale for the Childhood Cancer Survivor Study (CCSS) Over the last several decades, advances in treatments for childhood and adolescent cancer have substantially improved survival following diagnosis. These improvements gave rise to the responsibility for investigating long-term treatment-associated morbidity and mortality. Early efforts to describe late effects were largely conducted through single-institution and limited consortia studies. However, by the mid-1980s, it became increasingly clear that these approaches had inherent limitations, including small sample size, convenience sampling, incompletely characterized populations, and limited length of follow-up. To overcome these limitations, the CCSS was proposed and funded by the National Cancer Institute (NCI) as a U01 grant in 1994. Subsequently, the strengths of the CCSS, including an efficient and extensive infrastructure, plus expanding database and biorepository, were recognized and appreciated. Thus, in consultation with the NCI, the CCSS was converted to a U24 (resource grant) funding mechanism to serve the scientific community in 2000. The overarching goal of the CCSS resource is to increase the conduct of innovative and high impact research related to pediatric cancer survivorship. CCSS has been used extensively by researchers from a wide range of disciplines to address a broad spectrum of topics. Strengths of the resource include its large size, comprehensive annotation of treatment exposures, ongoing longitudinal follow-up with characterization of a wide array of participant characteristics and outcomes, and an established biorepository. Design of the Childhood Cancer Survivor Study The Childhood Cancer Survivor Study (CCSS) is a multi-institutional, multi-disciplinary collaborative research resource comprised of a retrospective hospital-based cohort of survivors of childhood cancer and a comparison sibling cohort. Eligible survivors from 31 participating institutions were diagnosed between 1970 and 1999, prior to age 21 years, with selected common pediatric cancers (leukemia, central nervous system tumors, Hodgkin lymphoma, non-Hodgkin lymphoma, kidney tumors, neuroblastoma, soft tissue sarcoma, or bone tumors). All patients who survived five years from the date of diagnosis were eligible, regardless of disease or treatment status. The baseline questionnaire was completed by 24,368 survivors and 5,039 siblings recruited to serve as a comparison group. To date, participants have completed three general follow-up surveys, as well as a number of specialized surveys on specific topics (e.g. health care, insurance, screening practices, men's and women's health issues, adolescent health, sleep and fatigue). In addition, biological samples (buccal cells, saliva and/or blood) have been collected for over 11,000 participants. Full descriptions of the design and characteristics of the CCSS have been previously published (Robison et al; Leisenring et al.), and available data and samples are described at https://ccss.stjude.org/develop-a-study/gwas-data-resource.html. Treatment Data in the Childhood Cancer Survivor Study A key feature of CCSS is the availability of detailed treatment data, which were collected by abstraction of medical records for each individual member of the cohort. Detailed abstraction included dates of therapy, protocol information, and specific details regarding surgery, chemotherapy and radiation. Quantitative dose details were collected for 22 specific chemotherapeutic agents, including alkylating agents, anthracyclines, platinum compounds and epipodophyllotoxins. In addition to individual agent doses, algorithms have been created to calculate cumulative doses of all drugs in a specific class, such as anthracyclines (doxorubicin, daunomycin and idarubicin) or platinum agents (cisplatinum and carboplatinum). Data abstracted for surgeries included dates and both the names and corresponding International Classification of Diseases (9th revision) code. For radiation treatment data, all relevant records were sent to the Radiation Physics Center at M.D. Anderson Cancer Center for detailed abstraction and dosimetry. Initial body region dosimetry was performed for all participants, followed by more detailed dosimetry as needed for specific studies. Genomics Data in the Childhood Cancer Survivor StudyThe NCI's Division of Cancer Epidemiology and Genetics and CCSS investigators collaborated to conduct genomics studies (SNP array genotyping and whole exome sequencing) using samples from the CCSS Biorepository. Studies included all cohort participants with available DNA regardless of sex or ancestry when the genomics studies were initiated. Phenotype Data in the Childhood Cancer Survivor Study Vital status and cause of death for both participants and non-participants is determined via linkage with the National Death Index (NDI). Identification of subsequent neoplasms is based on self-report, followed by validation using medical records, or via NDI. A wide array of additional health outcomes have been ascertained via a comprehensive set of questions on the CCSS questionnaires, covering potential adverse events across a range of organ systems (hearing/vision/speech, urinary, hormonal, heart and circulatory, respiratory, digestive, brain and nervous systems). In addition to health outcomes, longitudinal data have been collected on demographics, health behaviors, family history, screening practices, insurance status, and a range of psychosocial and neurocognitive factors. A full listing of available variables and copies of the CCSS questionnaires are available at http://ccss.stjude.org. Research Areas in the Childhood Cancer Survivor Study Extensive use by the research community has resulted in over 265 published manuscripts on a wide range of topics, including associations between treatment factors and mortality, subsequent neoplasms, chronic health conditions, cardiac events, neurocognitive sequelae, psychosocial factors, fertility, and health status. Additional topics have included health behaviors, screening practices, health care access and utilization, statistical and exposure assessment methodology, and development of risk prediction models. A full listing of published manuscripts using CCSS data is available on the CCSS website at https://ccss.stjude.org/published-research/publications.html. The Childhood Cancer Survivor Study as a Resource for Investigators The CCSS is an NCI-funded resource (U24 CA55727) to promote and facilitate research among long-term survivors of cancer diagnosed during childhood and adolescence. Interested investigators are encouraged to develop research ideas and propose projects within CCSS, whether or not they are from a participating CCSS institution. The CCSS is now accepting proposals to collaborate with CCSS and NCI investigators in the use of genomics data and corresponding outcomes-related data to address innovative research questions relating to potential genetic contributions to risk for treatment-related outcomes. Any researcher, or group of researchers, qualified to conduct genetic research can submit a proposal. There are no restrictions relative to country, institution, or prior involvement in CCSS. A full description of the process for developing a proposal for genetic research in CCSS can be found at https://ccss.stjude.org/develop-a-study/gwas-data-resource.html, along with listings of approved proposals.

  Study phs001327

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age<20 0.043 Age>40 0.032 Age<30, ≥20 0.251 Age>30, ≤40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• Genetic Studies of Chronic Kidney Disease (CKD)

  The Genetic Studies of Chronic Kidney Disease (CKD) is an ongoing genetic research and biobanking protocol which aims to elucidate the genetic basis CKD. The study recruits patients seen at the Columbia University Medical Center (CUMC) Nephrology Division for the evaluation and care of CKD. All patients clinically diagnosed with CKD are eligible to participate; there are no inclusion or exclusion criteria related to age, sex/gender, and/or race/ethnicity. In addition to office visits, patients are recruited in contexts including perinatal care and nonprofit events for patients with various forms of CKD; recruitment tools include bilingual informational brochures, flyers, and consent forms. All individuals provide informed consent; for minors, signature of the parent/guardian is required. Consent includes: use of biosamples given for genetic studies, and the request to be re-contacted if medically actionable genetic findings are identified. In the case of the latter, such research-level findings are first validated in a clinically certified (CLIA) laboratory environment, using a second sample given by the individual at the time of re-contact; following CLIA validation, the individual is once again re-contacted, and, assuming he or she still desires return of these results, they can then be returned. Following the above consent process to participate in the study, individuals provide a single biosample (generally, a venous blood sample), from which DNA is extracted using standard protocols and used for genetic studies, such as exome sequencing. Basic clinical and demographic data, including sex/gender, age, and race/ethnicity are also collected. All data collected is stored in a secure computerized database, with patient samples anonymized using numerical identifiers; the relation of this identifier to patients' names is kept in a locked computer file in a centralized database. Electronic data complies with all HIPAA and other privacy and security regulations, and resides on a firewall server maintained by the CUMC IT department.

  Study phs001828

• Genetic Associations in Idiopathic Talipes Equinovarus (Clubfoot) - GAIT

  Isolated clubfoot or idiopathic talipes equinovarus (ITEV) is one of the five most common birth defects, affecting approximately 4,000 newborns each year in the US. While the orthopedic care of these children has improved, long-term problems persist and the health care costs are significant. Studies suggest that clubfoot is a complex disorder with segregation analyses and family studies indicating that genetic factors play an important etiologic role in the development of clubfoot. Only one environmental factor, maternal smoking during pregnancy, has been implicated. We postulate that a small number of genes account for a substantial fraction of clubfoot and that these genes can be identified in a defined population. The challenge now is to identify the genetic loci and, later, the effect of environmental exposures. To accomplish this task, it is important to have a well-defined population and the methodology to detect linkage with and without association. Towards these goals, we have identified and characterized multiplex clubfoot families, including two large clubfoot families, a resource which is among the largest ITEV populations in existence. We will perform a high-density SNP genome scan (GWAS) on our clubfoot dataset to identify chromosomal regions that may harbor clubfoot genes with subsequent interrogation of these regions and candidate genes. We are in a position with our unique clubfoot population and with the methodology in place to undertake this study. The study phases are: 1) continued ascertainment of multiplex and simplex families and 2) GWAS and characterization of identified chromosomal regions and candidate genes. The results of this study will provide data essential to the identification of the gene(s) contributing to the clubfoot phenotype. Identification of high-risk genotypes can lead to the development of prevention programs in selected populations and may suggest gene-based prevention strategies.

  Study phs000314

• Metagenomic Analysis to Identify Novel Infectious Agents in Systemic Anaplastic Large Cell Lymphoma

  Anaplastic large cell lymphoma (ALCL) is a rare T-cell non-Hodgkin lymphoma (NHL). Risk of systemic ALCL is markedly increased among immunosuppressed people, such as those with human immunodeficiency virus (HIV) infection or solid organ transplant recipients. This increased risk in immunosuppressed populations suggests a viral etiology, given similar elevations for diffuse large B-cell lymphoma (DLBCL), Burkitt lymphoma, and Hodgkin lymphoma (caused by Epstein-Barr virus [EBV]) and other virus-related cancers in immunosuppressed individuals. EBV might be a plausible candidate, but most reported ALCL tumors are EBV-negative. Therefore, we conducted a metagenomic analysis of microbial associations with ALCL to determine whether a known or novel pathogen is associated with the tumor. We obtained archived formal fixed paraffin embedded (FFPE) ALCL tumor tissue from the Iowa cancer registry and an additional case from an immunosuppressed individual infected with human immunodeficiency virus. Controls included 3 diffuse large B-cell lymphomas (DLBCLs) in transplant recipients (shown to be related to Epstein-Barr virus [EBV] by in situ hybridization) and 3 breast cancers (no known viral etiology). RNA was extracted from FFPE specimens, and total RNA libraries were prepared using the KAPA RNA HyperPrep Kit (Roche). Five samples (IA01, IA53, IA57, IA07, and IA17) were sequenced on a NextSeq 500 (Illumina) and the remainder on a NovSeq 6000 (Illumina). Using novel computational approaches, we eliminated human reads and aligned residual non-human reads to known microbial references using GATK-PathSeq or conducted de novo assembly of unassigned reads using virID pipeline. Although EBV was detected in the 3 DLBCL controls, we did not detect EBV or any novel pathogen in ALCL tumors or in the breast cancers. Our study had a modest sample size and only one case arising in HIV-infected individual. Therefore, further studies are required to characterize the metagenome of systemic ALCLs, especially cases arising in immunosuppressed people.

  Study phs002064

• GATA2 Deficiency and the MonoMAC Syndrome

  The aim of this study was to identify the germline mutation(s) in an extended family with individuals having MonoMAC Syndrome/GATA2 deficiency but lacking a canonical GATA2 mutation. GATA2 deficiency patients develop bone marrow failure, severe immunodeficiency and may progress to myeloid malignancies, including myelodysplastic syndrome (MDS), acute myeloid leukemia (AML), and chronic myelomonocytic leukemia (CMML). The definitive treatment for GATA2 deficiency is a bone marrow transplant. Approximately 90% of GATA2 deficiency patients have a known de novo or inherited germline mutation in the GATA2 gene, but ~10% have no identified mutation. The study was initiated with the first patient and her second cousin, both of whom were treated for MonoMAC Syndrome and received bone marrow transplants at the NIH. Pedigree analysis and clinical evaluation identified the individuals in several generations of these patients' near and distant relatives who are/were presenting or carrying the disease manifestations of GATA2 deficiency. Whole Genome Sequencing (WGS) was employed on these patients' two related nuclear families to identify variants that segregated with the disease trait and carrier status of their families. Genotyping was confirmed with direct DNA sequencing of these and other family members within the extended family across generations. A single base adenine-to-thymidine change was identified in a highly conserved enhancer element ~117,000 bp upstream of the GATA2 gene. It creates a new Composite Element, a DNA motif known to be critical in the regulation of hematopoiesis. This variant is unique to this family and is not present in dbSNP or other variant databases. It segregates with the disease trait and obligate carriers throughout a large pedigree. In vitro studies show that this variant drives allele-specific overexpression of the GATA2 gene in cultured cells and luciferase assays. The WGS sequence from the nuclear families will be shared on dbGaP.

  Study phs003269

• Somatic Mutations and Their Etiological Determinants for Breast Cancer in African American Women (B-CAUSE Study)

  The breast cancer health disparity between women of African ancestry (AA) and European ancestry (EA) remains a major public health challenge in the United States. AA women are afflicted by higher rate of triple-negative breast cancer (TNBC) and bear the highest mortality rate of all populations from the disease. Even within TNBC, some data suggest that AA women have poorer outcomes than EA women. Mounting evidence points to population differences in cancer biology, a fundamental question that remains unsettled. The disparity also manifests in representativeness in tumor sequencing projects, due to the low inclusion of AAs in genomic studies. A recent analysis of The Cancer Genome Atlas (TCGA) data revealed that the number of AA cases sequenced was sufficient only for studying frequently mutated genes (≥10%), and the power was worse for TNBC as a separate disease entity. As a result, the breast tumor mutational landscape elucidated to date is derived mostly from EA cases, and may not necessarily represent AA cancer genomes. Moreover, as discovery potential for new driver genes has come close to a plateau, cancer in AAs derived from distinct genetic and environmental contexts may provide a powerful venue for discovering mutations that are rare in EA cases. This is showcased in recent studies in colon and prostate cancer. Thus, we carried out a collaborative project, B-CAUSE, to characterize the mutational landscape of AA breast cancer genomes by pooling resources from five established studies, including the Women's Circle of Health Study (WCHS), the Black Women's Health Study (BWHS), the Southern Community Cohort Study (SCCS), the Nashville Breast Health Study (NBHS), and the Southern Tri-State Breast Health Study (STSBHS). This effort has created the largest AA-specific breast tumor mutation dataset to date in an efficient manner. The data deposited here are from the whole-exome sequencing (WES) of matched tumor-normal pairs of 462 TNBC in AA women from the B-CAUSE Study.

  Study phs003962

• Emirati Genome Project subset of 43,608 WGS samples for population-scale variant discovery and allele frequency mapping.

  Here, we present a comprehensive genomic characterization of a cohort of 43,608 Emirati genomes sequenced as part of the Emirati Genome Program (EGP). This study identified more than 421 million single nucleotide variants and indels and more than 600 million copy number- and structural variants. Small variants had 756 million molecular effects annotated. Of the identified variants, 69.04% were observed with more than one allele. Of 7.7 million polymorphic variants having an allele frequency (AF) of more than 5% in EGP, 1,348 have a predicted deleterious effect on a protein. Characterization of global variation reveals that EGP represents a genetic continuum encompassing the range of African, Asian, and European populations. It is best described by two Arabian, an Eurasian, and an African component, with the predominant Arabian component linked to mitochondrial haplogroups J and T, which are commonly attributed to the Middle East. Various aneuploidies of sex chromosomes were detected in 93 individuals overall and of chromosome 21 in 41 individuals. The median inbreeding coefficient and cumulative runs of homozygosity (ROHs) lengths were increased due to extensive consanguinity, being largest in the groups with Arabian main ancestry components and higher than reported for Qatar. Families were identified based on genetic relatedness and classified into 264 families with unrelated parents and 247 families with third- and fourth-degree consanguineous parents. Representative consanguineous pedigrees of families in EGP were outlined. Cumulative ROHs were affected by the main ancestry component and significantly increased in offspring of consanguineous parents, with a pronounced difference between 3rd and 4th-degree relatedness. Investigation of cumulative AFs of variants causing Mendelian diseases highlighted genes related to alpha- and beta-thalassemia (HBB, HBA2). It showed a high burden of variants causing severe recessive diseases, metabolic and retinal disorders, and hearing loss. In summary, EGP represents a landmark effort in characterizing the genetic diversity of the Emirati population, leveraging the largest Middle Eastern cohort reported to date.

  Study EGAS50000001071

• Liver biopsy derived induced pluripotent stem cells provide an unlimited supply for the generation of patient-specific hepatocyte-like cells

  Background: Hepatocyte-like cells (HLCs) differentiated from induced pluripotent stem cells (iPSCs) have emerged as a promising cell culture model to study metabolism, biotransformation, viral infections and genetic liver diseases. However the derivation of iPSCs is restricted by ethical and procedural constraints. Furthermore, incomplete HLC differentiation remains a major challenge. iPSC may carry-on a tissue of origin dependent expression memory influencing iPSC differentiation into different cell types. If liver derived iPSCs (Li-iPSCs) maintain a liver specific gene expression profile is not known. It is also not known, if Li-iPSCs would allow the generation of more fully differentiated HLCs.Methods: Primary liver cells (PLCs) were expanded from liver needle biopsies and reprogrammed into Li-iPSCs using a non-integrative Sendai virus-based system. Li-iPSCs were differentiated into HLCs using established differentiation protocols. The HLC phenotype was characterized at the protein, functional and transcriptional level. RNA sequencing data were generated from the originating liver biopsies, the Li-iPSCs, fibroblast derived iPSCs, and differentiated HLCs, and used to characterize and compare their transcriptome profiles.Results: PLCs were obtained from small pieces of liver biopsies and could be reprogrammed into Li-iPSCs. Li-iPSCs indeed retain a liver specific transcriptional footprint. Li-iPSCs can be propagated to provide an unlimited supply of cells for differentiation into Li-HLCs. Similar to HLCs derived from fibroblasts, Li-HLCs could not be fully differentiated into hepatocytes. Relative to the originating liver, Li-HLCs showed lower expression of liver specific transcription factors and increased expression of genes involved in the differentiation of other tissues.Conclusions: PLCs and Li-iPSCs obtained from small pieces of human needle liver biopsies constitute a novel unlimited source for the production of HLCs. Despite the preservation of a liver specific gene expression footprint in Li-iPSCs, the generation of fully differentiated hepatocytes cannot be achieved with the current differentiation protocols.

  Study EGAS00001002676

• Whole exome sequencing of germline DNA was performed and subsequent polymorphisms in genes known and putatively involved in the innate immune response to fungi were identified

  Disease can be conceptualized as the result of interactions between infecting microbe and holobiont, the combination of a host and its microbial communities. It is likely that genomic variation in the host, infecting microbe, and commensal microbiota are key determinants of infectious disease clinical outcomes. However, until recently, simultaneous, multiomic investigation of infecting microbe and holobiont components has rarely been explored. Herein, we characterized the infecting microbe, host, micro- and mycobiomes leading up to infection onset in a leukemia patient that developed invasive mucormycosis. We discovered that the patient was infected with a strain of the recently described Mucor velutinosus species which we determined was hypervirulent in a Drosophila challenge model and has a predisposition for skin dissemination. After completing the infecting M. velutinosus genome and genomes from four other Mucor species, comparative pathogenomics was performed and assisted in identifying 66 M. velutinosus-specific putatively secreted proteins, including multiple novel secreted aspartyl proteinases which may contribute to the unique clinical presentation of skin dissemination. Whole exome sequencing of the patient revealed multiple non-synonymous polymorphisms in genes critical to control of fungal proliferation, such as TLR6 and PTX3. Moreover, the patient had a non-synonymous polymorphism in the NOD2 gene and a missense mutation in FUT2, which have been linked to microbial dysbiosis and microbiome diversity maintenance during physiologic stress, respectively. In concert with host genetic polymorphism data, the micro- and mycobiome analyses revealed that the infection developed amid a dysbiotic microbiome with low α-diversity, dominated by staphylococci. Additionally, longitudinal mycobiome data showed that M. velutinosus DNA was detectable in oral samples preceding disease onset. Our genome-level study of the host-infecting microbe-commensal triad extends the concept of personalized genomic medicine to the holobiont-infecting microbe interface thereby offering novel opportunities for using synergistic genetic methods to increase understanding of infectious diseases pathogenesis and clinical outcomes.

  Study EGAS00001001542

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• ctDNA to predict risk of progression and death after trifluridin/tipiracil therapy

  Background. Late-line treatment in metastatic colorectal cancer (mCRC) can improve the prognosis. However, not every patient has a benefit and may experience severe side effects. Thus, predictive/prognostic biomarkers are urgently needed. Despite many promising results, the role of circulating tumor DNA (ctDNA) analysis in trifluridin/tipiracil (FTD/TPI) treated mCRC patients is so far still elusive. Study design. This prospective non-interventional translational biomarker phase II study enrolled 30 metastatic CRC patients treated with FTD/TPI. The primary study aim was to identify a molecular biomarker to predict overall survival (OS) benefit upon FTD/TPI treatment. Methods. mCRC patients (60% male, 40% female) with FTD/TPI therapy were included. Molecular profiling in cell-free DNA from plasma was performed prior to treatment and on average 4, 8 and 12 weeks after FTD/TPI initiation. Tumor levels were assessed as the highest variant allele frequency (hVAF) and correlated with OS. Uni- and multivariate analyses for survival were performed with clinical variables. Multivariate analyses for survival and treatment efficacy were adjusted to age, gender and ECOG performance status. Results. Compared to previous data, our disease control rate of 30% was lower with a median OS of 8.1 months and a median PFS of 3.2 months. At baseline (BL) and the first two follow-ups (FU), a hVAF cut-off of 7.5% was most discriminative (BL HR 0.39 95% CI 0.16 - 0.98 P=0.0212, FU1 HR 0.30 95% CI 0.12 -0.77 P=0.0021, FU2 HR 0.23 95% CI 0.08-0.70 P=0.0004) whereas at the last follow-up the stratification was most pronounced at a 15% cut-off. An elevated hVAF trajectory over time was associated with a higher risk of death. Conclusion. ctDNA is detectable in a high proportion of mCRC patients. Changes in ctDNA levels are associated with survival among FTD/TPI therapy and may identify patients who benefit most from treatment in these late-stage disease.

  Study EGAS00001006883

• Nala GSI GSAv3 PGx Study

  Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay's performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes. Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets. Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100 % phenotype inter-run concordance. Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.

  Study EGAS00001007710

• Genomic Diagnosis and Individualized Therapy of Highly Penetrant Genetic Diabetes

  The most common and well-known causes of diabetes are type 1 and type 2 diabetes; however, there are many other etiologies of diabetes. At least 1-2% of diabetes cases result from high penetrance single gene defects, most commonly in a gene encoding either a transcription factor involved in beta cell development and function or the enzyme glucokinase (GCK). Others have mutations in transcription factors necessary for beta cell development and function. This subset of monogenic diabetes cases is autosomal dominant and is known as "Maturity-Onset Diabetes of the Young" (MODY). Patients with type 1 diabetes are insulin dependent, meaning they lack insulin production and therefore require multiple daily injections of insulin, as well as multiple times a day blood glucose monitoring. This can be quite burdensome. Type 2 diabetes is predominantly an insulin resistance problem and can often be managed with pills initially, but there are many who also require insulin either at diagnosis or later on in their disease course. Usually, monogenic diabetes is misdiagnosed as type 1 or type 2 diabetes and thus treated suboptimally. Those with monogenic diabetes, due to a defect in a gene encoding a transcription factor, respond extremely well to a class of oral diabetes medications called sulfonylureas. Those with GCK-MODY often have a mild, stable, fasting, nonprogressive hyperglycemia for which pharmacological treatment is often not necessary. It is important to accurately diagnose our patients with the correct etiology to their diabetes for a multitude of reasons. Accurately diagnosing a patient with MODY, for example, can predict their clinical course and we can tailor treatment accordingly. If diagnosed with a transcription factor MODY, we can try switching the patient from insulin to an oral sulfonylurea, and if diagnosed with a GCK-MODY, we can consider discontinuing pharmacological treatment altogether. With specific tailoring of treatment, we would hope to improve quality of life by discontinuing perhaps multiple daily injections of insulin and glucose checking as these may not be necessary. In addition, we would hope to improve glycemic control with an eventual decreased cost to society by decreasing the complication rate of diabetes, resulting in less specialty referrals, lab tests, supplies and procedures. Further, given MODY is an autosomal dominant condition with a 50% chance of inheritance to first-degree family members, we could offer testing to asymptomatic family members which could lead to prevention and/or early diagnosis and treatment. Overall, testing for monogenic diabetes is underutilized clinically. Testing is being done in the U.K., but in the U.S. we are lagging behind. This is most predominantly due to lack of knowledge and concern over cost. In addition, it is difficult to differentiate the relatively small number of monogenic diabetes cases from the larger number with type 1 and type 2 diabetes as each of these etiologies have overlapping characteristics. In fact, many patients with monogenic diabetes are being misdiagnosed with type 1 and type 2 diabetes. There are recommendations set forth by different societies on who to consider screening for monogenic diabetes. However, these recommendations are difficult to employ clinically as they are general recommendations, there is no specific algorithm, and they are based on varying levels of evidence. The purpose of this study is to implement a personalized diabetes medicine program to enhance the identification of individuals and families affected by highly penetrant diabetes gene mutations through a combination of systematic screening and genetic testing at the University of Maryland Center for Diabetes and Endocrinology, the Baltimore VA Medical Center and additional partner centers at Geisinger Health System and Bay West Endocrinology Associates, and other UM outpatient clinics. Our hope is to develop an approach that can be eventually implemented across the United States so that we can more often uncover the correct etiology to diabetes, tailor treatment accordingly, and test asymptomatic family members.

  Study phs001771

• Detroit Research on Cancer Survivors (ROCS) and Disparities and Cancer Epidemiology - Colorectal Cancer (DANCE)

  The goals for this study were as follows:1. Enroll a total of 5,060 African Americans newly diagnosed with cancer into the Detroit Research on Cancer Survivors (Detroit ROCS) Cohort. These population-based cases will be ascertained through the Detroit Metropolitan Detroit Cancer Surveillance System (MDCSS), a founding member of the NCI SEER Program. Participation at baseline will include a written, web-based, or telephone interview, saliva and/or blood collection, and tumor block retrieval, with detailed cancer-related information coming from the MDCSS registry and medical records.2. Enroll a subgroup of colorectal cancer patients identified through the Louisiana Tumor Registry (LTR). An additional 500 colorectal cancer patients, approximately half non-Hispanic white and half African American, will be identified through the LTR and enrolled into the ROCS protocol. The survey is the same survey administered to the ROCS cohort. The Louisiana (“DANCE-CRC”) cohort will not be followed beyond baseline, and blood will not be collected (tumor tissue, however, will be collected, deidentified, and sent for processing through Dr. Rozek's laboratory at Georgetown University).The proposed cohorts will provide for a broad research agenda evaluating cancer outcomes in African Americans across a variety of factors from individual, provider, health care system and community perspectives. These factors include tumor characteristics driving individualized treatment planning, quality of life after a diagnosis and recurrence. Utilizing the MDCSS registry, we will enroll a large population-based sample of African-American cases with lung, breast, colorectal, and prostate cancers and their caregivers resulting in a cohort that will provide substantial benefit to the cancer research community. KCI has a strong history of research in the African-American community and the faculty represents a breadth of experience that includes clinical oncology, genetic epidemiology, environmental exposures, quality of life, treatment decision making, racism/discrimination, and health behaviors. Drs. Schwartz and Beebe-Dimmer have been and will continue to be generous collaborators with other institutions to ensure that this resource will be extensively utilized. The proposed overall cohort will be the only one of its kind, to our knowledge, filling a substantial gap in our understanding of the determinants driving cancer outcomes in African Americans. In addition to registry data detailing cancer specifics, yearly surveys have collected information about individualized treatment experiences, heath histories, family histories, quality of life after a diagnosis, recurrence and caregiving. Population: Adult cancer survivors (see inclusion criteria in next section) Molecular Technologies: Genotyping: Infinium Expanded Multi-Ethnic Genotyping Array (MEGAEX) DNA Sequencing: Illumina NovaSeq X Plus using XLEAP-SBS (sequencing by synthesis) Whole genome sequencingPrincipal Findings: The preliminary data collected reinforces differences by race in factors affecting cancer outcomes. Variants in DNA damage repair genes and HOXB13 may be important cancer risk factors for Black men diagnosed with prostate cancer, and are more frequently observed in men with a family history of cancer. ROCS participants reported high rates of a family history of cancer. The high rate of eligibility for Cancer genetic counseling among ROCS participants supports the need for interventions to increase referrals and uptake of genetic counseling among African Americans 60% of ROCS participants reported participating in regular physical activity (PA), with 24% reporting ≥150 min/wk. There were no differences by sex, but prostate cancer survivors were the most likely to report participating in regular PA, whereas lung cancer survivors were the least likely. Survivors who reported participating in regular PA reported higher health-related quality of life and lower depression. More African American than White survivors reported financial hardship and limiting care. More White than African American survivors reported utilizing assets, while more African American survivors reported cancer-related debt. Data available in dbGaP: Individual phenotype data Individual genotype data Individual sequencing dataSample types: Germline DNA

  Study phs003116

• Single-Cell Profiling of Premature Neonate Airways Reveals a Continuum of Myeloid Differentiation

  We set out to develop a reference single-cell transcriptomic profile of airway aspirate samples from extremely premature neonates (collected within an hour of birth). In this study, we profiled samples from 10 subjects. We identified cells in the airways of premature neonates representing a continuum of myeloid differentiation, including fetal monocytes, differentiating myeloid cells, and macrophages. Trajectory analysis identified two trajectories consistent with interstitial and alveolar macrophages, and a bridging trajectory providing an alternative route between these terminal states. We defined 259 alveolar-specific genes, 666 interstitial-specific genes, and 285 bridging-specific genes providing the first single-cell transcriptional map of differentiating airway macrophages in humans.

  Study phs003427

• Center for Common Disease Genomics (CCDG) - Cardiovascular: Harvard Gene-Diet Interaction in a Costa Rican Cohort

  The National Human Genome Research Institute (NHGRI) has funded the Centers for Common Disease Genomics (CCDG), a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes and to better understand the general principles of genomic architecture underlying common, complex inherited diseases. This study contains whole genome sequence data and associated variant calls of more than 4200 participants in a cohort collected by the Harvard School of Public Health. The cohort includes subjects from thirty-four countries in the Central Valley of Costa Rica covering a full range of socioeconomic levels, as well as urban, peri-urban and rural lifestyle

  Study phs002282

• Proteogenomic discovery of a novel class of cancer antigens by HLA ligandome analysis of colon cancer tissues

  CD8+ T cells recognize peptides displayed by HLA class I molecules on cell surfaces, monitoring pathological conditions such as cancer. Recent advances in proteogenomic analysis of HLA ligandomes have demonstrated that cells present a subset of cryptic peptides derived from non-coding regions of the genome; however, the roles of cryptic HLA ligands in tumor immunity remain unknown. In the present study, we comprehensively and quantitatively investigated the HLA class I ligandome of a set of human colorectal cancer (CRC) and matched normal tissues, showing that cryptic translation products account for a small fraction of the HLA class I ligandome and serve as antigens for patient T cell surveillance against colon cancer.

  Study JGAS000280

• Host-microbe interactions in a novel SARS-CoV-2 human challenge model

  This research leverages previously collected clinical data and samples from a first-in-human SARS-CoV-2 challenge study conducted in healthy adults without serological evidence of prior infection or vaccination. We performed shotgun metagenomic and RNA sequencing of serially collected mid-turbinate nasal and throat swab samples from 34 adults who were inoculated with a wild-type virus, 18 (53%) of whom developed PCR-confirmed infection. By integrating microbiome and host transcriptome data, this research will provide insight into the complex interplay between the upper respiratory microbiota and the host immune system, offering a deeper understanding of factors that influence susceptibility to and severity of SARS-CoV-2 and other respiratory viral infections.

  Study EGAS50000001440

• Illumina Omni5 SNP chip genotyping of MacTel cases and unaffected controls for a genome-wide association study

  Macular telangiectasia type 2 (MacTel) is a rare neurovascular degenerative retinal disease. To identify genetic susceptibility loci for MacTel, we performed a genome-wide association study (GWAS). We genotyped 704 samples, of which 678 have consented to be available here. These samples mainly include MacTel cases but also some unaffected controls (often spouses). The samples were collected through the MacTel Project (funded by the Lowy Medical Research Institute), which includes a registry and extensive clinical analysis to confirm the presence of MacTel in affected individuals. Additional controls were obtained from dbGap [phs000429.v1.p1]. After QC steps, the GWAS utilised 476 cases and 1733 controls of European ancestry.

  Study EGAS00001002249

• scD&D-seq of mobilized PBMC from a healthy individual having IDH2 R140Q CHIP

  Single-cell D&D-seq profiles from a mobilized CHIP (clonal hematopoiesis of indeterminate potential) PBMC sample (2 replicates) co-profiled with IDH2 R140Q GoT-ChA.

  Study EGAS50000001590

• Whole Exome Sequencing of a Chinese Cataract Girl

  Whole exome sequencing of a Chinese girl with congenital cataract. The dataset contains one sample with two fastq files. The novel PAX6 mutation (c.221G>A) is associated with congenital cataract, and the WFS1 mutation (c.2070_2079del) interactively aggravates this process.

  Dataset EGAD00001008267