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• Detection and characterization of lung cancer using cell-free DNA fragmentomes

  Lung cancer remains the leading cause of cancer death world-wide, largely due to its late diagnosis. Non-invasive approaches for assessment of cell-free DNA (cfDNA) provide an opportunity for detection and intervention that may have broader accessibility than current imaging approaches. Using a machine learning model for detecting tumor-derived cfDNA through genome-wide analyses of cfDNA fragmentation, we examined a prospective study of 365 individuals at risk for lung cancer (Lung Cancer Diagnostic Study, LUCAS), including 129 individuals ultimately diagnosed with lung cancer and 236 individuals determined to not have lung cancer. We externally validated the cancer detection model using an independent cohort of 385 non-cancer individuals and 46 predominantly early stage lung cancer patients. Combining fragmentation features with clinical risk factors and CEA levels followed by CT imaging detected 94% of patients with cancer across stages and subtypes, including 91% of stage I/II and 96% of stage III/IV, at 80% specificity. Genome-wide fragmentation profiles across ~13,000 ASCL1 transcription factor binding sites could be used to distinguish individuals with small cell lung cancer (SCLC) from those with non-small cell lung cancer (NSCLC) with high accuracy (AUC=0.98). Among individuals with lung cancer, a higher cfDNA fragmentation score was associated with tumor size and invasion, and represented an independent prognostic indicator of survival. These studies provide a facile approach for non-invasive detection of lung cancer and clinical management of this disease.

  Study EGAS00001005340

• The Effect of the Menstrual Cycle on DNA Expression in the Normal Human Breast Epithelium

  The Susan G. Komen for the Cure® Tissue Bank at the IU Simon Cancer Center [www.komentissuebank.iu.edu] (KTB) was established expressly for the prospective collection of normal, healthy breast tissue from volunteer donors. Blood is also obtained from donors at the time of donation and is processed for serum, plasma and peripheral blood leukocyte DNA. Specimens are annotated and data includes age, race, ethnicity, personal health history, family cancer history, medication usage at the time of donation, and breast cancer risk factors. Premenopausal donors to the KTB were identified by a query of the Bank's database. Hematoxylin and eosin stained sections of the formalin-fixed paraffin-embedded tissue of the identified donors were reviewed and tissue was graded on the basis of the abundance of epithelium within the section. Only tissue containing abundant epithelium was considered for this study. Based on dates, the specimens of nine women in the follicular phase of the menstrual cycle and five in the luteal phase were chosen. Six donors using hormonal contraception at the time of donation were also included. Whole blood obtained from 19 of the 20 donors at the time of tissue donation was available and it was processed for serum. Estradiol, estriol, luteinizing hormone and progesterone concentrations were determined by the Indiana University Health Pathology Laboratory using a Beckman Unicel DxI 800 Immunoassay System. The phase of the menstrual cycle was verified by serum progesterone concentration. The epithelium of these 20 specimens was microdissected from multiple 8 micron frozen tissue sections. Total RNA extracted from the tissue was subsequently depleted of rRNA via locked nucleic acid probes. This enabled profiling of both poly-A and non-poly-A RNA species. Barcoded cDNA libraries from the 20 normal breast epithelia were prepared and sequenced on an Applied Biosystems (AB) SOLiD3 or SOLiD 4 platform. RNA-seq reads for each sample were then mapped to the human genome (hg19) using the LifeScope software version 2.5.1 (Life Technologies, Foster City, CA) and BAM (Binary Alignment/Map) files generated. Read counts for each gene were derived from the output BAM files using the RefSeq database (UCSC Genome Brower) as the gene model.

  Study phs000644

• University of Utah Pelvic Organ Prolapse Disorder Study

  The overall purpose of this University of Utah Pelvic Organ Prolapse Disorder Study was to identify and localize predisposition genes contributing to pelvic organ prolapse (POP). POP cases recruited for this study were identified by one of three methods: high-risk POP pedigree cases, POP sister pairs, and surgically-treated POP cases reporting a family history of POP. High-risk POP pedigree cases were identified using the Utah Population Database (UPDB), a genealogy database of residents in Utah that has been linked to diagnostic ICD9 and CPT codes in medical records at the University of Utah and Intermountain Healthcare. We identified families with a significant excess number of POP cases compared to matched population rates and targeted these individuals for recruitment as well as any other POP cases in the family. POP sister pair cases were identified at the University of Utah Urogyncology clinic for women who had undergone POP surgery and also self-reported one or more sisters who were also surgically treated for POP. POP affection status of all sisters was confirmed either by physical examination or by chart review. Surgically treated-POP cases reporting a family history of POP were identified at the University of Utah Urogyncology clinic by self-report of a family history of POP. Efforts were made to recruit other affected family members and confirm affection status. To obtain DNA, subjects provided either a blood specimen or saliva. Medical records were reviewed by a urogynecologist and diagnostic information for pelvic organ prolapse and stress and overactive bladder were obtained. Collected DNA was genotyped and analyzed. To maintain confidentiality of the familial data, genetic data from only one subject per family has been submitted to dbGaP. Use of the University of Utah Pelvic Organ Prolapse Disorder Study data is limited to investigators studying pelvic floor disorders. These pelvic floor disorders include pelvic organ prolapse, urinary and anal incontinence, and other conditions related to weakening or injury to the muscles and connective tissue in the pelvis as a result of pelvic surgery, pregnancy, or vaginal delivery of a child. These data will be used only for research purposes related to pelvic floor disorders. They will not be used to determine the individual identity of any person or their relationship to another person or for research on non-disease traits.

  Study phs001439

• Gabriella Miller Kids First Pediatric Research Program in Germline and Somatic Variants in Myeloid Malignancies in Children

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource).All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed.This project aims to sequence an unparalleled number of cases of de novo Acute Myeloid Leukemia (AML) and Down Syndrome AML (DS-AML), to establish a database comprised of genomic and transcriptome information which can be interrogated for both somatic and germline variants. Identification of the somatic variants will provide valuable data on the potential genes and pathways that can be targeted for therapeutic purposes. In addition, interrogation of the host’s constitutional genome may yield valuable information about potential germline variants that, in combination with the somatic data, might provide a more informed approach to patient care. For those patients with predisposition mutations, chemotherapy alone might not be adequate for cure, and stem cell transplantation might be required. Also, those who might be at high risk of adverse secondary events (cardiac complications, secondary malignancies, etc.) can be identified early and their therapy can be tailored to minimize anticipated complications. Thus, we propose that the optimum outcome can only be obtained through comprehensive interrogation of the somatic and germline genomes to fully annotate the genomic makeup of the leukemia and its host. Knowing the genomic and transcriptomic makeup of these patients, along with a full complement of clinical characteristics for this cohort, will be critical for making strong correlations which may aid in therapeutic development for future patients. The de novo AML, DS-AML, and Acute Promyelocytic Leukemia (APL) cases were all collected through clinical protocols conducted by the Children’s Oncology Group (COG). In addition to funding from the Gabriella Miller Kids First Pediatric Research Program, the DS-AML cohort was specifically funded by the Lifespan to Understand Down syndrome (INCLUDE) Project.

  Study phs002187

• Immune-Related Adverse Events after Immune Checkpoint Blockade-Based Therapy are Associated with Improved Survival in Advanced Sarcoma

  Immune activation after immune checkpoint blockade (ICB) can lead to a unique group of adverse events (AEs), which have been associated with improved outcome in many carcinomas. The association between immune-related AEs (irAEs) and outcome in patients with sarcoma is not well studied. This study has two components: (1) a retrospective clinical study of irAEs among 131 patients treated with ICB at Memorial Sloan Kettering Cancer Center and (2) an analysis of a subset of these patients who have whole transcriptome sequencing available for analysis. In the clinical study portion, we reviewed a cohort of patients with advanced sarcoma treated on prospective clinical trials utilizing ICB-based therapy between April 2017 and January 2020. The objectives were to pool the safety data from each trial, identify irAEs, and correlate them with best overall response by RECIST 1.1, progression-free survival (PFS) and overall survival (OS). Association of irAEs with response and survival was assessed using a Cox regression model. A total of 131 patients were included. Forty-two (32%) had at least one irAE of any grade and 16 (12%) had at least one Grade ≥ 3 irAE. On Cox analysis adjusting for clinical covariates that were significant in the univariate setting, the hazard ratio (HR) for an irAE (HR 0.662, 95% CI 0.421 - 1.041) approached, but did not reach statistical significance for PFS (P = 0.074), while patients had a significantly lower HR for OS (HR 0.443, 95% CI 0.246 – 0.798; P = 0.007) compared to those without or before an irAE. Tumor samples with available RNA sequencing data were stratified by presence of an irAE to identify patterns of differential gene expression. In total, 71 unique patients had RNA sequencing available for analysis. The transcriptomes of 31 of these patients have been previously uploaded to dbGaP (phs002852), leaving 36 unique transcriptomes that have not been previously publicly shared. Three patients did not agree for their sequencing to be publicly shared. Therefore, 33 unique patient samples will be uploaded to this dbGaP study. Overall, this study found that gene expression profiling on baseline tumor samples from patients who had an irAE had higher numbers of tumor-infiltrating dendritic cells, CD8+ T cells, and regulatory T cells as well as upregulation of immune and inflammatory pathways.

  Study phs003284

• Genome_wide_association_study_of_vaccine_responses_in_infants_living_in_the_Developing_World__VaccGene___Phase_II_African_Cohorts

  Human genetic heterogeneity accounts for approximately 70% of the observed variability inresponse to common childhood vaccinations. Identifying the elements of this heterogeneitywill enable the development of vaccines which have improved clinical and cost effectivenessthrough rational adjuventation approaches, or by targeting particular at-risk or responsivesubgroups. The studies published to date have been limited in terms of the number of vaccinesubtypes analysed, diversity of the populations included, sample sizes and breadth of otherenvironmental and lifestyle variables which may explain some of the remainder of variation inthe response to each vaccine. Nevertheless, these studies have proposed that the geneswhich harbour the variants associated with vaccine responsiveness reside within regions ofthe genome associated with immune function such as the HLA locus and FOXP1and ITGAL.We are proposing one of the largest genome-wide association studies of vaccine responseever undertaken, which will provide unparalleled power to identify the genetic factorsassociated with the response to all of the most commonly used childhood vaccinesworldwide. For the first phase of the project (Prelim I0308) we genotyped ca. 1,400 childrenfrom the Entebbe Mother and Baby (EMaB) study, an ongoing birth cohort in southernUganda, using the Illumina HumanOmni2.5-8 chip. Analyses for response to vaccinationagainst diphtheria, tetanus, pertussis, Haemophilus influenzae, measles, hepatitis B and BCGare now underway. Working alongside other ongoing studies, we plan for the second phaseof the project to expand sample sizes to up to 7,000 individuals in total. This large cohort willinclude 1,500 South African infants, 500 Burkina Faso infants, 1,800 children from Ecuadorand up to 1,800 from a variety of countries (MAL-ED Consortium). The principal measuredphenotypes will be the serological responses at 6 or 12 months of age to the vaccinesadministered to all enrolled children as part of expanded programme of immunisation in allcountries. As for the primary Ugandan study the responses will be analysed as quantitativetraits using mixed model (GEMMA) analyses following imputation using a combined 1000Genome and African Genome Variation Project reference panel. The data will be analysed asone large discovery mega-analysis to maximise the power of finding the relevant associatedvariants. Interim GWAS analyses will be performed on each population to test for populationspecific signals. Other phenotypes that will be assessed in the new studies includequantitative response to BCG, rotavirus and pneumococcal vaccines (South Africa, Ecuadorand Uganda), clinical and immunological response to malaria vaccines (Burkina),immunological correlates of atopy (Ecuador and Uganda) and malaria infection (Burkina,Ecuador and Uganda) in addition to non-communicable disease traits such as blood pressurepage 1[A8] If applicable, provide text (abstract) which will accompany data for this study in the ENA/EGA.[A9] Does this project use samples?[A10] Please choose which types of sample you will be using[A12] Please state the anticipated date (month/year) samples will be available in-house (if known). If samples arealready in-house, type 'in-house' here. Please note that for sequencing, genotyping and microarrays this is essentialfor scheduling the work.[A13] Please state the anticipated project start date (month/year).[A14] Please state the project duration (months).[A15] Please read WTSI's Data Sharing Policy and Guidelines, then explain your data sharing plans for the project[A16] Are the data sharing plans of this project compliant with the Institute's Guidelines?[A17] Are there any conflicts of interest related to this proposal?(Uganda).We are requesting funds to genotype on the Illumina HumanOmni2.5-8 platform 2,000 Africaninfants recruited through ongoing maternal and child vaccine clinical trials (againstpneumococcus in Soweto, South Africa, and malaria in Banfora, Burkina Faso). The DNAfrom the Burkina cohort is at the University of Oxford and ready to be shipped, while the DNAfrom the South African cohort will be available by mid-2014. Appropriate consent for geneticanalyses has been acquired for the proposed study cohorts from both local ethics committeesand UK-based Committees.

  Study EGAS00001000918

• Population Architecture Using Genomics and Epidemiology (PAGE): Epidemiologic Architecture for Genes Linked to Environment (EAGLE) - BioVU Cancer Project

  As part of Population Architecture using Genomics and Epidemiology PAGE study (Phase I), the Epidemiologic Architecture using Genomics and Epidemiology (EAGLE I) project accessed both epidemiologic- and clinic-based collections. The epidemiologic-based collection of EAGLE I included the National Health and Nutritional Examination Surveys (NHANES), ascertained between 1991-1994 (NHANES III), 1999-2002, and 2007-2008. NHANES is a population-based cross-sectional survey now conducted every year in the United States to assess the health status of Americans at the time of ascertainment and to assess trends over the years of survey. Genetic NHANES consists of 19,613 DNA samples linked to thousands of variables including demographics, health and lifestyle variables, physical examination variables, laboratory variables, and exposures. NHANES is diverse with almost one-half of the samples (46.4%) coming from self-reported Mexican Americans and non-Hispanic blacks. In contrast to NHANES, BioVU is a clinic-based collection of >150,000 DNA samples from Vanderbilt University Medical Center linked to de-identified electronic medical records (EMRs). Approximately 12% of BioVU's overall DNA sample collection is from African American, Hispanic, and Asian patients. The overall goals of PAGE I and EAGLE I were broad and several-fold: Replicate genome-wide association study (GWAS)- identified variants in European Americans; Identify population-specific and trans-population genotype-phenotype associations; Identify genetic and environmental modifiers of these associations. NHANES is an excellent resource for the study of quantitative traits associated with common human diseases. However, given that the age range of NHANES spans childhood to late adulthood and not all diseases are surveyed, NHANES is less useful for the study of adult-onset diseases such as major cancers. Therefore, under American Recovery and Reinvestment Act (ARRA) funding, EAGLE as part of PAGE I defined eight major cancers sites for genetic analysis in BioVU, Vanderbilt's biorepository linked to de-identified EMRs. The eight major cancers defined for this study included melanoma, breast, ovarian, prostate, colorectal, lung, endometrial, and Non-Hodgkin's lymphoma (NHL). Cancer cases were defined using a combination of ICD-9 codes and tumor registry entries. Controls include BioVU participants without cancer and encompassing the age and gender distributions of cancer cases. Targeted genotyping of GWAS-identified variants for these diseases (124 SNPs) and ancestry informative markers (128 AIMs) was performed by the Center for Human Genetics Research Vanderbilt DNA Resources Core. After quality control, a total of 116 cancer-associated SNPs and 122 AIMs were available for downstream analyses.

  Study phs000559

• GA4GH

  Standards The EGA is a long-standing supporter of the Global Alliance for Genomics & Health (GA4GH) to enhance responsible sharing of human genetic data through the development of interoperable global standards for human data access. The EGA is one of the founding GA4GH Driver Projects and has contributed to the development and implementation of several GA4GH standards and APIs. Below is a list of the GA4GH standards and APIs that are currently available or planned for implementation at EGA. TechnicalStandards Purpose SpecificationVersion SupportedVersion Implementation Large Scale Genomics htsget A protocol for secure, efficient, and reliable access to sequencing read and variation data. V1.3.0 V1.0.0 Specification Documentation Endpoint Read File Formats (SAM/BAM/CRAM) Specifications for storing next-generation sequencing read data. V3.0.0 V3.0.0 Implementation Example of Usage Variation File Formats (VCF/BCF) The specifications for Variant Call Format Files (VCF) and its binary counterpart BCF. V4.0.0 V2.0.0 V4.0.0 V2.0.0 Implementation Example of Usage Crypt4GH v1.0 Enables direct byte-level compatible random access to encrypted genetic data stored in community standards (e.g. CRAM, VCF) V1.0 V1.0 Specification Documentation Endpoint refget API Enables access to reference sequences using an identifier derived from the sequence itself. V1.2.6 NA Specification RNAget API v1 Provides a means of retrieving data from several types of RNA experiments including (i) feature-level expression data from RNA-seq type measurements and (ii) coordinate-based signal/intensity data similar to a bigwig representation via a client/server model. V1.0.0 NA Documentation Discovery Beacon v2 Supports discovery of genomic variants, phenotypes, and individuals V1.0.1 V0.3 Web UI API Source Code Service Info API v1 The Service Info API is an endpoint for describing GA4GH service metadata, designed for extension and inclusion in other APIs. Service info is used to describe a single service, while Service Registry is used to describe multiple services. V1.0.0 NA Documentation Service Registry API v1 provides information about other GA4GH services, primarily for the purpose of organizing services into networks or groups and service discovery across organizational boundaries. V1.0.0 NA Documentation Data Use Researcher Identities Data Use Ontology (DUO) Allow users to semantically tag genomic datasets with usage restrictions, allowing them to become automatically discoverable based on a health, clinical, or biomedical researcher’s authorisation level or intended use. 2021-02-23 2021-02-23 Specification Documentation Endpoint Authentication & Authorization Infrastructure (AAI) The GA4GH AAI specification leverages OpenID Connect (OIDC) Servers for use in authenticating the identity of researchers desiring to access clinical and genomic resources from data holders adhering to GA4GH standards, and to enable data holders to obtain security-related attributes of those researchers. V1.2.0 V1.2.0 API URI: ega.ebi.ac.uk:8443 Documentation Repository Researcher IDs (passport, visa) Specify the collection of researchers that may access a dataset at any given time, and the credentials they must supply. V1.0.1 V1.0.1 Specification Documentation Endpoint Cloud Tool Registry Service API TRS is a standard API for exchanging tools and workflows to analyze, read, and manipulate genomic data. V2.0.1 NA Documentation Repostiory Data Repository Service API ​DRS API is a standard for building data repositories and adapting access tools to work with those repositories, works with other approved APIs from the GA4GH Cloud Work Stream to allow researchers to discover algorithms across different cloud environments and send them to datasets they wish to analyse. V1.0.3 NA Documentation Repostiory Workflow Execution Service API This API lets users run a single workflow (defined using CWL or WDL) on multiple different platforms, clouds, and environments, and be confident that it will work the same way. The API provides methods to request that a workflow be run, pass parameters to that workflow, get information about running workflows, and cancel a running workflow. V1.0.1 NA Documentation Repostiory Genomic Knowledge Standards Variation Representation v1 Provides a flexible framework of computational models, schemas, and algorithms to precisely and consistently exchange genetic variation data across communities. V1.3.0 EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Clin/ Pheno Data Capture Phenopackets Provides information models with different levels of complexity to enable high level clinical phenotype information as well as deep clinical phenotype information to be exchanged. V2.0.0 Included in Ongoing Submissions EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Driver Project The EGA, jointly coordinated by the EBI and the CRG, was announced, in 2017, to be one of the 15 Driver Projects for GA4GH. Driver Projects are international genomic data initiatives, focussed on real projects and challenges that will guide the development efforts in order to accelerate and enable completely responsible and standarised data sharing by 2022. All chosen Driver Projects make a cross-sectional effort by playing an important role across the different workstreams. Thomas Keane, Jordi Rambla, Mallory Freeberg, and Aina Jené have been named Driver Project Champions for the EGA. All Driver Project Champions will be leading this ambitious initiative for the following years.

  Documentation about/projects-and-funders/ga4gh

• Sequencing of an organoid biobank for childhood kidney cancers that captures disease and tissue heterogeneity.

  Kidney tumors are among the most common solid tumors in children, comprising several distinct subtypes differing in many aspects, including cell-of-origin, genetics, and pathology. Pre-clinical cell models capturing the disease heterogeneity are currently lacking. Here, we describe the first pediatric cancer organoid biobank. It contains tumor and matching normal organoids from over 50 children with different subtypes of kidney cancer, including Wilms tumors, malignant rhabdoid tumors, renal cell carcinomas, and congenital mesoblastic nephromas. The malignant rhabdoid tumor organoids represent the first organoid model for tumors of non-epithelial origin. The tumor organoids retain key properties of native tumors, useful for revealing patient specific drug vulnerabilities. We further demonstrate that organoid cultures derived from Wilms tumors consist of multiple different cell types, including epithelial, stromal and blastemal-like. Our organoid biobank captures the cellular heterogeneity of pediatric kidney tumors, providing a representative collection of well-characterized models for basic cancer research, drug-screening, and personalized medicine.

  Study EGAS00001003853

• Reference exome data for Australian Aboriginal populations to support health-based research

  Whole exome sequencing (WES) is a popular and successful technology which is widely used in both research and clinical settings. However, there is a paucity of reference data for Aboriginal Australians to underpin the translation of health-based genomic research. Here we provide a catalogue of variants called after sequencing the exomes of 50 Aboriginal individuals from the Northern Territory (NT) of Australia and compare these to 72 previously published exomes from a Western Australian (WA) population of Martu origin. Sequence data for both NT and WA samples were processed using an ‘intersect-then-combine’ (ITC) approach, using GATK and SAMtools to call variants. A total of 289,829 variants were identified in at least one individual in the NT cohort and 248,374 variants in at least one individual in the WA cohort. Of these, 166,719 variants were present in both cohorts, whilst 123,110 variants were private to the NT cohort and 81,655 were private to the WA cohort. Our data set provides a useful reference point for genomic studies on Aboriginal Australians.

  Study EGAS00001003745