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• Dual-mTOR inhibitor Rapalink-1 reduces prostate cancer patient-derived xenograft growth and alters tumor heterogeneity

  Bone metastasis is the leading cause of prostate cancer (PCa) mortality, frequently marking the progression to castration-resistant PCa. In this study, we compared the molecular pathways enriched in a set of bone metastasis from breast and prostate cancer from snap-frozen tissue. To further model PCa drug resistance mechanisms, we used two patient-derived xenografts (PDX) models of bone-metastatic PCa, BM18 and LAPC9.

  Study EGAS00001004431

• Differential gene expression in the colon mucosa of irritable bowel syndrome patients with mixed type symptoms

  The aim of this study is to characterize the pathophysiology of the irritable bowel syndrome (IBS) on the functional level and in parallel on the gene expression level. For this purpose RNAseq of mucosal biopsies was performed. The data from the differential expression analysis will be further processed by Ingenuity Pathway Analysis (IPA) software to gather Information on activated or inhibited signaling pathways in the disease.

  Study EGAS00001004835

• Genetic regulation of RNA splicing in human pancreatic islets

  Genetic variants that influence transcriptional regulation in pancreatic islets play a major role in the susceptibility to type 2 diabetes (T2D). For many susceptibility loci, however, the mechanisms are unknown. To this end, we examined splicing and gene expression QTLs (sQTLs and eQTLs) in pancreatic islets from 399 human donors from publicly available cohorts and in-house data. Here we provide newly generated RNA-seq data and genotyping array data from 101 donors.

  Study EGAS00001006440

• Nasal epithelial cells of PCD and non-PCD patients grown at air-liquid interface for RNAseq analysis

  Raw RNAseq data files of genetically unsolved PCD patients used for transcriptomic analysis aming to uplift the diagnostic rate. The non-PCD patients were used as a clinical comparator to the PCD patients. Majority of the nasal epithelial cells used for RNAseq were cultured at an air-liquid interface for 21 days, unless the data file name indicates a different air-liquid-culture time-point.

  Study EGAS00001006632

• Exome sequencing of HCV+ lymphoma

  The present retrospective study aimed to explore the genetic landscape of a well-characterized series of 34 HCV-associated B-cell lymphomas from the observational multicentric ANRS HC-13 Lympho-C Study using tumor and matched germline whole exome sequencing (WES). It reported the first series of VHC-positive lymphoma patients analyzed by WES. Our results provide an overview of the genetic landscape associated to HCV-related B-cell lymphomas and highlight some novel putative candidate genes.

  Study EGAS00001006860

• The Landscape of N-6 Methyladenosine in Primary Localized Prostate Cancer

  Using meRIP-sequencing, we profiled N-6 methyladenosine (m6A) in a cohort of 148 primary prostate cancer samples as part of the Canadian Prostate Cancer Genome Network project (CPC-GENE). Paired-end sequencing of 150 bp reads were mapped to GRCh38.p13 using annotations from gencode.v34.chr_patch_hapl_scaff.annotation.gtf. Peaks were called using MeTPeak, joint peaks were identified and IP reads were quantitated, normalized and adjusted using Input reads to obtain estimates of m6A abundance.

  Study EGAS00001006925

• Epithelioid haemangioendothelioma (EHE) case series from the Stafford Fox Rare Cancer Program

  Nine EHE cases with comprehensive histologic and molecular profiling from the Walter and Eliza Hall Institute of Medical Research Stafford Fox Rare Cancer Program were collated via nation-wide referral to the Australian Rare Cancer Portal. Molecular analysis of RNA, DNA or both was possible in seven of nine cases. Survival was highly variable and unrelated to molecular profile. DNA sequences for two cases are deposited here.

  Study EGAS00001007474

• To_profile_the_landscape_of_sebaceous_tumours___RNA

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract RNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted RNA will be used for RNA sequencing.

  Study EGAS00001007803

• Synthetic - GDI synthetic data

  Synthetic - The Genomic Data Infrastructure (GDI) project is enabling access to genomic and related phenotypic and clinical data across Europe. It is doing this by establishing a federated, sustainable and secure infrastructure to access the data. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure the GDI project (funding: EC H2020 under grant agreement number 101081813) is acknowledged.

  Study EGAS50000000678

• Benchmark Dataset for Somatic Mutation Calling in Cell-Free DNA

  This study provides a comprehensive benchmarking resource for somatic variant detection in cell-free DNA (cfDNA) from cancer patients. Longitudinal plasma samples from colorectal and breast cancer cohorts were selected to create patient-matched dilution series spanning ultra-low to high circulating-tumour-DNA (ctDNA) fractions, while preserving each individual’s germline and clonal haematopoiesis background. Deep whole-genome sequencing (150×) and ultra-deep whole-exome sequencing (2,000×) generated a reference call set of ~37,000 single-nucleotide variants and ~58,000 insertions/deletions. These data enabled systematic evaluation of nine somatic variant callers across variable ctDNA levels and sequencing depths, and were further used to explore machine-learning–guided parameter tuning. The resulting dataset offers an openly accessible framework for developers and clinicians to assess and optimize somatic variant calling in liquid biopsy applications.

  Dataset EGAD50000001870

• Oral microbiome metagenomic sequencing - Human Phenotype Project (HPP)

  This study characterizes the oral microbiome of participants enrolled in the Weizmann Institute Human Phenotype Project (HPP), a longitudinal cohort study. Oral swab samples were collected and subjected to shallow whole-genome sequencing using the Gencove low-pass sequencing platform. Raw reads include residual human host sequences in addition to microbial sequences. The dataset comprises metagenomic FASTQ files from [N] participants. Data access is restricted in accordance with participant informed consent and Weizmann IRB approval

  Study EGAS50000001763

• Single cell transcriptomic data of human gut macrophages

  Cellular suspensions (∼15000 cells, with expected recovery of ∼7500 cells) of sorted CD45+ HLA-DR+ CD14+ macrophages from colonic mucosa and muscularis propria were loaded on the 10X Chromium Controller instrument (10X Genomics) according to the manufacturer’s protocol using the 10X GEMCode proprietary technology. All samples from individual patients were loaded in one batch. The Chromium Single Cell 3´ v2 Reagent kit (10X Genomics) was used to generate the cDNA and prepare the libraries, according to the manufacturer’s protocol. The libraries were then equimolarly pooled and sequenced on an Illumina NextSeq500 using HighOutput flow cells v2.5. A coverage of 400M reads per sample was targeted, in order to obtain 50 000 reads per cell. The raw data were then demultiplexed and processed with the Cell Ranger software (10X Genomics) v2.1.1.

  Dataset EGAD00001007765

• Disease specific alterations in the olfactory mucosa of patients with Alzheimer’s disease

  The sample AD_Library_1, AD_Library_2 and Control_Library were run on a Chromium Chip B with the Chromium Single Cell 3′ Library & Gel Bead Kit v3 kit (10x Genomics, CA, USA) . The 3’ gene expression libraries were sequenced at an approximate depth of 50,000 reads per cell using the NovaSeq 6000 S1 (Illumina, San Diego, CA, USA) flow cells. Cell Ranger v.3.0.2 was used to analyze the raw base call files. FASTQ files and raw gene-barcode matrices were generated and aligned human genome GRCh37 (hg19). The samples were integrated in R v.4.0.3 and generated Seurat objects, two related to AD samples and one to control samples, were analyzed using the Seurat package v.4.0.3 to perform downstream analysis, clustering of the cells and differential expression.

  Dataset EGAD00001008560

• Flexible and rapid validation of structural variants using adaptive sampling

  The goal of the study is to confirm and further characterize structural variants and complex genomic rearrangements using adaptive sampling with Oxford Nanopore Sequencing. Individuals with known structural variants were included in the study and the known rearrangement regions were targeted in the sequencing experiments. In addition to long-read coverage over the targeted regions (around 25X coverage), the rest of the genome is covered by short off-target reads (around 5X coverage).

  Study EGAS50000001279

• Follow_up_for_second_tier_signals_from_the_arcOGEN_GWAS

  The arcOGEN UK nationwide consortium has been funded by the arc to undertake a genome-wide association scan in osteoarthritis. GWA genotyping has been carried out at the Sanger on the illumina 610k array. This replication study was desinged to follow-up second-tier signals from the arcOGEN GWS in 25 SNPs (1Sequenom iPLEX) with p<5x10^-6 on 6000 additional UK OA and control samples.

  Study EGAS00001001017

• RNAseq data of polyA+ RNA from Leukocytes from 624 individuals of the ProgeNIA cohort.

  We sequenced the polyA+ fraction of the RNA of the leukocytes from 624 sardinian individuals with RNAseq. Prior to library preparation we added either ERCC ExFold RNA Spike-In. An average of 60M reads per samples with 51 bp paired-end reads were generated on a HiSeq 2000 (Illumina). Sequencing reads were then aligned using STAR-2.2.0c2 to the h37d5 reference genome supplemented with the ERCC spike-ins sequences. We further provided an exon-exon junction database that we generated from the GENCODE v14 annotation. In order to remove a contamination from a parallel experiment, we discarded any reads that mapped to the genomic regions of CBLB (chr3:105370773-105592330) and BCL11A (chr2:60672555-60784156). Filtered aligned reads (bam format) are shared.

  Dataset EGAD00001003102

• The Causes of Clonal Blood Cell Disorders Study - SCOR (2018-04-19)

  We will take a bone marrow aspirate and peripheral blood samples from a healthy patient aged around 60, and use flow cytometry to isolate 100 HSCs, 50 MEPs, and 50 GMPs. We will grow these up into colonies, then whole genome sequence each colony. Somatic mutations will act as a unique barcode for each clone. We will then design a panel for targeted resequencing of the mutations that we find. It will then be possible to look for these mutations in the peripheral blood over several years, to see the dynamics of how HSCs contribute to the peripheral blood in health. This dataset contains all the data available for this study on 2018-04-19.

  Dataset EGAD00001004086

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002696

• CPTAC: Proteogenomic Studies of Ovarian Tumor Responses to Agents Targeting the DNA Damage Response

  There is a critical unmet need for predictors of chemo-refractory High-grade serous ovarian cancer (HGSOC). Despite over 3 decades of research on platinum responses in cancer, no predictive biomarker has been translated into clinical use. Predictors of refractory disease could spare these patients the unnecessary toxicity of a platinum-based regimen and provide a means to triage these patients to clinical trials to identify effective therapies for refractory disease. This study has approached the development of a predictor in a novel way enabling detection of a multi-analyte panel biomarker capable of detecting a subset of refractory HGSOCs with high specificity and implicating potential treatment vulnerabilities for refractory disease. We reported the first proteogenomic analysis of platinum refractoriness in HGSOC and made the novel dataset available as a resource to the community, including a ProTrack portal: http://ptrc.cptac-data-view.org/. Detailed proteogenomic profiles were generated for this study from a retrospective cohort of 242 treatment-naive HGSOCs with enriched representation of "exceptional non-responders" (i.e., patients with chemo-refractory disease). Whole genome sequence (WGS) and RNA seq FASTQ files are available through dbGaP. Proteomic data are available through the NCI Proteomic Data Commons (PDC): https://pdc.cancer.gov/pdc/.

  Study phs003152

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC -- CA209-009

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Study EGAS00001004290

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC -- CA209-010

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Study EGAS00001004291

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC-- CA209-025

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Study EGAS00001004292

• eMERGE: Northwestern (NUgene) WGS

  The NUgene Project is a biorepository with longitudinal medical information from participating patients at Northwestern Medicine affiliated hospitals and outpatient clinics. Participants' DNA samples are coupled with data from a self-reported questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 3 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated enterprise data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. The electronic MedicalRecords and Genomics (eMERGE) Network is a consortium of 9 clinical sites with EMR linked DNA biobanks, including Northwestern University and its NUgene biobank, funded by the NHGRI (National Human Genome Research Institute) to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 100,000 individuals using EMR-derived phenotypes and DNA from linked biorepositories. Using electronic phenotyping methods, the consortium has been and is using DNA samples from all participating sites to explore the genetic determinants of approximately 80 phenotypes, including both diseases and traits, for which the electronic phenotyping algorithms have or are being published on PheKB.org. Thus, for the eMERGE network, ~900 NUgene subjects were selected, as described in the study inclusion/exclusion criteria section below, to be genotyped using whole genome sequencing (WGS), for use in the eMERGE network as eMERGE subjects. The criteria used below were selected so that these subjects will likely meet the criteria to be cases and/or controls, of diverse races and/or ethnicities, for at least 1 of the ~80 phenotypes being studied within eMERGE, and could be recontacted for future research if needed.

  Study phs001191

• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK): Identification of VUR genes by exome sequencing

  Primary vesicoureteric reflux (PVUR), or non-syndromic VUR, is the most common type of congenital anomaly of the kidney and the urinary tract (CAKUT). PVUR is the single most important risk factor for pyelonephritis and renal parenchymal scarring in the pediatric age group. Renal parenchymal scarring due to PVUR is referred to as reflux nephropathy and is a major cause of end stage kidney disease requiring dialysis and kidney transplantation in children. PVUR shows familial aggregation; however, the specific genetic cause(s) of PVUR is unknown despite a number of linkage studies. Reasons for this include: variable expression of the disease, difficulty with case ascertainment, genetic heterogeneity and lack of large pedigrees that can facilitate locus identification. We have ascertained a large 97 member PVUR kindred spanning five generations. We performed a genome-wide linkage study (GWLS) on this family and obtained a significant genome-wide LOD score of 3.3 on chromosome 6p. We performed exome sequencing on affected individuals in the family and identified mutations in tenascin XB (TNXB) as a cause of familial VUR. The proposed studies have the following specific objectives: a) to define the role of tenascin genes in the etiology of PVUR, and b) to identify new PVUR causative genes. Our specific aims are (1) To perform mutation analysis in TNXB and other tenascins in a cohort of 200 individuals with familial and sporadic PVUR and define genotype/phenotype correlations. (2) To perform sequential genome wide linkage studies (GWLS) and whole exome/targeted sequencing in families with PVUR. Impact on public health: Identification of PVUR genes may provide a novel non-invasive diagnostic tool for a subset of children with PVUR. Furthermore, this research will provide insights into the pathogenesis of PVUR and further elucidate the pathways involved in the development of the kidney and genitourinary tract. Future studies will define the role of the genes in the etiology of other malformations of the kidney and urinary tract and also seek to unravel the mechanisms by which the identified gene causes PVUR and other malformations of the kidney and the urinary tract.

  Study phs000778

• GENEVA Genes and Environment Initiatives in Type 2 Diabetes (Nurses' Health Study/Health Professionals Follow-up Study)

  Type 2 diabetes mellitus (T2D) affects approximately 21 million individuals in the U.S., or almost 10% of the U.S. adult population. Because diabetes is determined by both genetic and environmental factors, a better understanding of the etiology of diabetes requires a careful investigation of gene-environment interactions. The Nurses' Health Study (NHS) and Health Professionals' Follow-up Study (HPFS) are well-characterized cohort studies of women and men for whom stored blood and DNA samples are available as well as detailed information on dietary and lifestyle variables. The major goals of the project include: 1. To conduct a GWA analysis among 3,000 cases of T2D and 3,000 healthy controls in NHS/HPFS cohorts. 2. To use information on the joint effects of genes and a list of carefully selected environmental exposures at the initial screening stage to test gene-environment interactions. This approach optimizes our power to detect variants that have a sizeable marginal effect and those with a small marginal effect but a sizeable effect in a stratum defined by an environmental exposure. For this analysis, we have developed a joint test of genetic marginal effect and gene-environment interaction. This flexible two-degree-of-freedom test generally provides greater power than standard methods and has the potential to uncover both marginal genetic effects and stratum-specific effects. The Version 1 (v1) dbGaP release of data from the GENEVA Diabetes Study (NHS/HPFS) includes data from the NHS only. The Version 2 (v2) dbGaP release includes data from both the NHS and HPFS. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to type 2 diabetes mellitus through large-scale genome-wide association studies of well-characterized cohorts of nurses and health professionals. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000091