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• National Institutes of Health The Cancer Genome Atlas (TCGA)

  The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing. TCGA is a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), which are both part of the National Institutes of Health, U.S. Department of Health and Human Services. TCGA projects are organized by cancer type or subtype. Click here for a current list of cancer types selected for study in TCGA. Data from TCGA (e.g., gene expression, copy number variation and clinical information), are available via the Genomic Data Commons (GDC). Data from TCGA projects are organized into two tiers: Open Access and Controlled Access. Open Access data tier contains data that cannot be attributed to an individual research participant. The Open Access data tier does not require user certification. Data in Open Access tier are available in the TCGA Data Portal. Controlled Access data tier contains individual-level genotype data that are unique to an individual. Access to data in the Controlled Access data tier requires user certification through dbGaP Authorized Access. Controlled Access data types consist of the following: Individual germline variant data (SNP .cel files) Primary sequence data (.bam files), which are available at GDC Clinical free text fields Exon Array files (for Glioblastoma and Ovarian projects only) NOTE: TCGA strives to release most data in the open access tier. Individual genotype or sequence files are prominent exceptions. Commonly requested files such as descriptions of somatic mutations or clinical data are open access. Please go to this page: https://tcga-data.nci.nih.gov/docs/publications/ to access all data associated with TCGA tumor specific publications. The TCGA study is utilized in the following dbGaP substudies. To view genotypes and other molecular data collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000178 TCGA study. phs000854 Genome-wide Analysis of Noncoding Regulatory Mutations in Cancer

  Study phs000178

• Comparison of the performance of two commercial genome-wide association study genotyping platforms in Han Chinese Samples

  Affymetrix 6.0, Illumina OMNIExpress, and llumina Immunochip genotype data for Han Chinese population including rheumatoid arthritis cases and controls. Data is in PLINK binary format. Illumina genotype clustering was performed using Illumina’s BeadStudio software. SNPs were reclustered using the study samples, low quality subjects were removed, and a subset of clustering results were manually inspected and verified. All SNPs with GenCall scores less than 0.15 were excluded. For Affymetrix chips, clustering was performed using the program Birdseed version 2, as implemented using Affymetrix Genotyper Console v4.0, using the default quality control (QC) thresholds.

  Study EGAS00000000131

• DAC for BillionToOne

  This is the Data Access Committee for studies published by BillionToOne.

  Dac EGAC50000000418

• Role_of_HPV_and_Interferon_in_APOBEC_mutational_signature

  The aim of this project is to test whether HPV oncogenes and /or interferon induce the APOBEC mutational signature in vitro, and to test the role of APOBEC3A in this process.

  Study EGAS00001002988

• Ribosome Profiling of Macrophages during Salmonella Infection

  The aim of this study is to assess translational changes in macrophages over a time course of Salmonella infection.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001001393

• Exome sequencing of early and late passage Patient Derived Xenogratf Tumoroids with matched Patient Derived Xenogratfs and matched normal liver

  The breadth and depth at which cancer models are interrogated contribute to successful translation of drug discovery efforts to the clinic. In colorectal cancer (CRC), model availability is limited by a dearth of large-scale collections of patient-derived xenografts (PDXs) and paired tumoroids from metastatic disease, the setting where experimental therapies are typically tested. XENTURION is a unique open-science resource that combines a platform of 129 PDX models and a sister platform of 129 matched PDX-derived tumoroids (PDXTs) from patients with metastatic CRC, with accompanying multidimensional molecular and therapeutic characterization. This specific dataset is focused on a comparison of early and late passage tumoroids transcriptomes. In this study we focused our attention on early (passage 3) and late (passage 8-12) PDXTs with their matched PDXs and normal liver

  Study EGAS50000000185

• SS18-SSX-mediated hijacking of BAF complexes drives synovial sarcoma

  Synovial sarcoma (SS) is defined by a recurrent t(x;18) chromosomal translocation, which produces the hallmark SS18-SSX oncogenic fusion. Incorporation of SS18-SSX into BAF complexes renders BAF complexes aberrant in two distinct manners: the addition of 78aa of SSX onto SS18, and concomitant loss of BAF47 assembly. However, the importance and functional contributions of each of these perturbations on BAF complex targeting and gene expression regulation remain unclear. Here we use an integrative set of genomic approaches in human cancer cell lines and primary tumor samples to define the mechanistic consequences of the SS18-SSX fusion oncoprotein. We find that SS18-SSX hijacks BAF complexes to broad polycomb domains to activate bivalent genes, driving a unique gene expression program distinct from other loss-of-function BAF complex malignancies. Importantly, restoration of BAF47 rescues enhancer activation but is dispensable for proliferative arrest in cell lines. These results demonstrate that gain-of-function SS18-SSX-mediated BAF complex targeting and gene activation is the driving event in SS, and present a mechanism by which distinct functions of BAF complexes can be co-opted to drive oncogenesis.

  Dataset EGAD00001004135

• CyTOF of 27 DLBCLs

  Diffuse large B-cell lymphoma (DLBCL) is the most common histologic subtype of non-Hodgkin lymphoma and is notorious for its clinical heterogeneity. Patient outcomes can be predicted by cell-of-origin (COO) classification, demonstrating that the underlying transcriptional signature of malignant B-cells informs biological behavior in the context of standard combination chemotherapy regimens. In the current study, we used mass cytometry (CyTOF) to examine tumor phenotypes at the protein level with single cell resolution in a collection of 27 diagnostic DLBCL biopsy specimens from treatment naïve patients. We found that malignant B-cells from each patient occupied unique regions in 37-dimensional phenotypic space with no apparent clustering of samples into discrete subtypes. Interestingly, variable MHC class II expression was found to be the greatest contributor to phenotypic diversity. Within individual tumors, a subset of cases showed multiple phenotypic subpopulations, and in one case we were able to demonstrate direct correspondence between protein-level phenotypic subsets and DNA mutation-defined subclones. In summary, CyTOF analysis can resolve both inter- and intra-tumoral heterogeneity among primary samples, and reveals that each case of DLBCL is unique and may be comprised of multiple, genetically distinct subclones.

  Dataset EGAD00001005419

• Population Architecture using Genomics and Epidemiology (PAGE): Causal Variants Across the Life Course (CALiCo): Strong Heart Study (SHS) and Strong Heart Family Study (SHFS)

  The SHS is a study of cardiovascular disease and its risk factors among American Indian men and women. Using standardized methodology, it was designed to estimate cardiovascular disease mortality and morbidity and the prevalence of known and suspected cardiovascular disease risk factors and to assess the significance of these risk factors in a longitudinal analysis. The study included 13 American Indian tribes and communities in three geographic areas: an area near Phoenix, Arizona, the southwestern area of Oklahoma, and western and central North and South Dakota. The SHS included three components: The first was a survey to determine cardiovascular disease mortality rates from 1984 to 1994 among tribal members aged 35-74 years of age residing in the 3 study areas (the community mortality study). The second was the clinical examination of 4,500 tribal members aged 45-74. The SHS has completed three clinical examinations of the original Cohort (Phase I: 1989-1991; Phase II: 1993-1995; Phase III: 1998- 1999, respectively). The third component is the morbidity and mortality (M&M) surveillance of these 4,500 participants. Yearly SHS surveillance has only 0.2% loss to follow-up. All deaths and all nonfatal CVD events are classified by standardized criteria, including details of stroke and HF. The Strong Heart Family Study (SHFS) is a genetic epidemiological study designed to investigate the heritability of CVD and its risk factors and to localize genes that contribute to CVD risk in American Indians. SHFS participants include 3,838 family members that were >/=15 years old, and ascertained through sibships of the original SHS, from 94 extended (large, multigenerational) families. Exams have occurred in a pilot Phase III (1998-1999, 900 SHFS participants), in Phase IV (2001-2003), and Phase V (2006-2009). SHFS morbidity and mortality surveillance has occurred throughout the study phases, with 0.3% lost to follow-up. Genetic data includes complete pedigree information, DNA samples from all family members, a 10cM-spaced microsatellite map used for IBD estimation and to perform linkage analysis, genotypes for more than 12,000 SNPs in candidate regions, and genotypes from commercially available SNP assays.

  Study phs000580

• Effects of tobacco smoking on the tumor immune microenvironment in head and neck squamous cell carcinoma

  This study was designed to measure immune cell differences between HNSCC patients according to smoking history. We measured CD3, CD8, FoxP3, PD-1 and PD-L1 for immune markers and Pancytokeratin to distinguish between tumor and surrounding tissue. We observed that current smokers have significantly lower numbers of immune cells surrounding the tumor than former or never smokers. GSEA analysis of RNAseq data from this cohort suggests that smoking is associated with reduced Interferon (IFN) Alpha and Gamma levels, and also with reduced levels of IFN-response cytokines CXCL9, 10 and 11. These results emphasize the hypothetical benefits of smoking cessation during treatment for HNSCC.

  Study phs001994