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• ATAC-seq

  ATAC-seq data for 26 CLL samples (7 controls, 19 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005967

• Arriba: accurate and efficient detection of gene fusions from RNA-Seq (H021)

  The identification of gene fusions from RNA sequencing data is a routine task in cancer research and precision oncology. However, despite the availability of many computational tools, fusion detection remains challenging. Existing methods suffer from poor prediction accuracy and are computationally demanding. We developed Arriba, a novel fusion detection algorithm with high sensitivity and short runtime. When applied to a large collection of published pancreatic cancer samples (n=803), Arriba identified a variety of driver fusions, many of which affected druggable proteins, including ALK, BRAF, FGFR2, NRG1, NTRK1, NTRK3, RET, and ROS1. The fusions were significantly associated with KRAS wild-type tumors and involved proteins stimulating the MAPK signaling pathway, suggesting that they substitute for activating mutations in KRAS. In addition, we confirmed the transforming potential of two novel fusions, RRBP1-RAF1 and RASGRP1-ATP1A1, in cellular assays. These results demonstrate Arriba’s utility in both basic cancer research and clinical translation.

  Study EGAS00001003554

• ctDNA diva aggregate data

  ctDNA biomarker and relevant clinical data for divarasib phase I GO42144 study, including tumor type, KRAS G12C mutation detectability in plasma at baseline, baseline SLD, sites of metastasis, lines of therapy, best response, confirmed best response, PFS, ctDNA tumor fraction and KRAS G12C VAF at baseline/C1D15/C3D1.

  Dataset EGAD50000000454

• GeneScreen, a Population Based, Targeted Genomic Screening Study

  The GeneScreen research study was based at the University of North Carolina (UNC) at Chapel Hill. It brought together researchers from different disciplines, including genetics, clinical medicine, bioethics, sociology, anthropology, psychology, and public health, to study the best ways to offer targeted genetic screening to the general adult population. DNA samples were collected from people who joined GeneScreen to look at a targeted panel of 17 genes. It tested for genetic differences (called mutations) that can cause one of 11 rare, but preventable or treatable conditions, including certain types of cancer and heart disease. Each condition has specific medical advice people can follow with their doctors to prevent or treat a serious health problem. The GeneScreen study was approved by the UNC Institutional Review Board and by the Kaiser Permanente Center for Health Research Institutional Review Board. GeneScreen is funded by the National Human Genome Research Institute of the National Institutes of Health.

  Study phs001817

• Study on the proliferation history of colorectal adenomas

  Mismatch repair (MMR) deficient colorectal adenomas are composed of transformed cells that descend from a common founder and progressively accumulate genomic alterations but their proliferation history is still largely unknown. Here we rebuilt the proliferation history of four MMR deficient colorectal adenomas from male individuals by deep sequencing the X chromosome and mapping the somatic mutations that were progressively acquired during tumor growth. We developed a novel method to call high and low frequency mutations, to cluster them according to their frequencies and rebuild the proliferation trees directly from these mutation clusters using a recursive algorithm. The trees of all four lesions were formed of a dominant subclone that coexisted with other genetically heterogeneous subpopulations of cells. Despite this similar hierarchical organization, however, the growth dynamics varied among and within tumors, likely depending on a combination of tumor-specific genetic and environmental factors. Our study provides insights into the biological properties of individual MMR deficient colorectal adenomas that may influence their growth and also the response to therapy. Extended to other solid tumors, our approach could inform on the mechanisms of cancer progression, thus providing insight into the best choice of cancer treatment methods.

  Study EGAS00001000883

• Cancer immune control needs senescence induction by Stat1 dependent cell cycle regulator pathways in tumours

  Immune checkpoint bloackade (ICB)-based or natural cancer immune responses largely eliminate tumours. Yet, they require additional mechanisms to arrest those cancer cells that are not rejected. Cytokine-induced senescence (CIS) can stably arrest cancer cells, suggesting that interferon-dependent induction of senescence-inducing cell cycle regulators is needed to control those cancer cells that escape from killing. Here we report in two different cancers sensitive to T cell-mediated rejection, we show that deletion of the senescence-inducing cell cycle regulators p16Ink4a/p19Arf (Cdkn2a) or p21Cip1 (Cdkn1a) in the tumour cells abrogated both, the natural and the ICB-induced cancer immune control. Also in humans, melanoma metastases that progressed rapidly during ICB have losses of senescence-inducing genes and amplifications of senescence inhibitors. Metastatic cells also resist CIS. Such genetic and functional alterations are infrequent in metastatic melanomas regressing during ICB. Thus, activation of tumour-intrinsic, senescence-inducing cell cycle regulators is required to stably arrest those cancer cells that escape from eradication.

  Study EGAS00001004151

• Sequencing files for "Transcriptional Mechanisms of Resistance to Anti-PD-1 Therapy"

  Files from whole exome sequencing of 26 tumors and two matched normals from one melanoma patient. The 26 tumors include the untreated primary, cutaneous metastases and distant metastases to internal organs.

  Dataset EGAD00001003200

• Epilepsy related sudden death (2019-08-21)

  These samples include exome sequences of samples from patients who suffered Sudden Unexplained Death in Epilepsy. They all are of European descent. . This dataset contains all the data available for this study on 2019-08-21.

  Dataset EGAD00001005276

• Childhood Cancer Data Initiative (CCDI): Enhancement of Data Sharing in Pediatric, Adolescent and Young Adult Cancers

  NCI's Childhood Cancer Data Initiative (CCDI) is building a community centered around childhood cancer care and research data. Through enhanced data sharing, we can improve our understanding of cancer biology to improve preventive measures, treatment, quality of life, and survivorship, as well as ensure that researchers learn from every child with cancer. While childhood cancers represent the leading cause of death in children over the age of 1, they are collectively rare, comprising approximately 1%‒3% of cancers diagnosed annually in the United States. Information on diagnosis, treatment, and outcomes is often stored at the hospital or institution where a child is treated, making it difficult to answer scientific questions about childhood cancer. Sharing clinical care and research data generated by children's hospitals, clinics, or networks broadly with the community can help us learn faster and, on a scale much larger than any single institution caring for children can learn on its own. To exploit the rapid advances in high-throughput DNA sequencing technologies and realize the goals of precision cancer medicine, the UMICH Cancer Center established the Michigan Oncology Sequencing Center (MI-ONCOSEQ). This UMICH Cancer Center provisions genomic data derived from the Michigan Oncology Sequencing Center (MI-ONCOSEQ) clinical sequencing assay for patients that fall within the inclusion criteria of the CCDI data sharing initiative. An "integrative sequencing approach" carried out in a CLIA-certified laboratory is utilized to provide a comprehensive landscape of the genetic alterations in individual tumor specimens for the purpose of identifying informative and/or actionable mutations. Using a number of computational pipelines that we have developed in-house or have adapted from the public domain, candidate molecular aberrations are nominated and then analyzed by scientists for clinical significance and/or relevance. This approach enables the detection of point mutations, insertions/deletions, gene fusions and rearrangements, amplifications/deletions, and outlier expressed genes. Furthermore, we can identify certain germline alterations that may also be relevant.

  Study phs002431

• Center for Common Disease Genomics [CCDG] - Autoimmune: Inflammatory Bowel Disease (IBD) Exomes and Genomes

  The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of: undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases; understanding how best to design rare variant studies for common disease; developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. The overarching aim of the Inflammatory Bowel Disease (IBD) program is to define the full allelic spectrum of protein-altering variation in genes associated to IBD, and assess their role in both Crohn's Disease (CD) and Ulcerative Colitis (UC) risk. The whole genome sequencing data generated here is comprised of samples from US-based diverse populations including African American, Puerto-Rican, Caribean and Cuban origins.

  Study phs001642