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• Detection of cancers three years prior to diagnosis using plasma cell-free DNA

  A major goal of early cancer detection is to identify subclinical disease when the tumor burden is low, so that treatments are more effective. But how early can cancers be detected prior to clinical signs or symptoms? This question can be answered only through the evaluation of participants whose clinical course has not been altered by the study itself. We here describe such an evaluation, performed on prospectively collected plasma samples from the Atherosclerosis Risk in Communities (ARIC) study, including 26 participants diagnosed with cancer and 26 matched controls. At the index time point, eight of these 52 participants scored positively with a multicancer early detection (MCED) blood test. All eight of these participants were diagnosed with cancer within 4 months after blood collection. In six of these 8 participants, we were able to assess an earlier plasma sample collected 3.1 to 3.5 years prior to clinical diagnosis. In four of these six participants, the same mutations detected by the MCED test could be identified, but at 8.6 to 79-fold lower levels. These results demonstrate that it is possible to detect circulating tumor DNA (ctDNA) more than three years prior to clinical diagnosis, and provide benchmark sensitivities required for the success of ctDNA-based tests for this purpose.

  Study EGAS00001008068

• Exome Sequencing of Esophageal Adenocarcinoma

  The incidence of esophageal adenocarcinoma (EAC) has risen 600% over the last 30 years. When coupled to the five-year survival rate of only 15% for this disease, identification of new therapeutic targets for EAC is of great importance. Here, we analyze the mutational spectra identified from the whole genome sequencing of 16 EACs and complete exome sequencing of 149 EAC tumors and matched germline samples. We identify a novel mutation signature marked by high prevalence of A to C transversions at AA*(N) trinucleotides. Notably, the development of EAC is preceded by pathologic intestinal metaplasia of the lower esophagus, Barrett's esophagus, itself a response to injury from gastric-esophageal reflux disease (GERD). Thus, we hypothesize to represent these AA*(N) mutations to a novel signature of GERD-induced mutagenesis. Analysis of the exome data identified 26 genes subject to statistically significant recurrent mutation. Of these 26 genes, only TP53, CDKN2A, SMAD4, and PIK3CA had been previously implicated in EAC. Novel mutations include those targeting chromatin modifying factors and novel candidate contributors to EAC: SPG20, TLR4, ELMO1 and DOCK2. Of these, ELMO1 and DOCK2 are notably direct dimerization partners that act to activate Rac1 to enhance cellular invasiveness, thus generating new hypotheses about the potential for the Rac1 pathway to be a novel target for therapy of EAC. "Reprinted from 'Unraveling the mutational complexity of esophageal adenocarcinoma', with permission from Nature Genetics."

  Study phs000598

• Barrett's and Esophageal Adenocarcinoma Genetic Susceptibility Study (BEAGESS)

  BEAGESS is a genome-wide association study (GWAS) which takes advantage of the extensive data collected by investigators in the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON, http://beacon.tlvnet.net), representing many of the high-quality population-based and other epidemiologic studies of BE and EA in the world. The overall goal of our research is to evaluate the influence of genetic susceptibility on risk of EA and its main precancerous condition, BE. The primary aims of the study are to identify tagSNPs most strongly associated with risk of esophageal adenocarcinoma (EA) and Barrett's esophagus (BE). In the secondary aims we will evaluate the extent to which the most significant associations vary according to key environmental and host factors for these conditions, including gender, obesity and cigarette smoking. These results will guide additional exploratory analyses examining ways in which individual SNP results might be aggregated to shed light in the importance of specific pathways relevant to the etiology of BE and EA, and to identify possible epistatic effects.

  Study phs000869

• Genome-Wide Association Study of Schizophrenia

  The goal of the study is to find susceptibility genes for schizophrenia. Dataset versioning Version 1: European-American (EA) ancestry only Version 2: Version 1 plus African-American (AA) ancestry Consent groups and participant set General research use (GRU): 4591 cases and controls (1217 EA cases, 1442 EA controls, 953 AA cases, 979 AA controls) This consent group includes a subset of schizophrenia cases and all controls (which overlap with Bipolar study controls in Bipolar: GRU dataset). Schizophrenia and related disorders (SARC): 475 cases (187 EA cases, 288 AA cases) This consent group includes a subset of schizophrenia cases.

  Study phs000021

• Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer.

  This dataset consists of shallow whole genome sequencing data and amplicon sequencing data for 26 ovarian cancer patients (21 high-grade serous ovarian cancer, 4 low-grade serous ovarian cancer and 1 clear cell ovarian cancer). The data are provided as single end FASTQ files for the shallow whole genome sequencing data (31 libraries) and paired end FASTQ files for the amplicon sequencing data (98 libraries).

  Dataset EGAD00001008716

• Foregut Microbiome in Development of Esophageal Adenocarcinoma

  The distal esophagus is an important anatomical area where gastric acid reflux can cause reflux esophagitis (RE), Barrett's esophagus (BE) (intestinal metaplasia), and esophageal adenocarcinoma (EA). The incidence of EA has increased 6-fold in the U.S. since the 1970s, parallel to a significant increase in the prevalence of gastroesophageal reflux diseases (GERD). Although specific host factors might predispose one to disease risk, such a rapid increase in incidence must be predominantly environmental. The cause remains unknown. Our hypothesis is that changes in the foregut microbiome are associated with EA and its precursors, RE and BE in the GERD sequence. We will conduct a case control study to characterize the microbiome in every stage of the GERD sequence as well as analyze the trend in changes in the microbiome along disease progression toward EA. Specific Aim 1. To conduct a comprehensive population survey of the foregut microbiome and demonstrate its association with GERD sequence, by a 16S rRNA gene survey. We will analyze samples of the foregut microbiome at three anatomic loci: mouth, distal esophagus, and gastric corpus. Changes of the microbiota in the distal esophagus will be correlated with the phenotypes. Spatial relationship between the esophageal microbiota and upstream (mouth) and downstream (stomach) foregut microbiotas as well as temporal stability of the microbiome-disease association will also be examined. Specific Aim 2. To define distal esophageal metagenome and demonstrate its association with GERD sequence, by shotgun metagenomic analysis. We will first classify samples of the metagenome into metagenotypes by between-sample k-mer distance and correlate the metagenotypes with the four phenotypes. Subsequent detailed analyses will include pathway-disease and gene-disease associations. DNA viruses and fungi, if identified, also will be correlated with the phenotypes. A significant association between the foregut microbiome composition and GERD sequence, if demonstrated, will be the first step for eventually testing the causal hypothesis that an abnormal microbiome is required for the development of the sequence of phenotypic changes toward EA. If EA and its precursors represent a microbial ecological disease, treating the cause of GERD might become possible, for example, by normalizing the microbiome through use of antibiotics, probiotics, or prebiotics. Causative therapy for GERD could prevent its progression and reverse the current trend of increasing incidence of EA.

  Study phs000260

• 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

• dataset1

  Contains test sample 1-26

  Dataset EGAD00010002041

• ATAC-seq

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

  Dataset EGAD00001005967

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: kidney (2019-03-26)

  This dataset contains all the data available for this study on 2019-03-26.

  Dataset EGAD00001004867