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• Genome-Wide Association Studies in Upper Gastrointestinal Cancers (Asian)

  This project aims to conduct genome-wide association studies (GWAS) in two anatomically different upper gastrointestinal (UGI) cancer sites in two populations with distinctly different disease rates and genetic profiles. One population has very high rates for both esophageal squamous cell carcinomas (ESCCs) and gastric cancers (GCs) and is comprised of Asians (the "Asian UGI GWAS"), while the other population has low rates of ESCC and GC and includes non-Asians from the Americas, Europe, and Australia (the "Non-Asian UGI GWAS"). Study participants for the Asian UGI GWAS reported here (Illumina 660W Quad chip) were drawn from 2 studies, the Shanxi Upper Gastrointestinal Cancer Genetics Project (Shanxi) and the Linxian Nutrition Intervention Trial (NIT), a prospective cohort, and included a total of 1898 ESCCs, 1625 GCs, and 2100 controls. For the 2nd phase (8 TaqMan SNPs), additional subjects from Shanxi and NIT as well as subjects from the Shanghai Men's Health Study (SMHS), the Shanghai Women's Health Study (SWHS), and the Singapore Chinese Health Study (SCHS) were also included (217 ESCCs, 615 GCs, 1202 controls). Altogether 2115 ESCCs, 2240 GCs, and 3302 controls were genotyped in this study.

  Study phs000361

• Understand_Paratyphoid_Disease___host_responses_to_human_challenge_with_S__Paratyphi_A

  This project aims to evaluate the transcriptional response to disease measured in whole blood of participants who developed enteric fever after challenge and, importantly, those who were challenged but stayed well throughout the challenge period. This data will provide unique coverage of the transcriptome and will yield invaluable insight after integration with a wealth of clinical data collected during this trial. 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/

  Study EGAS00001001260

• Ultraviolet radiation drives mutations in a subset of mucosal melanomas

  Although identified as the key environmental driver of common cutaneous melanoma, the role of ultraviolet radiation (UVR)-induced DNA damage in mucosal melanoma is poorly defined. We present the largest cohort of mucosal melanomas of conjunctival origin to be analyzed by whole genome sequencing and show a predominance of UVR-associated single base substitution signature 7 (SBS7) in the majority of the samples. Our data shows mucosal melanomas with SBS7 dominance have similar genomic patterns to cutaneous melanomas and therefore this subset could benefit from treatments currently used for common cutaneous melanoma.

  Study EGAS00001004697

• Genome- and epigenome-driven evolutionary dynamics of tumour-immune coevolution within primary colorectal cancers

  This data includes targeting sequencing of the immunopeptidome from 94 samples, usually individual laser microdissected cancer glands, from 11 cases of colorectal cancer. The data were used to test for evidence of immunoediting (antigen depletion) in colorectal cancers. The full data description is provided in the original manuscript https://pmc.ncbi.nlm.nih.gov/articles/PMC10888923/. The 11 colorectal cancers had been previously multiomic profiled with data described in the parts of this disposition.

  Study EGAS50000001154

• Keratinocyte CRISPR screens (2019-08-14)

  Immortalised HaCaT keratinocytes were transduced with Cas9 and the CRISPR-KO v1.1 genome-wide gRNA library. The gRNA library was prepared from genomic DNA isolated 14 days post library transduction. gRNA representation will be compared to the original CRISPR-KO v1.1 library to reveal genes essential for HaCaT survival and growth. . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005252

• Comprehensive molecular and clinicopathological profiling of glioma

  Various molecular profiles are needed to classify malignant brain tumors, including gliomas, based on the latest classification criteria of the World Health Organization, and their poor prognosis necessitates new therapeutic targets. The Todai OncoPanel 2 RNA Panel (TOP2-RNA) is a custom-target RNA-sequencing (RNA-seq) using the junction capture method to maximize the sensitivity of detecting 455 fusion gene transcripts and analyze the expression profiles of 1,390 genes. This study aimed to classify gliomas and identify their molecular targets using TOP2-RNA. A total of 124 frozen samples of malignant gliomas were subjected to TOP2-RNA for classification based on their molecular profiles and the identification of molecular targets.

  Study JGAS000671

• eMERGE Geisinger eGenomic Medicine (GeM) Abdominal Aortic Aneurysm Project (AAAP)

  A large research cohort of Geisinger Abdominal Aortic Aneurysm (AAA) patients was created by enrolling and consenting patients of the Geisinger Department of Vascular Surgery. Consented patients provide blood, serum and DNA samples for research and authorize use of data in their medical record for research. They also complete a data questionnaire that asks information about family history of AAA and other vascular diseases, as well as information on known or suspected AAA risk factors, including smoking history, body mass index, hypertension, type 2 diabetes, and atherosclerotic disease. The AAA cases are 78% male, with a mean age of 74 years; 39% have undergone surgical or endovascular repair; more than 85% or current or past smokers; approximately 20% of cases report a positive family history of AAA. Geisinger AAA patients undergo regular imaging studies, typically every 6 months, to monitor the progression of aneurysm expansion. This allows the growth rates of their aneurysm to be calculated. DNA samples from a total of 910 AAA patients were used for whole genome genotyping; these results are included in the dbGaP.

  Study phs000387

• scRNAseq of patients with chronic graft-versus-host-disease

  This dataset contains 10 samples from 9 patients with chronic graft-versus-host disease (GVHD). Each sample is analysed with Chromium V(D)J and 5' Gene Expression Platform v1.1 (10X Genomics). The raw data includes fastq files for Gene expression and fastq files for V(D)J Expression. The processed data have been deposited in the ArrayExpress database at EMBL-EBI (www.ebi.ac.uk/arrayexpress) under accession number E-MTAB-13419.

  Dataset EGAD00001012121

• Combined gene expression and digital pathology identifies molecular mediators of T cell exclusion and immune suppression in ovarian cancer

  Close proximity between cytotoxic T lymphocytes and tumour cells is required for effective immunotherapy. However, what determines the spatial distribution of T cells in the tumour microenvironment is not well understood. Coupling digital pathology and transcriptome analysis on a large ovarian tumour cohort, we develop a machine learning approach to molecularly classify and characterize tumour-immune phenotypes. Our study identifies two important hallmarks characterizing T cell excluded tumours: 1) loss of antigen presentation on tumour cells and 2) upregulation of TGFb and activated stroma. Furthermore, we identify TGFb as a key mediator of T cell exclusion. TGFb reduces MHC-I expression in ovarian cancer cells in vitro; TGFb also activates fibroblasts and induced extracellular matrix (ECM) production as a potential physical barrier to hinder T cell infiltration. Our findings indicate that targeting TGFb may represent a promising strategy to overcome T cell exclusion and improve clinical benefits of cancer immunotherapy.

  Study EGAS00001003487

• Mate Pair Sequencing data for Molecular Characterization of ETMRs

  This dataset contains Mate Pair Sequencing data from 15 samples from 13 patients. Mate pair DNA library preparation was carried out using the Illumina MP v.2 reagents and protocol. In brief, fragmentation of genomic DNA was performed using a Hydroshear device to an insert size of 4.5 kb followed by sequencing with Illumina HiSeq 2000 instruments resulting in 30 Fastq files (paired end).

  Dataset EGAD00001006207