9296 results for "cancer rna-seq"

in 51.23 milliseconds.

• Spatial transcriptomics of 1 untreated prostate cancer.

  Two sections of cryopreserved prostate cancer tissue from one untreated prostate cancer patient were profiled for spatial transcriptomics using the Visium Spatial library preparation protocol from 10x Genomics. The GRCh38 aligned sequencing reads from the two prostate cancer tissue sections are provided as BAM files.

  Dataset EGAD00001007921

• Germline genome sequencing samples from the Hereditary Cancer Syndromes (ICCon) Cancer Flagship

  A prospective study of individuals with suspicion of a hereditary cancer syndrome for whom previous clinical targeted genetic testing was either not informative or was not available. To identify pathogenic disease-causing variants explaining participant presentation, germline whole-genome sequencing and a comprehensive cancer virtual gene panel analysis were undertaken.

  Dataset EGAD00001011260

• Clinical data of breast cancer patients from EuCanImage - Use case 7

  This study is part of EuCanImage project. It contains the standardized clinical information following FHIR model. The data was collected together with MRI of patients diagnosed with breast cancer

  Study EGAS50000000191

• Accurate detection of tumor-specific fusion genes reveals strongly immunogenic personal neo-antigens

  Fusion genes arising from cancer-associated somatic mutations are a potential rich source for highly immunogenic neo-antigens. However, their exploitation as targets for personalized cancer immunotherapy is currently limited by the lack of computational tools allowing transcriptome-wide identification of unique fusion genes in an accurate and sensitive manner. Here, we present EasyFuse, a computational pipeline, to detect individual and cancer-specific fusion genes in next-generation-sequencing transcriptome data obtained from human cancer samples. Using machine learning, EasyFuse predicts personal fusion genes with high precision and sensitivity and outperforms previously described approaches as qualified by an unprecedented ground-truth dataset of >1500 verification experiments in relevant patient samples. By testing immunogenicity with autologous blood lymphocytes from cancer patients we detected pre-established CD4+ and CD8+ T cell responses for 10 of 21 (48%), and for 1 of 30 (3%) of identified fusion genes, respectively. In conclusion, we demonstrate accurate detection of cancer-specific fusion genes. The high frequency of T cell responses detected in cancer patients support the relevance of private fusion genes as neo-antigens for personalized immunotherapies, especially for tumors with low point mutation burdens.

  Study EGAS00001004877

• Whole Exome sequencing of colorectal cancer patients (SG-BULK)

  DNA-seq libraries were captured to exome regions using xGen Exome Research Panel v1.0 (IDT), and libraries were prepared using the KAPA Hyper prep kit. DNA libraries were sequenced to a target depth of ×200 for tumor sample, ×100 for normal samples on the Illumina HiSeq platform.

  Dataset EGAD00001008543

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__clear_cell_renal_cell_carcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001002608

• CRUK-ICGC Prostate Cancer Group Study

  Prostate cancer somatic genomic sequencing data generated from 2011 onwards under auspices of the International Cancer Genome Consortium Prostate Cancer UK consortium (CRUK-ICGC Prostate Group), co-led by Colin Cooper and Ros Eeles, with other Principal Investigators (Brewer, Neal, Bova, McDermott, Wedge, Lynch, Massie, and Foster) and others as listed in study publications. Funded by Cancer Research UK and other funders as listed in study publications. Contents and publications related to each dataset are described with each dataset (EGAD) entry. Our study was funded with the ambition of collecting Whole Genome DNA sequence data from 250 prostate cancers, with matching transcriptome and methylome data. The original aims of the project were: 1.To understand the significance of multifocal prostate cancer. 2.To understand the clinical heterogeneity of prostate cancer to devise markers for predicting outcome and for drug targeting. 3.To understand the molecular basis of development and spread of castration-resistant and metastatic disease 4.To understand the aetiology of prostate cancer particularly the large variation in incidences that occur in different populations and ethnic groups. Please see https://doi.org/10.5281/zenodo.4022439 for links between sample IDs reported in literature and EGA IDs.

  Study EGAS00001000262

• Genomics_of_Colorectal_Cancer_Metastases___Massively_Parallel_Sequencing_of_Matched_Primary_and_Metastatic_tumours_to_Identify_a_Metastatic_Signature_of_Somatic_Mutations__MOSAIC_

  Exome pulldown and SNP6 Affymetrix array of matched primary and metastatic colorectal cancer samples from 20 patients

  Study EGAS00001000103

• Pulldown_cytosine_deaminases

  We are looking at the causal factors behind hyper-mutator phenotypes found in previous Breast Cancer sequencing studies.

  Study EGAS00001000233

• Molecular Profiling of Gallbladder Cancer (MPOG)

  The purpose of this study is to investigate the underlying genetic factors involved in gallbladder cancer.

  Study phs001404