7413 results for "canc*"

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• Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  Dataset EGAD00001006237

• RNA-SEQ for the Caldas Lab breast cancer PDTX collection

  RNA-SEQ for the Caldas Lab breast cancer PDTX collection. This includes both single and paired end runs

  Dataset EGAD00001006307

• whole exome sequencing (WES) data of the HIPO head and neck cancer (HNC, n=83)

  Paired whole exome sequencing data of the HIPO head and neck cancer (HNC) (n=83), using Agilent SureSelect V4+UTRs and V6+UTRs with the sequencing platforms HiSeq2000 and HiSeq2500. The reads were aligned to hg19. This is part of project H019.

  Dataset EGAD00001006336

• Whole Exome Sequencing of High grade T1 non-muscle invasive bladder cancer

  The dataset consists of a multisample VCF (version 4.1) and the corresponding annotated MAF file, containing the somatic point mutations found from exome sequencing across the high-grade T1 bladder cancer cohort (HGT1, n=61 samples). The VCF file is in accordance with the HTS format specifications (https://samtools.github.io/hts-specs/). The dataset comprises also a CSV file with clinical data.

  Dataset EGAD00001006346

• Sequencing data for oesophageal and related samples - Katz-Summercorn, Jammula et al (WGS)

  Data supporting: “Multi-omic cross-sectional cohort study of pre-malignant Barrett’s esophagus reveals structural variation and retrotransposon activity occur early in cancer evolution.” Katz-Summercorn, Jammula et al. WGS (BAM files)

  Dataset EGAD00001006349

• Sequencing data for oesophageal and related samples - Katz-Summercorn, Jammula et al (RNA)

  Data supporting: “Multi-omic cross-sectional cohort study of pre-malignant Barrett’s esophagus reveals structural variation and retrotransposon activity occur early in cancer evolution.” Katz-Summercorn, Jammula et al. RNAseq (BAM files)

  Dataset EGAD00001006353

• RNA-seq of Bone Metastasis from breast and prostate cancers

  RNA-seq of Bone Metastasis from breast and prostate cancer (4 breast and 5 prostate samples). Dataset contains BAM files from RNA-seq performed using Illumina HiSeq 2500.

  Dataset EGAD00001006356

• Gene expression profiles of single disseminated breast cancer cells

  A set of 56 EpCAM-positive cells derived from bone marrow aspirates of breast cancer patients or patients without a cancererous disease (30 cells from 21 M0-stage and 11 cells from five M1-stage breast cancer patients, 15 cells from seven non-cancer patients serving as controls). EpCAM-positive cells from breast cancer patients were considered disseminated tumor cells as they harbored copy number alterations and showed high expression of the epithelial marker EpCAM and the mammary luminal progenitor marker KIT in comparison to EpCAM-positive bone marrow cells from non-cancer patients. Paired-end RNA-Sequencing of the samples was performed on Illumina NovaSeq6000, raw data are provided in the Fastq format.

  Dataset EGAD00001006359

• Data for the study "Plasma ctDNA is a tumor tissue surrogate and enables clinical-genomic stratification of metastatic bladder cancer"

  Sequencing data from patients with bladder cancer. BAM files from targeted DNA sequencing of bladder cancer driver genes in 344 circulating tumor DNA and tumor tissue samples. BAM files from whole exome sequencing of 49 circulating tumor DNA and tumor tissue samples. Paired FASTQ files from RNA sequencing of 86 tumor tissue samples.

  Dataset EGAD00001006362

• 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