6048 results for "canc*"

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• Sequencing data for oesophageal samples - Killcoyne, Gregson et al (sWGS)

  Data supporting: "Genomic copy number predicts esophageal cancer years before transformation." Killcoyne, Gregson et al. sWGS data 1000 samples BAM files

  Dataset EGAD00001006033

• Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer

  The dataset for the study Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer includes 207 bam files from hybrid capture targeted error-correction next-generation sequencing (TEC-Seq) from plasma cell-free DNA and matched white blood cell DNA from 30 individuals with non-small cell lung cancer, alongside 46 bam files from whole exome sequencing of tumor and matched normal DNA for 21 individuals with non-small cell lung cancer who received immunotherapy-containing regimens.

  Dataset EGAD00001011991

• Geographic variation of mutagenic exposures in kidney cancer genomes – structural variation vcf files (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – structural variation vcf files ( Mutographs )

  Dataset EGAD00001013726

• Geographic variation of mutagenic exposures in kidney cancer genomes – copy number variants (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – copy number variants (Mutographs)

  Dataset EGAD00001013727

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Kidney (1)

  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.

  Dataset EGAD00001006427

• MutWP1 CRUK Grand Challenge Mutographs of Cancer Colorectal

  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.

  Dataset EGAD00001007510

• MESA colorectal cancer cfDNA EM-seq dataset

  This dataset contains the methylation sequencing data of 60 nonCancer and 70 colorectal cancer cfDNA samples. The methylation library is constructed by using NEBNext Enzymatic-seq Kit.

  Dataset EGAD00001009165

• Targeted and shallow whole genome sequencing identifies therapeutic opportunities in p53abn endometrial cancers

  Shallow whole genome sequencing of 196 formalin-fixed paraffin-embedded p53abn endometrial cancers.

  Dataset EGAD00001015241

• Geographic variation of mutagenic exposures in kidney cancer genomes – filtered vcf files (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – filtered vcf files (Mutographs)

  Dataset EGAD00001012222

• cfMeDIP data for 67 VPC samples

  We analyzed the cell free DNA methylomes using 67 plasma samples from patients with mCRPC prostate cancer in the VPC project. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology.

  Dataset EGAD00001008711