12086 results for "cancer rna-seq"

in 13.41 milliseconds.

• National Cancer Institute (NCI) Head and Neck Cancer Study

  Head and neck cancers have well-documented associations with tobacco and alcohol exposure, but the disease develops in only a small fraction of users, which implies an important role for genetic susceptibility. Therefore, head and neck cancers are an excellent model for studying genetic susceptibility to environmental carcinogens. The primary goal of this study is to perform a comprehensive two-stage, high-density, genome-wide single-nucleotide polymorphism (SNP) analysis of head and neck cancer cases and corresponding frequency matched controls to identify novel genetic risk factors for head and neck cancer. In the study, we genotyped 2242 head and neck cancer cases and 1198 controls using Illumina HumanOmniExpress-12v1 BeadChip.

  Study phs001173

• Proteogenomic discovery of a novel class of cancer antigens by HLA ligandome analysis of colon cancer tissues

  CD8+ T cells recognize peptides displayed by HLA class I molecules on cell surfaces, monitoring pathological conditions such as cancer. Recent advances in proteogenomic analysis of HLA ligandomes have demonstrated that cells present a subset of cryptic peptides derived from non-coding regions of the genome; however, the roles of cryptic HLA ligands in tumor immunity remain unknown. In the present study, we comprehensively and quantitatively investigated the HLA class I ligandome of a set of human colorectal cancer (CRC) and matched normal tissues, showing that cryptic translation products account for a small fraction of the HLA class I ligandome and serve as antigens for patient T cell surveillance against colon cancer.

  Study JGAS000280

• 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

• APOBEC3 mutagenesis drives therapy resistance in breast cancer

  Acquired genetic alterations commonly drive resistance to endocrine and targeted therapies in metastatic breast cancer, however the underlying processes engendering these diverse alterations are largely uncharacterized. To identify the mutational processes operant in breast cancer and their impact on clinical outcomes, we utilized a well-annotated cohort of 3,880 patient samples with paired tumor-normal sequencing data. The mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were highly prevalent and enriched in post-treatment compared to treatment-naïve hormone receptor-positive (HR+) cancers. APOBEC3 mutational signatures were independently associated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor combination therapy in patients with HR+ metastatic breast cancer. Whole genome sequencing (WGS) of breast cancer models and selected paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted resistance to both endocrine and targeted therapies through characteristic alterations such as RB1 loss-of-function mutations. Evidence of APOBEC3 activity in pre-treatment samples illustrated a pervasive role for this mutational process in breast cancer evolution. The study reveals APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlights its potential as a biomarker and target for overcoming resistance.

  Study EGAS50000000875

• Sequencing data for oesophageal and related samples - Normals release 1 (RNA)

  Dataset EGAD00001002258

• Dataset for RNA sequencing of Glioblastoma samples

  This dataset contains 10x scRNA sequencing of glioblastoma samples. Sequencing was performed on a Illumina HiSeq 4000. The sequencing was always paired.

  Dataset EGAD50000000081

• Single-cell Full Transcriptome RNA sequencing

  Single cell full transcriptome sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD50000000201

• RNA Sequencing of Control and Myotonic Dystrophy Type 1 Cells During Myogenic Differentiation

  RNAseq data of 30 muscle cell samples (proliferating myoblasts to differentiating myotubes) of immortalized control cells, and myotonic dystrophy type 1 (DM1) patient-derived cells and their edited versions.

  Dac EGAC50000000592

• Alveolar Rhabdomyosarcoma sequencing data

  This dataset comprises DNA sequencing for tumor and matched normal from an Alveolar Rhabdomyosarcoma patient. It also include RNA sequencing data from the tumor sample.

  Dataset EGAD00001006622

• Single cell targeted RNA sequencing

  Single cell hybrid-capture targeted sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006327