516 results for "cancer rna-seq"

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• GBM cancer stem cell lines, RNA-seq and WGS data

  This dataset contains 3 GBM stem cell samples profiled by RNA-seq. Two of those samples have been profiled with WGS as well (with matched blood WGS data available)

  Dataset EGAD00001005077

• Oesophageal adenocarcinoma whole exome and RNA-seq raw sequencing data

  Study EGAS00001005957

• RNA-seq data from the tumor samples of head and neck cancer patients

  This dataset contains paired-end RNA sequencing data (2x50 bp) from the primary tumors and the recurrences/metastases of 6 head and neck cancer patients.

  Dataset EGAD00001011279

• Whole genome, RNA-seq and single-cell Multiome profile of multiple myeloma

  Study EGAS00001007014

• RNAseq data to study PRPF6 regulated splice forms in colon cancer cell lines

  Alternative splicing plays critical roles in differentiation, development, and cancer (Pettigrew et al., 2008; Chen and Manley, 2009). The recent identification of specific spliceosome inhibitors has generated interest in the therapeutic potential of targeting this cellular process (van Alphen et al., 2009). Using an integrated genomic approach, we have identified PRPF6, an RNA binding component of the pre-mRNA spliceosome, as an essential driver of oncogenesis in colon cancer. Importantly, PRPF6 is both amplified and overexpressed in colon cancer, and only colon cancer cells with high PRPF6 levels are sensitive to its loss. Our data clearly point to an important role for PRPF6 in colon cancer growth and suggest that a better understanding of its role in alternative splicing in colon cancer is warranted. To determine the specific alternative splice forms that PRPF6 regulates in colon cancer, we plan three experiments: 1. The first involves knocking down expression of PRPF6 in two different cancer cell lines with 3 different siRNAs, and then completing RNA-seq to determine the gene expression changes that occur relative to a non-targeting control siRNA. Because of the role for PRPF6 in pre-mRNA splicing, we especially want to quantify the changes in splice-specific forms of all genes genome-wide to identify genes whose splicing is altered upon PRPF6 knockdown. 2. The second involves immunoprecipitating PRPF6 from two different cancer cell lines and isolating any RNA that is bound to PRPF6, since PRPF6 is an RNA-binding protein. We then want to carry out RNA-seq to identify which RNA molecules co-immunoprecipitated with PRPF6. This will help us determine possible functions for PRPF6 in regulating colon cancer growth. 3. The third involves overexpressing PRPF6 in cell lines and then carrying out RNA-seq to identify any changes in splice-specific gene expression. This will allow us to determine whether increased PRPF6 expression is sufficient to drive alternative splicing changes.

  Dataset EGAD00001000817

• Cancer Alliance RNA-Seq PolyA

  PolyA selection transcriptome profiling by high-throughput for individualized cancer interpretation

  Dataset EGAD00001006234

• RNA-seq data from the tumor samples of a head and neck cancer patient

  This dataset contains paired-end RNA sequencing data (2x50 bp) from the three synchronous primary tumors and the recurrence of a head and neck cancer patient.

  Dataset EGAD00001006654

• RNA-seq of Breast Cancer Cells in Bone-Mimetic Matrices

  Bulk RNA sequencing dataset of four breast cancer cell lines (MDA-MB-231, SCP2, MCF7 and BT-4747) cultured in collagen or in collagen-hydroxyapatite (bone mimetic) matrices to model microenvironment-driven gene expression changes.

  Study EGAS50000001966

• RNA-seq and WGS data of MB-0152

  Identification of fusion transcripts by RNA-sequencing and Whole genome sequencing of a breast cancer patient sample (METABRIC ID MB-0152)

  Dataset EGAD00001003342

• January 2016 update of RNA-Seq data for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  January 2016 update of RNA-Seq data (bams, fastqs) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001885

• Data access policy for PDTX Breast Cancer RNA-seq data from Ros et al (2020)

  Dac EGAC00001001620

• Ex vivo modeling of precision immuno-oncology responses in lung cancer

  Single-cell RNA-sequencing (scRNA-seq) data from paired lung cancer organoids and immune cells. The experiment was performed using the Single Cell 5' solution of 10X Genomics. The dataset includes 15 samples from 4 multiplexed experiments. The multiplexing was performed using the Feature Barcoding technology of 10X Genomics.

  Study EGAS50000000593

• Single cell RNA-sequencing of tissues from NSCLC patients treated with chemoimmunotherapy

  The goal of this study is to characterize immune cell populations by single cell RNA-sequencing (scRNA-seq) in tumor and uninvolved normal tissues from non-small cell lung cancer (NSCLC) patients with resectable non-small cell lung cancer and who received neoadjuvant chemoimmunotherapy. scRNA-seq was performed on seven pairs of tumor and normal tissues as well as one lymph node (LN) sample. Data set includes pair-end fastq files for single cell RNA sequencing of 7 neo-immuno patients. (Total 15 samples and 50 runs).

  Dataset EGAD00001009778

• scRNA-seq profile of three ATC and three lethal PTC samples

  To elucidate molecular and immunological characteristics distinguishing anaplastic thyroid cancer (ATC) from aggressive papillary thyroid cancer (PTC), we performed single-cell RNA sequencing on three ATC and three lethal PTC samples.

  Study JGAS000942

• Targeted RNA-Seq

  This dataset contains targeted RNA-Seq generated with the Illumina RNA Pan-Cancer panel. It comprises 2200 cancers from children and adults. The cancers represent a wide range of CNS, solid and haematopoietic tumours. Samples are from pathology specimens including FFPE, fresh frozen, bone marrow aspirate and peripheral blood. Samples were tested in a clinical diagnostic lab to identify relevant SNVs, indels and gene fusions.

  Dataset EGAD50000000980

• Integrative Molecular Characterization of Breast Cancer

  Version 1: We have performed integrative analyses of breast cancer tumors, including whole exome sequencing (WES) of tumor and normal pairs, whole transcriptome sequencing, and single-cell RNA sequencing (scRNA-seq) or single-nucleus RNA sequencing (snRNA-seq), to determine molecular correlates of response to novel and immune therapies. We have focused on dissecting the role of anticancer immunity in response to these therapies and understanding biological mechanisms underlying therapeutic resistance. The goal of this work is to advance a precision medicine approach to breast cancer treatment by identifying molecular biomarkers to improve therapy selection and novel therapeutic targets to overcome resistance. Version 2: We performed bulk whole exome sequencing (WES) of fresh frozen tissue from primary hormone receptor-positive breast cancer. Additionally, where available, we performed bulk whole transcriptome sequencing for the same individuals (tumor only). Additionally, we performed single cell sequencing on fresh frozen tissue from primary hormone receptor-positive breast cancer.

  Study phs002419

• PDiamond Korean Lung Cancer Data

  WES and RNA-seq data of PDiamond Korean lung cancer data

  Dataset EGAD50000000844

• Breast Cancer bulk RNA-Seq Dataset

  Bulk RNA-Sequencing of 18 primary breast cancers from Wu et al. (2021) study.

  Dataset EGAD50000000649

• RNA-SEQ data from 47 CAF (Cancer Associated Fibroblast) samples sorted from fresh breast cancer

  Dataset EGAD00001003808

• Whole-genome and single-cell sequencing of lethal metastatic castration resistant prostate cancer

  Contains a total of 9 patients with whole-genome sequencing of 30 tumours or germline samples, 10X single-cell multiome RNA-seq + ATAC-seq of 24 tumours, 10X 5' single-cell RNA-seq of 10 tumours, and snPATHO-seq of 2 primary tumours. All single-cell experiments have matched whole-genome sequencing. When matched tumour (and germline) whole-genome sequencing is missing, it can be found under EGAS00001006598.

  Dataset EGAD50000001869

• Analysis of chromosomal background of cancerous mutations using a long-read sequencer

  In our previous study detecting cancerous complex SVs, we performed whole-genome sequencing of lung cancer clinical samples using PromethION. In this study, its depth and quality was substantially enriched and we conducted the phasing analysis in human lung cancer genomes. In addition, long read and short read RNA-seq was performed for transcriptome analysis.

  Study JGAS000349

• Very Low Tumor Mutation Burden Identifies Inflamed Recurrent Glioblastomas Responsive to Cancer Immunotherapy

  A subset of available tumors (with matched blood) from patients enrolled in a phase I clinical trial testing a recombinant poliovirus, published by Desjardins et al. NEJM 2018 (PMID:29943666), were analyzed by whole exome sequencing and RNA-seq. It was discovered that low tumor mutation burden correlated with survival outcome, and also discovered that low tumor mutation burden correlated with higher inflammatory gene signatures by RNA-seq.

  Study phs002270

• Longitudinal single-cell RNA-seq data of metastatic ovarian cancer

  Study EGAS00001005010

• Combined PDCD1, BRAF and MAP2K7 Inhibition in BRAFV600E Colorectal Cancer: A Phase 2 Trial

  In this study, we evaluated the clinical efficacy of combined PDCD1, BRAF, and MAP2K7 inhibition in metastatic BRAFV600E Colorectal Cancer (CRC) patients (NCT03668431). We performed bulk whole exome sequencing (WXS) and bulk RNA sequencing (RNA-Seq) in 35 pre-treatment tumor biopsies and matching germline for tumor mutational burden (TMB), BM1/BM2 transcriptional subtypes, and consensus molecular subtypes (CMS) analysis, which were previously reported to affect prognosis and response to therapy (PMIDs: 32047001, 27354468, and 26457756). Analysis of bulk data showed that TMB, BM1/BM2 subtypes, and CMS did not correlate with clinical response in this study. Analysis of single cell RNA sequencing (scRNA-Seq) data of tumor epithelial cells from 23 paired day 0 and day 15 tumor biopsies revealed greater induction of tumor cell-intrinsic immune programs and more complete MAPK inhibition in patients with better clinical outcome.

  Study phs003178

• Phenotypic Signatures of Circulating Neoantigen-Reactive CD8+ T Cells in Patients with Metastatic Cancers

  Following enrichment of neoantigen-reactive T cells using pHLA tetramers or cell-surface markers, we performed single-cell sequencing (RNA-seq and TCR-seq) of circulating CD8+ T cells from metastatic cancer patient samples (Melanoma, Colorectal, and Breast cancer). In samples from previously studied patients, we identified cells bearing neoantigen-reactive T cell receptors and were able to study their phenotypic program. By studying the circulating neoantigen-reactive T cell program, a gene-signature was derived to identify neoantigen-reactive T cells from blood samples prospectively.

  Study phs003064