495 results for "cancer rna-seq"

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• 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 dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

  RNA-seq dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

  Dataset EGAD00001015639

• 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

• 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

• 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

• 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

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

  Dac EGAC00001001620

• 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

• PDiamond Korean Lung Cancer Data

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

  Dataset EGAD50000000844

• 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

• 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

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

  Dataset EGAD00001003808

• 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

• Breast Cancer bulk RNA-Seq Dataset

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

  Dataset EGAD50000000649

• 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

• 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

• Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

  Genetic and non-genetic heterogeneity within cancer cell populations represents a major challenge to anti-cancer therapies. We currently lack robust methods to determine how pre-existing and adaptive features affect cellular responses to therapies. Here, by conducting clonal fitness mapping and transcriptional characterization using expressed barcodes and single-cell RNA-sequencing, we have developed TraCe-seq, a method that captures at clonal resolution the origin, fate, and differential early adaptive transcriptional programs of cells in a complex population in response to distinct treatments. We used TraCe-seq to benchmark how next-generation dual EGFR inhibitors-degraders compare to standard EGFR kinase inhibitors in EGFR-mutant lung cancer cells. To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

  Study EGAS00001005405

• RNA-seq of Liver Cancer

  The present series corresponds to 161 RNA-seq samples from tumors with matched WES or WGS. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003993

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

  Study EGAS00001005010

• Whole-exome sequencing and RNA-seq of paired normal-tumour samples from MMR-proficient early-onset colorectal cancer patients

  This dataset contains fastq files obtained from paired samples of normal colonic mucosa and tumour tissue, collected from 19 patients diagnosed with MMR-proficient colorectal cancer at an age of 50 years or younger. It includes both whole-exome sequencing and RNA-seq data, generated on the Illumina HiSeq 3000 platform. Additionally, the dataset includes phenotypic information from the patients.

  Dataset EGAD50000001844

• RNA-sequençing of 21 inflammatory hepatocellular adenomas

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors.The present series corresponds to 21 RNA-seq of IHCA samples. Aligned bam files correspond to hg38 human reference.

  Study EGAS00001003685

• RNA sequencing for gastric cancer ascites

  Whole transcriptome sequencing (RNA-seq) was performed on 39 PC specimens. Among them, 21 specimens also had WES data.

  Dataset EGAD00001004365

• RNA sequencing of intestinal metaplasia

  We perform bulk RNA-seq of 10 and single cell RNAseq of 2 intestinal metaplasia samples. We also perform stereoseq spatial transcriptomic analysis of 4 gastric cancer samples. The dataset contain cram files from 10 bulk RNAseq samples, and raw fastq files from 2 single cell RNAseq and 4 stereo-seq samples.

  Dataset EGAD50000002010

• Extended longitudinal single-cell RNA-seq data from ovarian cancer across multiple treatment phases

  The dataset contains single-cell RNA-seq data of 73 tumor samples high-grade serous carcinoma (HGSC) patients sequenced with Novaseq. The samples were collected at primary, interval, and relapse treatment phases from multiple tissue sites. The files provided are fastq files.

  Dataset EGAD50000001855