11750 results for "cancer rna-seq"

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• 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

• DESIGN II HNSCC RNA-Seq

  RNA-Seq data of 28 HPV-negative HNSCC specimens from patients treated at the Netherlands Cancer Institute (Amsterdam), VU Medical Centre (Amsterdam) or MAASTRO Clinic (Maastricht) in The Netherlands. HNSCC biopsy samples were obtained prior to treatment (chemo-radiotherapy) for the prospective study within the DESIGN project and used for polyA mRNA sequencing.

  Dataset EGAD00001005722

• 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

• Whole exome and transcriptome sequencing of gastric cancer patients

  Whole exome and RNA-seq of matched normal gastric mucosa (n=34) and gastric cancer tissues (n=34) from gastric cancer patients (n=34)

  Dataset EGAD00001004164

• Whole Exome Sequencing and RNA-Seq to Characterize the Somatic Breast Cancer Landscape Among Latinas in California

  Somatic mutational profiles are increasingly being used to guide treatment. However, there is a dearth of data from non-European populations. To address this gap, we conducted paired tumor/normal whole exome paired-end sequencing and tumor RNA-Seq on 146 breast tumors from 140 Hispanic/Latina (H/L) women with breast cancer. We characterized somatic mutations, copy number alterations, tumor subtypes [Prediction Analysis of Microarray 50 (PAM50)], Catalogue Of Somatic Mutations In Cancer (COSMIC) mutation signatures and expression profiles, and compared them to breast tumors from non-Hispanic White (White) women in The Cancer Genome Atlas (TCGA). Using MutSigCV, we found that the most commonly mutated genes, including TP53, RUNX1, PTEN, PIK3CA, MAP3K1, GATA3, CDH1 and CBFB, were similar to those in breast tumors from non-Hispanic white women. Novel findings were that outliers of BLTP2 (aka KIAA0100) over-expression and COSMIC mutational signature 16 were more common in tumors from H/L women than White women. We also identified that the known germline APOBEC3A/B deletion variant was significantly more common in H/L women and was associated with indigenous American ancestry. Data available through dbGaP will be whole-exome sequencing (WES) and RNA sequencing (RNA-Seq) data, as well as phenotypic data, including estrogen receptor, progesterone receptor, and HER2 receptor status, tumor histology, stage, and grade, and age at diagnosis.

  Study phs003218

• Molecular and cellular composition changes after neoadjuvant letrozole and palbociclib in early luminal breast cancer

  The NeoPAL trial compared neoadjuvant letrozole-palbociclib (LP) with chemotherapy (CT) in 103 patients with high-risk early luminal breast cancer. Deconvolution of bulk RNA-seq data revealed that myoepithelial cells, normal-like fibroblasts, FOLR2+ macrophages and SELL+ CD4+ T lymphocytes accumulated after treatment (p: 0.046 to 7.2e-07). All changes were similar between the LP and CT arms.

  Study EGAS50000001021

• Prospective Procurement of Solid Tumor Tissue to Identify Novel Therapeutic Targets

  Recent advances and insights into the molecular pathogenesis of cancer have led to the development of novel molecular and biologic targeted therapies for the treatment of advanced cancer patients. A critical challenge in extending these studies involves the identification and validation of new therapeutic targets for future cancer therapies. In this study, we performed whole exome and RNA-Seq analysis metastases to determine the nature and frequency of somatic mutations.

  Study phs001003

• RNA-seq data from 70 non-small cell lung cancer (NSCLC)

  Dataset EGAD00001006145

• Bulk and Single-Nuclei RNA-seq with ATAC-seq of Breast Tumors Pre- and Post-Palbo ciclib/Endocrine Therapy

  This dataset comprises bulk and single-nuclei multiomic profiles from patients with ER+/HER2- early breast cancer enrolled in the NeoRHEA phase 2 trial. The bulk RNA-seq component includes 78 pre-treatment and 49 post-treatment tumor samples from 97 patients. The single-nuclei component includes matched pre- and post-treatment samples from 37 patients, totaling 63 samples analyzed by simultaneous snRNA-seq and snATAC-seq. Combined, the data contains bulk transcriptional profiles and single-nuclei gene expression/chromatin accessibility matrices for over 226,000 high-quality nuclei, encompassing tumor, immune, and stromal cells. Technologies used include Illumina NovaSeq 6000 for sequencing and the 10x Genomics Chromium platform (Multiome kit for single-nuclei, standard RNA library prep for bulk).

  Dataset EGAD50000002038