9296 results for "cancer rna-seq"

in 18.58 milliseconds.

• ART-NKI II HNSCC RNA-Seq

  RNA-Seq data of 25 HNSCC specimens from patients treated at The Netherlands Cancer Institute, Amsterdam and enrolled in the ARTFORCE trial. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for polyA mRNA sequencing.

  Dataset EGAD00001005721

• The role of the mammalian SWI/SNF chromatin remodeling complex in neuroendocrine prostate cancer

  We sought to determine the effects of SMARCA4 and SMARCA2 depletion in prostate cancer cell lines. We performed siRNA-mediated knock-down of SMARCA4 and SMARCA2 in an androgen-sensitive (LNCaP) cell line and in a castration-resistant prostate cancer (CRPC)-adenocarcinoma cell line (22Rv1) and compared global transcriptional alterations using RNA-seq.

  Study EGAS00001004177

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

  Dataset EGAD00001003808

• RNA-seq data from 121 tumor samples with muscle invasive bladder cancer.

  In this study, a total of 300 patients with MIBC receiving chemotherapy were included; 62 received NAC before cystectomy and 245 received first-line chemotherapy upon detection of locally-advanced (T4b) or metastatic disease. Treatment response, defined as pathological downstaging (< pTa,CIS,N0) after NAC or complete or partial response after first-line treatment (RECIST criteria). RNA-seq was performed using the QuantSeq kit FWD HT kit (Lexogen) using 500 ng input RNA from 121 tumor samples. Data provided here consist of 780 fastq files for RNA-seq.

  Study EGAS00001004505

• 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 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

• Pheno-Seq, linking 3D phenotypes of clonal tumor spheroids to gene expression

  3D-culture systems have advanced cancer modeling by reflecting physiological characteristics of in-vivo tissues, but our understanding of functional intratumor heterogeneity including visual phenotypes and underlying gene expression is still limited. Transcriptional heterogeneity can be dissected by single-cell RNA-sequencing, but these technologies suffer from low RNA-input and fail to directly correlate gene expression with contextual cellular phenotypes. Here we present pheno-seq for integrated high-throughput imaging and transcriptomic profiling of clonal tumor spheroids derived from 3D models of breast and colorectal cancer. Specifically, we identify characteristic expression signatures that are associated with heterogeneous invasive and proliferative behavior including a rare cell subtype. Furthermore, we identify functionally relevant transcriptional regulators missed by single-cell RNA-seq, link visual phenotypes defined by heterogenous expression to inhibitor response and infer single-cell regulatory states by deconvolution. We anticipate that directly linking molecular features with patho-phenotypes of cancer cells will improve the understanding of intratumor heterogeneity and consequently prove to be useful for translational research.

  Study EGAS00001002999

• Whole Exome Sequencing of 60 tumor/normal matched liver Cancers (HCC)

  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 using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 60 whole exome tumor/normal pairs with matched RNA-seq. 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.

  Study EGAS00001003063

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

  Study EGAS00001005010

• GELATO clinical trial RNA-Seq data (primary tumors and local recurrences)

  RNA-Seq data of 10 lobular breast cancer primary tumors and 3 local recurrences obtained from 11 unique patients from GELATO clinical trial. The included raw transcriptome sequencing data in fastq format was generated using Illumina NovaSeq 6000 from archived FFPE material.

  Dataset EGAD00001009835