381 results for "cancer rna-seq"

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• Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer RNA-Seq

  The goal of the sequencing study was to determine the neoantigen profile of melanoma patients. We performed whole exome sequening of the tumor and respective patien matched PBMC samples (2x50nt) and RNA-sqeuencing of the tumor samples. The was analyzed for somatic point mutaions, using the RNA-Seq data to determine mutation expression. This study contains the patient matched RNA-Sequencing data.

  Study EGAS00001003307

• Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer

  The goal of the sequencing study was to determine the neoantigen profile of melanoma patients. We performed whole exome sequening of the tumor and respective patien matched PBMC samples (2x50nt) and RNA-sqeuencing of the tumor samples. The was analyzed for somatic point mutaions, using the RNA-Seq data to determine mutation expression. This study contains the exome seq data.

  Study EGAS00001003306

• bladder cancer patient data

  This contains H3K27ac ChIP-seq, RNA-seq and HiC fastq files.

  Dataset EGAD00001007052

• Genomic Profiling of Advanced Pancreatic Cancer to inform therapy - RNA-Seq unmapped reads

  Genomics-Driven Precision Medicine for Advanced Pancreatic Cancer - Early Results from the COMPASS Trial - RNA-Seq unmapped reads

  Dataset EGAD00001003582

• Genomic Profiling of Advanced Pancreatic Cancer to inform therapy - RNA-Seq mapped reads

  Genomics-Driven Precision Medicine for Advanced Pancreatic Cancer - Early Results from the COMPASS Trial - RNA-Seq mapped reads

  Dataset EGAD00001003584

• single-cell RNA-Seq of colorectal cancer patient samples

  Study EGAS00001006665

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

  Study EGAS00001005006

• Prostate cancer datasets RNA Seq

  Total RNA Seq: 15 Samples (2 patients (MF1 and MF3)) (HiSeq) and Poly A RNA Seq: 27 Samples (4 patients Normal and Tumour ) (HiSeq)

  Dataset EGAD00001004468

• QSEA – modelling of genome-wide DNA methylation from sequencing enrichment experiments

  We describe a new method, QSEA, for analyzing methylation enrichment data. We generated a benchmark experiment consisting of MeDIP-seq enrichment data, targeted BS-seq validation data, and RNA-seq data on five pairs of tumor and adjacent normal samples of non-small cell lung cancer patients. Details of the method and its performance on the data have been described in Lienhard et al. (2016).

  Study EGAS00001001822

• Complete DNA/RNA sequencing dataset for Australian ICGC ovarian cancer sequencing project 2014-07-07

  Complete WGS and RNA-Seq dataset for Australian ICGC ovarian cancer sequencing project 2014-07-07, representing 93 donors. Sequencing was performed on Illumina HiSeq. Alignment of the lane-level fastq data was performed with bwa (WGS data) and RSEM (transcriptome data). For this dataset lane-level .bam files have been merged and de-duplicated to create a single bam file for each sample type (tumour/normal) for each donor. This dataset supersedes all previous datasets for this study. 2016-08-08 updated with 14 outstanding RNA-seq samples & corresponding RSEM bams 2016-12-07 updated with 7 outstanding RNA-seq controls and corresponding RSEM bams

  Dataset EGAD00001000877

• Transcriptional and Epigenetic Profiles of Male Breast Cancer at Single-Cell Resolution Nominate Salient Cancer Specific Enhancers

  We performed matched single-cell RNA sequencing (scRNA-seq) and single-cell chromatin accessibility sequencing (scATAC-seq) for two fresh human tumors collected from male breast cancer patients. The integration of these datasets revealed the intratumoral heterogeneity in both transcription and chromatin accessibility for each male breast cancer patient and allowed for comparisons to be made between male and female breast cancer. We hope these data will be a useful reference in the field of breast oncology, specifically for the treatment of males, as few studies have explored male breast cancer genetics.

  Study phs003006

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

  Study EGAS00001005957

• RNA sequencing of multiple tumor biopsies and patient-derived spheroids from five colorectal cancer patients (BAM files)

  Whole transcriptome, strand-specific RNA-seq libraries were prepared from total RNA purified using RNeasy mini kit (Qiagen) using Ribo-Zero technology (Epicentre, an Illumina company) for depletion of rRNA followed by library preparation using ScriptSeq ScriptSeq RNA-Seq Library preparation Kit from Illumina. The paired raw sequence reads were processed using TopHat2 and mapped to the humane reference genome HG19.

  Dataset EGAD00001003820

• 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.

  Dataset EGAD00001006238

• 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

• Cancer Alliance RNA-Seq PolyA

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

  Dataset EGAD00001006234

• 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

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

  Study EGAS00001007014

• 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

• 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

• 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

• 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

• 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

• 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

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

  Dac EGAC00001001620