510 results for "cancer rna-seq"

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• Single-cell RNA sequencing of metastatic colorectal cancer patient-derived xenografts treated with cetuximab

  Single-cell RNA sequencing was performed on a cetuximab-sensitive metastatic colorectal cancer (mCRC) patient-derived xenograft (PDX) model. The objective of this analysis was to assess whether the transcriptional patterns identified in the single-cell RNA-seq data of matched organoids were preserved in the in vivo context.

  Study EGAS50000001459

• UIC HNSCC RNA-Seq and miRNA-Seq Data

  This dataset contains matched RNA-Seq and miRNA-Seq fastq files from 109 match samples of 34 human Papillomavirus-negative Head and Neck cancer patients, including 72 lymph nodes, 29 tumor and 8 normal samples.

  Dataset EGAD00001004489

• Identification of therapeutic target molecules for prostate cancer by using next generation sequencer

  Comprehensive transcriptional characterization of cancer tissues can reveal important molecular signatures associated with the disease progression. Long non-coding RNA (LncRNA) has a diversity of functions such as transcription, epigenetic and gene regulation in cancer cells including prostate cancer cells. Here, we performed directional RNA-sequence (RNA-seq) on clinical samples obtained from prostate cancer (PC) and lethal castration-resistant PC (CRPC) patients to identify novel molecular signatures including protein coding genes and non-coding RNAs induced in CRPC tissues.

  Study JGAS000198

• Bulk RNA-seq of stromal cells from multiple cancer types

  We sorted CD45-CD44+CD90+ stromal cells from multiple tumor types and performed bulk RNA-seq. The data allows to infer CAF programs active across indications.

  Study EGAS00001006497

• single-cell RNA-seq profiling of 2 patient derived colorectal cancer organoids after treatment with a combination of different anticancer drugs

  This dataset consists of single-cell RNA-seq profiling of colorectal cancer organoids derived from two patients. The organoids were profiled both after 4 weeks of treatment and after a drug holiday of two weeks. There are 49 RNA sequence files generated using single cell RNA sequencing technology from 10X genomics.

  Dataset EGAD50000001495

• The transcription factor GABP selectively binds and activates the mutant TERT promoter in cancer

  Dataset contains Exome-seq and RNA-seq from 2 GBM patients, as well as RNA-seq from the derived cultured cells (GNS).

  Dataset EGAD00001001359

• Characterization of Prostate Cancer Organoids

  Using models from the LuCaP series as well as those generated at the National Cancer Institute, we have established organoids for in vitro mechanistic testing, including drug screening and genetic manipulation. The major findings from these continuing studies is the durability of organoids for maintaining complex subpopulation and intratumoral heterogeneity and the parallels between in vitro testing and patient outcomes. Existing data from prior releases includes whole-genome sequencing, whole-exome sequencing, single-cell and bulk RNA-seq, single-cell ATAC-seq, and SNP array. New data in this release is ChIP-seq data from three models and RNA-seq data from one model.

  Study phs001587

• Targeted pancancer 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 haematopoeitic tumours. Samples are from pathology specimens including FFPE, fresh frozen, bone marrow aspirate and peripheral blood.The data is used for tumour driver identification. SNVs, indels and fusion detection.

  Study EGAS50000000700

• Microbiome cross talk, Fusobacterium n. and formate metabolite

  This data comes into 2 pairs of experiments: - RNA-seq Control versus Formate treated colorectal cancer T18 cells - Humix device, RNA-seq of control versus co-culture colorectal cancer T18 cells with Fusobacterium nucleatum

  Dataset EGAD00001008533

• Whole Exome Sequencing and RNA Sequencing of High Grade Serous Ovarian Cancer in Black and White Patients

  In this study, we generated new RNA and whole exome sequencing data from high-grade serous ovarian cancer tumor samples of self-identified Black and White individuals. Our RNA-Seq analysis revealed that, while the prevalence of subtypes varied across racial groups, the cluster-specific gene expression patterns were consistent. Despite these differences in subtype prevalence, the subtype-specific survival rates were similar across racial groups. Additionally, we used the WES-Seq data to characterize mutational signatures and their underlying causes in Black high-grade serous ovarian cancer (HGSC) cases, and compared the prevalence and distribution of these signatures with those in White TCGA cases.

  Study phs003632

• Bulk RNA Sequencing of 112 Bladder Cancer Tumor Samples Using Lexogen QuantSeq 3′ mRNA-Seq

  Bulk RNA sequencing dataset comprising tumor samples from 112 bladder cancer patients. Gene expression profiling was performed using the Lexogen QuantSeq 3′ mRNA-Seq library preparation protocol, which generates strand-specific 3′ end transcript libraries for digital gene expression quantification. The dataset provides transcriptomic profiles for molecular characterization of bladder cancer and supports studies of tumor biology, biomarker discovery, and clinical outcome associations.

  Study EGAS50000002032

• Single-cell RNA sequencing of metastatic colorectal cancer organoids treated with cetuximab

  Single-cell RNA sequencing was performed on metastatic colorectal cancer (mCRC) organoids derived from a cetuximab-sensitive patient-derived xenograft (PDX) model. The objective of this analysis was to investigate, at single-cell resolution, the transcriptional changes previously identified in bulk RNA-seq analyses of PDX models exposed to anti-EGFR therapeutic pressure.

  Study EGAS50000001460

• RNA-seq of Bone Metastasis from breast and prostate cancers

  RNA-seq of Bone Metastasis from breast and prostate cancer (4 breast and 5 prostate samples). Dataset contains BAM files from RNA-seq performed using Illumina HiSeq 2500.

  Dataset EGAD00001006356

• Ewings_Sarcoma_RNA_seq_drug_sensitivity

  Illumina RNA-Seq will be performed on four Ewing’s sarcoma cell lines and two control cell lines. RNA was extracted from all the lines using a basic Trizol extraction protocol.

  Study EGAS00001000419

• RNA-seq of Liver Cancer

  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 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.

  Study EGAS00001002879

• Expressed_fusion_transcripts_in_rare_bone_tumours

  mRNA-Seq on total RNA from primary osteoblastomas and phosphaturic mesenchymal tumours, focussing on fusion transcript expression

  Study EGAS00001000763

• The Transcriptomic Landscape of Oncogenic PI3K Reveals Key Functions in Splicing and Gene Expression Regulation

  This study includes RNA-seq of paired tumor biopsies from PIK3CA-mutated breast cancer patients that underwent treatment with PI3Kα inhibitors.

  Study phs002840

• BarcUVa-Seq (Biology of Colorectal Cancer Risk Enhancers)

  This study was designed to generate a cohort of normal colon mucosal biopsies from the "average risk" population. Its primary aims included the development of an RNA-seq dataset of normal colon mucosal biopsies across three colon regions (ascending, transverse and descending). Further, we aimed to provide plausible prioritization to genetic components of colorectal cancer risk by employing methods such as expression quantitative trait loci analysis. In doing so, we provide a novel reference dataset for the study of colon cancer risk in the healthy colon epithelium. RNA-seq was performed in batches on an Illumina HiSeq 2500 (batch 1-7) or NovaSeq 6000 (batch 8) on a total of 463 samples. Matched genotyping data was generated on the Illumina OncoArray BeadChip. Phasing was carried out using Minimac 3 and imputation was performed using The Haplotype Reference Consortium panel on the Michigan Imputation Server.Genotype and RNA-seq data will be made available in dbGaP.

  Study phs003338

• Single-cell 10x Genomics Multiome RNA-seq data from primary and metastatic colorectal cancers and normal colon tissues

  This dataset contains single-cell 10x Genomics Multiome RNA-seq data from 33 primary colorectal cancer, 11 metastatic colorectal cancer, and 7 matched normal colon tissue samples generated as part of the study "Epigenetic evolution of colorectal cancer and its microenvironment reveals novel vulnerabilities."

  Dataset EGAD50000002945

• RNA-seq of multi-regional CRC samples

  BAM files of RNA sequencing (RNA-seq) experiment on multi-regional colorectal cancer (CRC) samples. 58 samples corresponding to 16 patients were sequenced and there is one BAM file for each sample.

  Dataset EGAD00001006164

• UROMOL 2020 - RNA-seq data validation

  For this project about non-muscle invasive bladder cancer (NMIBC), we analysed total RNA-seq data from 47 patients used for validation. Sequencing of total RNA was performed using KAPA RNA HyperPrep Kit with RiboErase HMR (Roche). RNA input was 100 to 500 ng. The dataset is composed of 94 fastq files.

  Dataset EGAD00001006967

• RNA-Seq of tumors

  RNA-Seq on an Ion Torrent Proton of corresponding tumor material of two metastasized breast cancer patients (Breast7, Breast13).

  Dataset EGAD00001002216

• Expanding the utility of transcriptome analysis for mutation detection in high-risk childhood precision oncology

  In precision oncology, rapid and comprehensive mutation detection is essential for diagnosis, prognosis and treatment. Whole transcriptome sequencing (RNA-seq) offers unique advantages by capturing functional consequences of genomic alterations and has the potential to detect not only oncogenic fusions, but also a broad spectrum of clinically relevant mutations traditionally identified from DNA-based approaches. We evaluated the utility of RNA-seq in a cohort of 477 high-risk paediatric tumours enrolled in the ZERO childhood cancer precision medicine programme with matched WGS data. A combination of reference-guided and reference-free RNA-seq algorithms were used to detect and interpret fusions and intragenic structural variants (SVs), resolving events from complex rearrangements and paralogous loci. RNA-seq detected 95% of gene fusions, including 33 missed by WGS. All intragenic SVs (100%) detected by WGS were also identified by RNA-seq and RNA-seq was essential for identification and/or interpretation of 30% of SVs. Additional functional insight such as aberrant splice-junctions and transcript abundance were critical for resolving pathogenicity. For single nucleotide variants and small insertions/deletions (SNVs/Indels), RNA-seq confirmed 92% and was essential for refining pathogenicity in 22% through allele-specific expression and splice assessment. These findings highlight RNA-seq as a critical complement to WGS, that transforms interpretation by adding functional context, thereby elevating diagnostic confidence and clinical decision-making.

  Study EGAS00001008472

• RNA-Seq data from 34 CAF-S3 subset in human breast and ovarian cancers

  This dataset is related to publications Costa et al. Cancer Cell 2018 and Givel et al. Nat. Commun. 2018 which describe the identification of 4 Cancer Associated Fibroblasts (CAF) in breast and ovarian cancer. This dataset contains transcriptomic profiles obtained by RNA-Seq of 34 CAF-S3 samples from breast and ovarian Tumors.

  Dataset EGAD00001004810

• Cancer RNA-seq consisting of FASTQ paired-end reads from melanoma and lung cancer sample

  Cancer RNA-seq consisting of FASTQ paired-end reads from 6 individuals (4 melanoma, 1 lung cancer). RNASEQ was performed on illumina, Truseq capture kit, 40M-80M clusters. 2 Melanoma datasets contain reads from 1 tumor region and from a tumor derived cell line 2 Melanoma, 1 Colon and 1 lung datasets contain each reads from a single region.

  Dataset EGAD00001007951