10004 results for "cancer rna-seq"

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• Genomic (WGS) data for the validation of the glioblastoma progression study (GBMatch).

  43 low-coverage genomes derived from fresh-frozen glioblastoma tumor samples. These genomes have been produced for validation purposes and match the corresponding RRBS and RNA-seq profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004077

• KNS42 and SF188 H3K36me3 chipSeq

  Chromatin immunoprecipitation (ChIP) was carried out employing antibodies against H3K36me3 and RNA polymerase II using the HistonePath and TranscriptionPath assays by ActiveMotif. Whole genome sequencing was carried out using an Illumina HiSeq2000 and data is provided as 6 BAM files. H3K36me3 chipseq RNA polymerase II chipseq and input coverage for each cell line.

  Dataset EGAD00001004119

• COLONOMICS small RNA sequencing

  This dataset consists of SOLiD small RNA-seq of 250 colorectal samples: 100 tumor tissue samples, 100 normal tissue samples (adjacent to tumor sites) and 50 matched control samples of healthy individuals. CSfasta and qual files converted to single fastq files prior to uploading.

  Dataset EGAD00001004827

• MESA colorectal cancer cfDNA EM-seq dataset

  This dataset contains the methylation sequencing data of 60 nonCancer and 70 colorectal cancer cfDNA samples. The methylation library is constructed by using NEBNext Enzymatic-seq Kit.

  Dataset EGAD00001009165

• Single cell RNA-Seq of Clear Cell Sarcoma of the Kidney

  Dataset EGAD00001007498

• UTSW ChRCC Cohort 2024

  This DAC controls access to the WES and RNA-Seq data for study: Molecular underpinnings of dedifferentiation and aggressiveness in chromophobe renal cell carcinoma.

  Dac EGAC50000000203

• Time course acetalax bisacodyl treatment

  RNA-Seq raw data of PDX treated with acetalaxor bisacodyl for 4h00 to 24h00.

  Dataset EGAD50000000875

• Ribosomal Depleted Total RNA-Seq of PBMCs and Skin from Controls and Systemic Sclerosis Patients

  This study involved prospective collection of skin biopsies and peripheral blood mononuclear cell (PBMC) samples from controls with no self-reported history of autoimmune or inflammatory disease and cases with Rheumatologist-confirmed systemic sclerosis: limited cutaneous systemic sclerosis (lcSSc), diffuse cutaneous systemic sclerosis (dcSSc), very early diagnosis of systemic sclerosis (VEDOSS), and systemic sclerosis sine scleroderma (SSS). Some SSc cases were sampled at a 6 month routine follow-up visit. PBMCs were collected and lysed immediately. Skin punches were stabilized in RNAlater until extraction. All RNA-Seq libraries were created using Takara/Clontech ribosomal depletion kits, and sequenced on either a HiSeq2500 or HiSeq3000.

  Study phs002902

• BLUEPRINT RNA-seq data for common cells in the haematopoietic lineages, from adult and cord blood samples.

  RNA-seq data for common cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000327

• Childhood Cancer Data Initiative (CCDI): Comprehensive Genomic Sequencing of Pediatric Cancer Cases (CMRI/KUCC)

  This study provides paired tumor normal genomic sequencing data from approximately 200 children with cancer, including both solid tumors and leukemias, done by the Children’s Mercy Research Institute (CMRI) and University of Kansas Cancer Center (KUCC). These data include whole genome sequencing (generally, ~20x), whole exome sequencing (generally, ~300x), bulk RNA sequencing (generally, ~80 million reads), and single-cell RNA and ATAC sequencing (>50,000 reads/cell). Additional phenotypic, pathologic, and genetic data, gathered clinically for these samples, are also provided.

  Study phs002529

• CPTAC: Proteogenomic Studies of Ovarian Tumor Responses to Agents Targeting the DNA Damage Response

  There is a critical unmet need for predictors of chemo-refractory High-grade serous ovarian cancer (HGSOC). Despite over 3 decades of research on platinum responses in cancer, no predictive biomarker has been translated into clinical use. Predictors of refractory disease could spare these patients the unnecessary toxicity of a platinum-based regimen and provide a means to triage these patients to clinical trials to identify effective therapies for refractory disease. This study has approached the development of a predictor in a novel way enabling detection of a multi-analyte panel biomarker capable of detecting a subset of refractory HGSOCs with high specificity and implicating potential treatment vulnerabilities for refractory disease. We reported the first proteogenomic analysis of platinum refractoriness in HGSOC and made the novel dataset available as a resource to the community, including a ProTrack portal: http://ptrc.cptac-data-view.org/. Detailed proteogenomic profiles were generated for this study from a retrospective cohort of 242 treatment-naive HGSOCs with enriched representation of "exceptional non-responders" (i.e., patients with chemo-refractory disease). Whole genome sequence (WGS) and RNA seq FASTQ files are available through dbGaP. Proteomic data are available through the NCI Proteomic Data Commons (PDC): https://pdc.cancer.gov/pdc/.

  Study phs003152

• Molecular determinants of response to PD-L1 blockade across tumor types

  Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis lead to durable clinical responses in subsets of cancer patients across multiple indications, including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and renal cell carcinoma (RCC). Herein, we complement PD-L1 immunohistochemistry (IHC) and tumor mutation burden (TMB) with RNA-seq in 366 patients to identify unifying and indication-specific molecular profiles that can predict response to checkpoint blockade across these tumor types. Multiple machine learning approaches failed to identify a baseline transcriptional signature highly predictive of response across these indications. Signatures described previously for immune checkpoint inhibitors also failed to validate. At the pathway level, significant heterogeneity was observed between indications, in particular within the PD-L1+ tumors. mUC and NSCLC were molecularly aligned, with cell cycle and DNA damage repair genes associated with response in PD-L1- tumors. At the gene level, the CDK4/6 inhibitor CDKN2A was identified as a significant transcriptional correlate of response, highlighting the association of non-immune pathways to the outcome of checkpoint blockade. This cross-indication analysis revealed molecular heterogeneity between mUC, NSCLC and RCC tumors, suggesting that indication-specific molecular approaches should be prioritized to formulate treatment strategies.

  Study EGAS00001004343

• Non-coding RNAs in breast cancer

  Using RNA CaptureSeq we annotated non-coding RNAs transcribed from genome intervals surrounding breast cancer risk signals in a range of mammary-derived tissue and cell lines.

  Study EGAS00001003353

• Single-Cell and Spatial Multi-Omics Highlight Effects of Anti-Integrin Therapy Across Cellular Compartments in Ulcerative Colitis

  This is a focused, nested case-control study within our larger cohort "Immunoprofiling of the Blood and Intestine and Creation of a Gut Cell Atlas". This sub-study is titled as "Single-cell and spatial multi-omics highlight effects of anti-integrin therapy across cellular compartments in ulcerative colitis”. We examined the impact of Vedolizumab (VDZ), an anti-integrin antibody therapy, on the cellular landscape of ulcerative colitis (UC). While VDZ is primarily recognized for its role in preventing lymphocyte migration to the gut, the extent of its influence on other cellular populations has not been fully characterized. We used single-cell RNA sequencing (scRNA-seq) and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to profile cells from both the blood and colon tissue samples. We pooled single-cell suspensions together before running scRNA-seq and CITE-seq, and subsequently deconvoluted the samples using the freemuxlet and demuxlet algorithms and variant call files (vcf) from bulk RNA-seq. This allowed us to assign cells to individual study subjects. We compared the cellular compositions of healthy individuals to those of UC patients undergoing treatment with VDZ or mesalamine (5-aminosalicylic acid/5-ASA). Our results revealed that VDZ induces significant changes in the variety and dynamics of mononuclear phagocytes within both the bloodstream and intestinal tissue, accompanied by subtle variations in lymphocyte populations. The dbGaP submission will provide raw sequencing data and participant phenotype data regarding disease and treatment status.

  Study phs003502

• Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas: RNAseq variants

  Variants called from RNA-seq data of meningioma tumors.

  Dataset EGAD00001002649

• Berlin Neuroblastoma Dataset

  Paired tumor/normal WGS and RNA-seq of primary neuroblastoma.

  Dataset EGAD00001005488

• Covacta RNAseq merged EGA metadata

  Sample metadata for the RNA-seq dataset. This dataset includes subject-level data and longitudinal visit day information for the corresponding samples.

  Dataset EGAD00001011162

• RNA-Seq of human stimulated and cultured CD4+ Treg cells

  This dataset includes whole transcriptome data of human stimulated and cultured CD4+ Treg cells (39 samples).

  Dataset EGAD00001005964

• RNA-seq data of CRC-PDX tumors

  We obtained bulk RNAseq data of CRC-PDX tumors and performed molecular subtype classification.

  Dataset EGAD50000000850

• NKI-AvL CRC-OVC DNA-seq

  The dataset “NKI-AvL CRC-OVC DNA-seq" includes 4 normal and 4 tumor BAM files from paired-end whole exome sequencing on Illumina HiSeq2500 and Illumina NovaSeq6000 for 2 colorectal cancer and 2 ovarian cancer patients.

  Dataset EGAD00001004340

• Patient-derived lung cancer organoids

  Patient-derived lung cancer organoids cram files : targeted seq 13 samples, whole exome seq 12 samples mutation profiles of PDO and matched tissue : aggregated vcf 1 file details : https://www.nature.com/articles/s41467-019-11867-6

  Dataset EGAD00001005317

• CITE-seq of early breast cancer

  CITE-seq of early breast cancer samples.

  Dataset EGAD00001007058

• Extracellular transcriptome in seminal plasma for non-invasive prostate cancer diagnosis

  A diagnostic non-invasive biomarker test for prostate cancer at an early stage, with high sensitivity and specificity, would improve diagnostic decision making. Extracellular RNAs present in seminal plasma might contain biomarker potential for the accurate detection of clinically significant prostate cancer. So far, the extracellular messenger RNA (mRNA) profile of seminal plasma has not been interrogated for its biomarker potential in the context of prostate cancer. Here, we investigate the mRNA transcriptome in seminal plasma samples obtained from prostate cancer patients (n=25), patients with benign prostate hyperplasia (n=26) and individuals without prostatic disease (n=6). Seminal plasma harbors a complex mRNA repertoire that reflects prostate as its tissue of origin. The endogenous RNA content is higher in the prostate cancer samples compared to the control samples. Prostate cancer antigen 3 (PCA3), a long non-coding RNA with prostate cancer-specific overexpression, and ATP-binding cassette transporter 1 (ABCA1), known to be involved in the prostate cancer pathogenesis, were more abundant in the prostate cancer group. In addition, twelve high confidence fusion transcripts could be detected in prostate cancer samples, including the bona-fide prostate cancer fusion transcript TMPRSS2-ERG. Our findings provide proof-of-principle that the extracellular transcriptome of seminal plasma can reveal information of an underlying prostate cancer.

  Study EGAS00001005277

• Single cell RNA sequencing of colorectal cancer

  To understand intrinsic cancer cell signatures and the surrounding microenvironemt and their interactions, we performed single-cell RNA sequencing on 63,689 cells from 23 patients with 23 primary colorectal cancer and 10 matched normal mucosa samples. Analyzing of primary colorectal cancer and normal mucosa samples show a comprehensive cellular landscape of colon cancer, which is a valuable resource for the development of therapeutic strategies.

  Dataset EGAD00001005198

• Pancreatic cancer RNA sequencing

  Study EGAS00001004706