15013 results for "cancer studies using rna-seq"

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• MSC_busulfan_small_intestine_organoids

  This dataset represent the RNA-seq, which was done on untreated small intestinal organoids; small intestinal organoids treated with chemotherapeutic, busulfan; untreated small intestinal organoids co-cultured wth mesenchymak stromal/stem cells (MSCs; busulfan treated small intestinal organoids co-cultured with MSCs. The same set of samples was done for 3 different primary bone marrow MSC donors.

  Dataset EGAD00001011176

• RNA-seq transcriptome of bronchial brush samples from COPD and control

  Human subjects (COPD patients or apparently healthy controls) where investigated by bronchoscopy and a 5 mm brush was used to sample the subsegment airways of the right lung. The material obtained mainly consist of bronchial epithelial cells plus some contamination with leukocytes. For further details see Ziegler-Heitbrock et al, European Respiratory Journal, 40:823-829, 2012.

  Dataset EGAD00001002003

• RNA-seq data of Metabolic profiling of patient-derived organoids reveals nucleotide synthesis as a metabolic vulnerability in malignant rhabdoid tumors

  Patient-matched normal kidney organoid (103H) and MRT tumoroid (103T2) models were treated for 24h with either DMSO (ctrl), 400nM MTX, or 50nM BAY to investigate the direct effects of drug treatment on the expression of key metabolic enzymes in the nucleotide biosynthesis pathways.

  Dataset EGAD00001015391

• Adipocytes Regulate Fibroblast Function and Their Loss Contributes to Fibroblast Dysfunction in Inflammatory Diseases

  We profiled live synovial cells from 16 individuals with no diagnosed arthritis using single-cell RNA sequencing. Our study was designed to provide a reference single cell RNA sequencing dataset for researchers interested in studying arthritic synovium, providing sequencing data on healthy synovial cells for comparison to cells from diseased synovial tissues. Synovial tissue was collected post-mortem from three different sources between 2019-2021: the National Disease Research Interchange, a collaboration with Rush University and the Gift of Hope, and the Brigham and Women's Hospital Autopsy Department. To be included in the study, patients had to be between the ages of 18 to 72 and have no diagnosed arthritis or autoimmune diseases. Additionally, this study includes bulk RNA sequencing data of cultured primary synovial fibroblasts isolated from three rheumatoid arthritis patents. Cells were stimulated with either cortisol, fat conditioned media, TGFβ, TNFα, fat conditioned media with mifepristone, TGFβ with fat conditioned media, or TNFα with fat conditioned media. Cells were harvested 4 or 22 hours later and lysates collected for sequencing. Data from this study submitted to the Gene Expression Omnibus (GEO) may be accessed via accession number GSE233504.

  Study phs003304

• MP2PRT-MNG: Identifying Novel Molecular Markers of Response to Radiotherapy in Meningiomas Using Samples from the RTOG-0539 (NCT00895622)

  The Molecular Profiling to Predict Response to Treatment (MP2PRT) program is part of the NCI's Cancer Moonshot Initiative. The aim of this program is the retrospective characterization and analysis of biospecimens collected from completed NCI-sponsored trials of the National Clinical Trials Network and the NCI Community Oncology Research Program. NRG RTOG (Radiation Therapy Oncology Group)-0539, which was a nonrandomized phase II cooperative group trial in 2009, was selected for inclusion in this program. NRG RTOG-0539 assigned patients with histologically confirmed diagnosis of meningioma to 1 of 3 risk groups based on 2007 WHO grade, resection extent, and recurrence status, and radiotherapy was given per protocol to the intermediate- and high-risk cases. Under the MP2PRT program, DNA methylation profiling, RNA sequencing, and whole exome sequencing were performed on clinical trial cases with available tissue for molecular analyte extraction and subsequent sequencing. Raw molecular data with metadata are available for this study.

  Study phs003707

• Assessing the impact of low frequency coding variants on disease risk using the Exomechip

  Following several rounds of Genome Wide Association (GWA) scans and subsequent meta-analyses of results multiple risk loci have been identified for many common diseases. However, in most instances the implicated common variants identified so far explain only a modest fraction of the genetic risk. In parallel to our efforts to identify the causative variants in the known loci it is necessary to assess the full spectrum of sequence variants for disease risk and in particular low frequency and rare variants that have not been tested in a comprehensive way so far. To this end an international effort by investigators who have performed whole exome sequencing in circa 12,000 individuals have assembled a set of ~250,000 exonic variants of low frequency – defined as seen in at least two studies and a minimum of three individuals (non-sysnonymous) or two individuals for SNPs altering splice sites / stop codons. The SNP content from the exome studies was complemented with additional interesting SNP sets totalling 25,000 markers (GWA tag SNPs, grid of common variants, HLA, Mitochondrial, Y-chromosome etc) and were used to generate a custom iSELECT array, the exome chip. Adequately powered association studies to test low frequency variants for association to disease risk are still very expensive if conducted by whole exome sequencing. The exome chip provides a cost efficient way to undertake such an experiment and the Wellcome Trust Cases Control Consortium will be applying this approach to eight diseases, type 1 and type 2 diabetes, coronary artery disease, hypertension, multiple sclerosis, rheumatoid arthritis, bipolar, and ankylosing spondylitis. The first objective will be to generate a large set of at least 10,000 common UK controls as analysis of lower frequency variants will require large sample sizes. This includes ~6000 samples from the 1958 Birth Cohort.

  Study EGAS00001000584

• Impact of mutational profiles on response of primary oestrogen receptor-positive breast cancers to oestrogen deprivation

  Presurgical studies allow study of the relationship between mutations and response of estrogen receptor positive (ER+) breast cancer to aromatase inhibitors (AIs) but have been limited to small biopsies. Here in Phase I of this study, we perform exome sequencing on baseline, surgical core-cuts and blood from 60 patients (40 AI treated, 20 Controls). In poor responders (based on Ki67 change) we find significantly more somatic mutations than good responders. Subclones exclusive to baseline or surgical cores   occur in approximately 30% of tumours. In Phase II we combine targeted sequencing on another 28 treated patients with Phase I. We find six genes frequently mutated: PIK3CA, TP53, CDH1, MLL3, ABCA13 and FLG with 71% concordance between paired cores. TP53 mutations are associated with poor response. We conclude that multiple biopsies are essential for confident mutational profiling of ER+ breast cancer and TP53 mutations are associated with resistance to oestrogen deprivation therapy.

  Dataset EGAD00001002651

• an integrated molecular study of clear cell renal cell carcinoma (ccRCC) including whole-genome/exome and RNA sequencing as well as array-based gene expression/copy-number/methylation analyses

  an integrated molecular study of clear cell renal cell carcinoma (ccRCC) including whole-genome/exome and RNA sequencing as well as array-based gene expression/copy-number/methylation analyses

  Study EGAS00001000509

• Clinical panel sequencing of cancer of unknown primary using Comprehensive cancer panel (CCP)

  This database includes comprehensive cancer panel (CCP) on paired tumour and germline DNA from cancer of unknown primary samples, all of which are matched to WGS data under this study. This data was used to compare biomarker yield against what was achieved with WGS. This dataset contains n=34 tumour-germline paired samples. All samples are in BAM format aligned with GRCh38 reference genome.

  Dataset EGAD50000000655

• A case of colorectal cancer with ERBB2 c.2264T>C (p.Leu755Ser) mutation

  This data set contains next generation sequencing (NGS) data of two serial tumor samples (primary and a metastasis) from a patient with colorectal cancer showing an ERBB2 c.2264T>C (p.Leu755Ser). NGS was performed using the Illumina TruSeq Amplicon Cancer Panel (TSACP, Illumina) covering 212 amplicons in 48 cancer associated genes on the Illumina MiSeq sequencing platform. The dataset contains two BAM files.

  Dataset EGAD00001002252

• Studies of a Targeted Risk Reduction Intervention through Defined Exercise (STRRIDE)

  The STRRIDE study is the combination of three interventional trials to evaluate dose and intensity of physical activity on cardiometabolic health. The three component studies are Peripheral Effects of Exercise on Cardiovascular Health (STRRIDE I, ClinicalTrials.gov Identifier: NCT00200993), Effects of Resistence and Aerobic Exercise on Cardiovascular Health (STRRIDE II, ClinicalTrials.gov Identifier: NCT00275145) and Exercise Dose-Response Effects in Prediabetes (STRRIDE-PD, ClinicalTrials.gov Identifier: NCT00962962).

  Study phs001855

• Oxford Nanopore long-read sequencing data of high-grade serous ovarian cancer

  This dataset comprises whole-genome Oxford Nanopore long-read sequencing data from six high-grade serous ovarian cancer (HGSOC) patients, including cryopreserved, pre-treatment tumor tissues and matched peripheral blood samples (12 samples in total). High-molecular-weight DNA was prepared using the SQK-LSK114 Ligation Sequencing Kit and sequenced on FLO-PRO114M flow cells (R10.4.1). Basecalling was conducted using the super-accurate (SUP) model, enabling simultaneous detection of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). The dataset includes BAM files containing base modification information for downstream genomic and epigenomic analyses.

  Dataset EGAD50000001509

• Evaluation of capture and amplicon-based targeted sequencing methods on formalin-fixed tumours

  Evaluated performance of three capture (Agilent’s SureSelectXT HS, Illumina’s Nextera Rapid Capture Custom, and New England Biolabs’ Next Direct Custom) and one amplicon-based (Qiagen’s Human Breast Cancer Panel) targeted sequencing methods on paired blood and FFPE, using whole exome sequencing data from matched fresh-frozen tissue as a comparison.

  Study EGAS00001004965

• scRNA seq and scTCR seq data from 5 melanoma patients

  The Chromium Controller and Chromium X platfor of 10X Genomics were used for single cell partitioning and barcoding. Each cell's transcriptome was barcoded during reverse transcription, pooled cDNA was amplified and Single Cell 5' Gene Expression (GEX), V(D)J and Feature Barcode (FB) Libraries were prepared according to the manufacturer's protocols (CG000330 and CG000331, 10X Genomics). All libraries were quantified and normalized on library QC data generated on the Bioanalyzer system according to manufacturer's protocols (G2938-90321 and G2938-90024, Agilent Technologies). Based on the expected target cell counts, a balanced library sub-pool of samples was compsed for SC5'GEX, V(D)J and FB libraries. Library sub-pools were quantified by qPCR, accodring to the KAPA Library Quantification Kit Illumina(R) Platforms protocol (KR0405, KAPA Biosystems). Based on qPCR results a final sequencing pool was composed. Paired end sequencing was performed on a NovaSeq 6000 Instrument (Illumina) using NovaSeq 6000 Reagent Kits v1.5 100 cycles (cat. no. 20028401, 20028319, 20028316 Illumina), using 28 cycles for Read 1, 10 cycles for Read i7, 10 cycles for Read i5 and 90 cycles for Read 2.

  Dataset EGAD50000001155

• Targeted sequencing of 72 prostate cancer driver in 712 plasma cell free DNA samples

  Dataset contains targeted sequencing data of 712 plasma cell free DNA samples and 428 white blood cell samples collected from 428 men with metastatic prostate cancer. Target capture was performed using a hydridization-based custom Roche SeqCap EZ Choice kit, designed to capture all exons of 72 prostate cancer driver genes. Cell free DNA was extracted from 10 mL blood samples. Libraries were sequenced using Illumina HiSeq 2500 or Illumina MiSeq instruments to a median coverage of 750x. 62% of samples had ctDNA fraction above 2% of total cfDNA. Note that "Dataset type" is erroneously listed as "Amplicon sequencing", because "Captured-based targeted sequencing" or "Hybridization-based targeted sequencing" were not available options in EGA at the time of submission.

  Dataset EGAD00001004208