12055 results for "cancer rna-seq"

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• Pilocytic Astrocytoma RNA sequencing

  This dataset contains RNA sequencing samples from the Duesseldorf/LIsbon pilocytic astrocytoma cohort which was profiled using Proteogenomics (RNA Sequencing, proteomics and methylation). There are 48 samples which were sequenced using paired-end sequencing at the University Hopstial Dusseldorf.

  Dataset EGAD00001009053

• RNA sequencing data pre-treatment and post-treatment for NABUCCO cohort 1

  NABUCCO cohort 1 sequencing data. The dataset includes RNA sequencing pre-treatment on tumor samples (n=18) and RNA sequencing post-treatment on bladder tumor samples (n=18).

  Dataset EGAD00001006855

• Global RNA sequencing data of human iPSC-derived microglia from frontotemporal dementia (FTD) patients

  Global RNA sequencing of RNA samples extracted from human iPSC-derived microglia from healthy controls and sporadic (non-genetic) and genetic C9orf72 hexanucleotide repeat expansion-carrying patients with FTD

  Dataset EGAD50000002423

• MINCR is a MYC-induced lncRNA able to modulate MYC’s transcriptional network in Burkitt lymphoma cells

  Despite the established role of the transcription factor MYC in cancer, little is known about the impact of a new class of transcriptional regulators, the long non-coding RNAs (lncRNAs), on the way MYC is able to influence cellular transcriptome. To this aim we have intersected RNA-sequencing data from two MYC-inducible cell lines and from a cohort of 91 mature B-cell lymphomas carrying, or not carrying, genetic variants resulting in MYC over-expression. By this approach, we identified 13 lncRNAs differentially expressed in IG-MYC-positive Burkitt lymphoma and regulated in the same direction by MYC in the model cell lines. Among them we focused on a lncRNA that we named MINCR, for MYC-Induced long Non-Coding RNA, showing a strong correlation with MYC expression in MYC-positive lymphomas and also in pancreatic ductal adenocarcinomas. To understand its cellular role we performed RNA interference (RNAi) experiments and found that MINCR knock-down is associated with a reduction in cellular viability, due to an impairment in cell cycle progression. Differential gene expression analysis following RNAi showed a strongly significant enrichment of cell cycle genes among the genes down-regulate following MINCR knock-down. Interestingly these genes are enriched in MYC binding sites in their promoters, suggesting that MINCR acts as a modulator of MYC transcriptional program. Accordingly, following MINCR knock-down, we observed a reduction in the binding of MYC to the promoters of selected cell cycle genes. Finally we provide evidences that down-regulation of AURKA, AURKB and CTD1 may explain the reduction in cellular proliferation observed upon MINCR knock-down. We therefore suggest that MINCR is a newly identified player in the MYC transcriptional network able to control the expression of cell cycle genes.

  Dataset EGAD00001001441

• Type 2 Diabetes Starr County GWAS and Exome Sequencing

  The T2D Seq GWAS Starr County Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs001166 T2D Seq GWAS Starr County Cohort. phs000143 CIDR T2D Hanis phs001099 T2D GENES Starr County

  Study phs001166

• Type 2 Diabetes in African Americans, GWAS and Exome Sequencing

  The T2D Seq GWAS AA Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001167 T2D Seq GWAS AA Cohort. phs000140 CIDR T2D Bowdens phs001102 T2D GENES AA

  Study phs001167

• Evolving Cell States and Oncogenic Drivers during the Progression of IDH-Mutant Gliomas

  The study aims to understand the changes in cell states during the progression of IDH mutant gliomas. We generated scATAC-seq data from tumor samples of patients with IDH mutant gliomas, ranging from grade 2 to grade 4, including both IDH mutant oligodendroglioma and IDH mutant astrocytoma samples. Additionally, we have generated scRNA-seq data from patient-derived organoids that were treated with a DNMT1 inhibitor.

  Study phs003697

• Gene regulation of human stimulated and cultured CD4+ Treg cells

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs) stimulated using PMA and ionomycin or cultured without stimulus for 18 hours. It includes whole genome sequence data for ChM-seq (18 H3K4me3, 20 H3K27ac and 3 inputs), ATAC-seq (42 samples) and whole transcriptome (39 samples). All individuals were genotyped using coreExome Illumina SNP chip array (included in EGAS00001003516).

  Study EGAS00001003515

• Genomic Characterization of Head and Neck Squamous Cell Carcinoma Cell Lines

  Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer by incidence worldwide(1). Various chemical carcinogens (tobacco, alcohol and betel nut), human papillomavirus (HPV) infection, and genetic predisposition contribute to the etiology of HNSCC, and to the complex genetic alterations in tumor subsets that differ in prognosis and response to therapies (2). Recently, a comprehensive landscape of genomic and transcriptomic alterations in HNSCC tumors has emerged from The Cancer Genome Atlas (TCGA) Network (3). TCGA revealed novel and previously recognized gene and chromosomal region copy number alterations (CNAs), mutations, and expression clusters, and defined their frequency, co-occurrence, and relationship to common and rare subtypes of HPV(-) and (+) tumors that vary in prognosis. To identify cell line models for determining the functional role and therapeutic importance of these alterations, we are performing whole exome and RNA sequencing and bioinformatic analysis of an expanded panel of 15 HPV(-) and 11 HPV(+) HNSCC cell lines and primary oral keratinocytes. We find that the recurrent genomic alterations in cell lines are remarkably consistent with those found in more aggressive tumors, from which cell lines have traditionally been most readily adapted to culture (4). Genome-wide correlation of CN (copy number) with expression identified a suite of potential drivers or modifier genes that differ by HPV status, and are of potential biologic and therapeutic relevance. Further, our findings elucidate and validate genomic alterations underpinning numerous discoveries made with these widely-used and recently derived HNSCC lines, and provide a roadmap for their potential use as models for future studies of tumor subtypes with worse prognosis. References Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87-108. Van Waes C, Musbahi O. Genomics and advances towards precision medicine for head and neck squamous cell carcinoma. Laryngoscope Investig Otolaryngol. 2017;2(5):310-9. Cancer Genome Atlas N. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature. 2015;517(7536):576-82. White JS, Weissfeld JL, Ragin CC, Rossie KM, Martin CL, Shuster M, et al. The influence of clinical and demographic risk factors on the establishment of head and neck squamous cell carcinoma cell lines. Oral Oncol. 2007;43(7):701-12.

  Study phs001581

• Pathogenic Neurofibromatosis type 1 (NF1) RNA splicing resolved by targeted RNAseq

  Neurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. Therefore, a targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants. an in-house developed tool (QURNAS) was used to calculate the enrichment score (ERS) for each splicing event. RNA enrichment of NF1 and SPRED1 was done using SPET (NUGEN - NF1 only) and using SureSelect (Agilent - NF1 and SPRED1).

  Study EGAS00001005530

• Microbiomic and immunogenic biomarkers of adjuvant chemotherapy efficacy in stage III colorectal cancer

  The standard treatment for stage III colorectal cancer (CRC) is surgery, followed by adjuvant chemotherapy (AC). However, the efficacy of AC is limited, and approximately 30% of patients experience recurrence. Therefore, easily assessable molecular biomarkers that can predict response to AC are needed. Here, we aimed to identify predictive biomarkers of response to AC using tumor transcriptomic data. Tumor specimens from 253 patients who underwent surgery for stage III CRC between 1997 and 2019 were analyzed using RNA sequencing. Transcriptional subtyping and analyses of gut microbiome, immune cell fractions, and T-cell receptor (TCR) were performed to identify factors associated with recurrence-free survival (RFS) in patients treated with or without AC. Of 253 patients, 118 (46.6%) received AC. Twenty phyla and 799 species of the microbiomes were identified, among which Fusobacteria were identified in 247 patients (97.6%). Multivariable Cox proportional hazards regression analysis of patients who received AC showed that intratumoral Fusobacterium and M1 macrophage abundance and diversity of TCR alpha and delta (TRAD) were independently associated with RFS. Fusobacterium and M1 macrophage abundance, and TRAD diversity were associated with the response to AC, suggesting that these factors could serve as biomarkers for personalized treatment in stage III CRC.

  Study JGAS000875

• ATAC-seq data from primary AML samples with t(3;8)

  Open chromatin regions in the MYC super-enhancer region were investigated by ATAC-seq in t(3;8) AML. ATAC-seq was performed as described (Buenrostro et al, 2013) with a modification in the lysis buffer (0.30 M sucrose, 10 mM Tris pH 7.5, 60 mM KCl, 15 mM NaCl, 5 mM MgCl2, 0.1 mM EGTA, 0.1% NP40, 0.15 mM Spermine, 0.5 mM Spermidine, 2 mM 6AA) to reduce mitochondrial DNA contamination.

  Dataset EGAD00001007910

• ATAC-seq dataset of patient and healthy donors

  ATAC-seq dataset on a patient (P) presenting with defects of immunity and two (C5, C6) healthy donors. This dataset contains raw and processed files from ATAC-seq chromatin accessibility analysis. There are 3 single-read (50 bp) fastq files (1 per patient/ donor). Processed files consist of narrowPeak files (1 per patient/ donor) and one file that contains read counts in consensus peaks.

  Dataset EGAD00001008370

• ChIP-Seq on multiple myeloma and plasma cell leukaemia cell lines

  ChIP-seq data (H3K4Me1, H3K4Me3, H3K27Ac histone modifications) in experimental triplicates on multiple myeloma cell line KMS11 and plasma cell leukaemia cell lines L363 and JJN3. ChIP reactions were performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal Kit. ChIP libraries were generated using HTP Illumina library preparation kit, and sequenced using Illumina HiSeq 2000 with 100 bp single-ended reads. ChIP-seq files are in BED format.

  Dataset EGAD00001003349

• BLUEPRINT September 2016, ChIP-Seq for thymocyte from thymus, on Genome GRCh38

  ChIP-Seq data for 5 sample(s) for thymocyte from thymus, on Genome GRCh38. 17 run(s), 17 experiment(s), 17 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002947

• Dataset to study clonal evolution in TCF3:PBX1 patient SJE2A066 using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJE2A066 with 69 high quality cells sequenced (62 blast and 7 normal)

  Dataset EGAD00001011329

• Dataset to study clonal evolution in TCF3:PBX1 patient SJE2A063 using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJE2A063 with 80 high quality cells sequenced (75 blast and 5 normal)

  Dataset EGAD00001011328

• Dataset to study clonal evolution in TCF3:PBX1 patient SJE2A067 using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJE2A067 with 78 high quality cells sequenced (73 blast and 5 normal)

  Dataset EGAD00001011330

• ATAC-seq of spermatogonia

  Raw sequencing reads of ATAC-seq of spermatogonia in FASTQ format, comprising 6 samples sequenced on the Illumina HiSeq 4000 platform.

  Dataset EGAD00001007759

• RCC ATAC-seq data

  ATAC-seq data 72cases

  Dataset EGAD00001009868

• Dataset to study clonal evolution in iAMP21 patient SJBALL030072using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJBALL030072with 66 high quality cells sequenced (61 blast and 5 normal)

  Dataset EGAD00001010288

• Neuroblastoma Cell Line Circle-seq Data

  This dataset comprises Circle-seq data for 12 neuroblastoma cell lines supporting Koche et al. Extrachromosomal circular DNA drives oncogenic genome remodeling in neuroblastoma (2020).

  Dataset EGAD00001006579

• non-IVF MeDIP-seq bam files

  Bam files consisting of aligned MeDIP-seq reads from cord blood cells and cord blood mononuclear cells of twins not conceived through in vitro fertilisation

  Dataset EGAD00001003159

• TRACERx 100: whole exome data of the first 100 TRACERx tumours

  BACKGROUNDTRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). METHODSMultiregion high-depth whole-exome sequencing (M-seq) was performed on 100 early stage NSCLC tumors resected prior to systemic therapy. A total of 327 tumor regions were sequenced and analyzed to define evolutionary histories, obtain a census of clonal and subclonal events, and assess the relationship between ITH and recurrence-free survival (RFS). RESULTSWidespread ITH was observed for both somatic copy number alterations (median 48% [0.03-88%]) and mutations (median 30% [0.5-93%]). Driver mutations in EGFR, MET, BRAF and TP53 were almost always clonal. However, heterogeneous driver alterations occurring later in evolution were found in over 75% of tumors and were common in PIK3CA, NF1 and genes involved in chromatin modification and DNA response and repair. Genome doubling and ongoing dynamic chromosomal instability (CIN), illustrated by mirrored subclonal allelic imbalance, were identified as causes of ITH resulting in parallel evolution of driver copy number events, including amplifications of CDK4, FOXA1, and BCL11A. Elevated copy number heterogeneity was associated with shorter RFS (HR=4.9, P=0.00044), which remained significant in a multivariate analysis.CONCLUSIONSITH mediated through CIN, rather than point mutational heterogeneity, was associated with increased risk of relapse, supporting its value as a prognostic predictor, and the need to target this high-risk phenotype.

  Study EGAS00001002247

• Bulk RNA Sequencing of 86 Human Donor Lungs

  The goal of this study was to characterize the effect of age on gene expression in normal human lung. We collected distal lung samples from 86 human donors distributed in age between 16 and 76 years and extracted RNA for Illumina-based sequencing.

  Study phs002484