11768 results for "cancer rna-seq"

in 14.69 milliseconds.

• Lipomatous tumors with 12q amplification

  The project concerns whole genome sequencing (short-read and long-read) and RNA-sequencing of lipomatous tumors with 12q-amplification. A subset of lipomatous tumors is driven by amplification of genes mapping to chromosome arm 12q, including the MDM2 gene. The goals of the study were to compare expression levels of genes mapping to 12q in tumors with amplification in rod-shaped or circularized chromosomes as well as to assess and compare the structural variants in those tumors. In total, 20 samples were analyzed, and the data were correlated with genomic data on bulk and single cell DNA from the same tumors. The fastq files from the tumors were uploaded to EGA.

  Study EGAS50000000062

• Single nuclei ATAC-Seq data from the human ganglionic eminences

  We performed the single nuclei Assay for Transposase-Accessible Chromatin with Sequencing (snATAC-Seq) to map potential regulatory genomic regions operating in individual cell populations of the human GE, using these to test for enrichment of schizophrenia common genetic variant liability and to functionally annotate non-coding variants associated with the disorder.

  Study EGAS50000000411

• ChIP-seq analysis of clear cell renal cell carcinoma

  In order to understand the epigenetic basis on ccRCC, we performed ChIP-seq on 3 ccRCC cell lines (786-O, A498, UMRC-2), and 1 normal kidney epithelium cell line (HK-2), cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. This study analysed data from H3k4me1, H3K4me3, H3K27ac, H3k27me3, H3k36me3, CTCF, and HIF1A

  Study EGAS50000001322

• ChIP-seq data of H3K4me3, H3K27ac and H3K27me3 on multiple human embryonic tissues.

  The regulatory landscape of the human genome during organogenesis is undescribed for most tissues. We used ChIP-seq to survey histone modifications in 13 human embryonic tissues. We describe patterns of both common and tissue-specific marking of promoter activation and repression and use enhancer usage to infer regulatory pathways.

  Study EGAS00001003163

• PhIP-Seq data

  Inflammatory bowel diseases (IBD), e.g. Crohn’s disease (CD) and ulcerative colitis (UC), are chronic immune-mediated inflammatory diseases. A comprehensive overview of an IBD-specific antibody epitope repertoire is, however, lacking. We leveraged a high-throughput phage-displayed immunoprecipitation sequencing (PhIP-seq) workflow to identify antibodies against 344,000 antimicrobial, immune and food antigens in 497 IBD patients.

  Study EGAS00001007054

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  ChIP-Seq data for 172 CD14-positive, CD16-negative classical monocyte sample(s). 572 run(s), 345 experiment(s), 340 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002672

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD4-positive, alpha-beta T cell, on genome GRCh37)

  ChIP-Seq data for 154 CD4-positive, alpha-beta T cell sample(s). 355 run(s), 265 experiment(s), 250 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002673

• scRNA-seq dataset of patient and healthy donors

  scRNA-seq dataset on a patient (P) presenting with defects of immunity and four healthy donors (C1, C2, C3, C4). This dataset contains raw and processed files from scRNA-seq performed on samples using the 10x Genomics Chromium Controller with the Chromium Single Cell 3′ Reagent Kit (v3 chemistry). There are 15 paired-end fastq files (3 per patient/donor - I1, R1, R2) and 15 processed files generated with 10x Genomics Cell Ranger v3.0.2 software against GRCh38 human reference transcriptome (3 per patient/donor - barcodes.tsv.gz, features.tsv.gz, matrix.mtx.gz).

  Dataset EGAD00001008372

• ChIP sequencing for β-catenin and histone modifications in HCC cell lines and organoids with CTNNB1 mutations

  CTNNB1 mutation is a major driver of HCC, particularly in metabolic-associated subtype. This study utilized patient-derived tumour organoids and cell lines harbouring various endogenous CTNNB1 mutations to comprehensively map the transcriptional repertoire regulated by mutant β-catenin through ChIP-seq under normal and fatty conditions. Genome-wide binding patterns of β-catenin were integrated with ChIP-seq data for histone modifications H3K27ac and H3K27me3 to assess active and repressive chromatin states. Oleic acid treatment was used to model fatty conditions.

  Study EGAS50000001274

• Title: Divergent levels of CD112 and INKA1 define a distinct subset of human long-term hematopoietic stem cells

  The data provided here was critical in establishing that human long-term hematopoietic stem cells (LT-HSC), previously described as the most primitive HSC population, is actually composed of distinct subsets that can be prospectively isolated. Via mechanistic studies centering around the Rho-GTPase effector kinase PAK4 and its inhibitor INKA1, we identified the immune checkpoint ligand CD112 as a marker for hematopoietic stem and progenitor cells, that is highest expressed on LT-HSC. More importantly, CD112 can be used to stratify functionally distinct subsets within LT-HSC: In response to regeneration-mediated stress, the CD112low subset exhibits a transient restraint (termed latency) before contributing to hematopoietic reconstitution, while the CD112high subset is primed to respond rapidly. High resolution RNA-seq of the CD112 surface expression spectrum within rare LT-HSC subsets (human umbilical cord blood) demonstrated that more genes are differentially upregulated in the deeper quiescent and less metabolic active subset. Genes enriched in this subset centre around cell adhesion and Rho-GTPase signaling. This is in agreement with the scRNAseq data from human G-CSF mobilized peripheral blood (mPB) generated here that was used as an model of in vivo activation/priming revealing via RNA-velocity and pseudo-time analysis that INKA1high versus PAK4high, CDK6high and CD112high enrichment are either detected early or late in diffusion pseudotime indicative of quiescent versus primed cell status, respectively. RNAseq following INKA1 overexpression in LT-HSC and ST-HSC revealed by GSEA an overall stemness preserving phenotype and particularly in LT-HSC, but not in short-term HSC (ST-HSC), suppression of transcriptional programs linked to activation. Collectively, our data decipher the molecular intricacies underlying HSC heterogeneity and self-renewal regulation and point to latency as an orchestrated physiological response that integrates quiescence control with HSC fate choices to preserve a stem cell reservoir.

  Dataset EGAD00001006541

• scRNA-seq and scTCR-seq from 7 MF patients

  Dataset containing scRNA and scTCR sequencing of 7 patients with cutaneous T cell lymphoma. Sequencing was performed on Illumina NextSeq 550, HiSeq 4000 and NovaSeq 6000. The sequencing was always paired.

  Dataset EGAD50000000332

• Spontaneously differentiatiated iPSCs to EBs

  SUM-seq data (single-cell chromatin accessibility and gene expression) for spontaneously differentiatiated iPSCs. This data is the representative data in the Nature Protocols publication.

  Study EGAS50000001094

• BLUEPRINT September 2016, ATAC-seq for tonsil, on Genome GRCh38

  ATAC-seq data for 7 sample(s) from tonsil, on Genome GRCh38. 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002708

• Transcription factor binding in human monocyte differentiation

  This dataset consists of ChIP-seq data data from human monocytes, monocyte-derived dendritic cells as well as monocyte-derived cells that were subjected to mRNA transfection for PU.1, IRF4, and EGR2. In total, it the data set includes 18 samples.

  Dataset EGAD00001006602

• BLUEPRINT September 2016, ATAC-seq Chronic Lymphocytic Leukemia from venous blood, on Genome GRCh38

  ATAC-seq data for 106 sample(s) Chronic Lymphocytic Leukemia from venous blood, on Genome GRCh38. 111 run(s), 109 experiment(s), 109 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002916

• scRNA-seq dataset for AD and Pso patients

  This dataset contains scRNA-seq fastq files to the paper entitled "Single-cell profiles reveal distinctive immune response in atopic dermatitis in contrast to psoriasis". The details of experiment setup was described in the paper.

  Dataset EGAD00001010106

• NKI-AvL OpACIN DNA-seq of stage III melanoma patients

  The dataset “NKI-AvL OpACIN DNA-seq of stage III melanoma patients" includes 2 x 18 normal and 2 x 18 tumor FASTQ files from paired-end whole exome sequencing on Illumina HiSeq2500 for 18 stage III melanoma patients.

  Dataset EGAD00001004217

• BLUEPRINT September 2016, ATAC-seq Mantle Cell Lymphoma from venous blood, on Genome GRCh38

  ATAC-seq data for 5 sample(s) Mantle Cell Lymphoma from venous blood, on Genome GRCh38. 5 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002918

• Single-cell profiling of co-cultures of GSCCs and macrophages

  This dataset contains scRNA-seq data from 8 co-cultures of GSCCs and macrophages, and 1 monoculture of macrophages. Samples were individually labeled and pooled using MULTI-seq technology and processed with 10x Genomics Technology.

  Dataset EGAD00001011275

• siRNA knockdown of Allelic Imbalance target TFs followed by mRNA-seq

  siRNA knockdown of 43 Allelic Imbalance target TFs followed by mRNA-seq done in triplicates in three (GP5D, LoVo, COLO320DM) different cell colorectal adenocarcinoma cell lines.

  Dataset EGAD00001004098

• COVID-19 Postmortem Lung snRNA-seq

  A deeper understanding of the pathological mechanisms of SARS-CoV-2 infection is required to combat COVID-19. Through this dataset, we analyze postmortem lung cells from patients that are infected/uninfected with SARS-CoV-2 with snRNA-seq.

  Dataset EGAD00001006584

• Gene expression adaptation of metastases to their host tissue

  The adaptation of metastatic cells to their host tissue critically determines the pathogenicity of a cancer and therefore patient survival. Yet, it remains elusive to what extent the host environment drives gene expression programs in metastatic cells. Here we identify adaptive mechanisms that enable metastases to establish themselves in a novel tissue context. We performed single-cell RNA-sequencing on malignant and benign tissue samples from untreated donors with colorectal adenocarcinoma and liver metastasis to deduce tissue adaptive expression patterns. A novel computational approach identified genes and pathways that consistently adapted to the host tissue at the transition from the primary tumor to the paired metastasis across donors. This analysis revealed that the majority of expression changes in the metastasis reflect an expression signature reminiscent of benign liver epithelial cells. Cellular processes adapting to the liver environment include basic cellular functions such as energy metabolism, as well as tissue-specific pathways such as the regulation of lipid metabolism by PPAR-α. These adaptations potentially increase the pathogenicity of the metastatic cells and may provide new therapeutic strategies.

  Study EGAS50000000817

• Mesenchymal inflammation drives genotoxic stress in hematopoietic stem cells and predicts disease evolution in human pre-leukemia

  Mesenchymal niche cells may drive tissue failure and malignant transformation in the hematopoietic system but the molecular mechanisms and their relevance to human disease remain poorly defined. We demonstrated that perturbation of mesenchymal cells in a mouse model of the preleukemic disorder Shwachman-Diamond syndrome induces mitochondrial dysfunction, oxidative stress and activation of DNA damage responses in hematopoietic stem and progenitor cells. In this study we demonstrate, through massive parallel RNA sequencing of highly purified mesenchymal cells in a range of human preleukemic syndromes, TP53-S100A8/9-TLR4 inflammatory signaling as a common driving mechanism of genotoxic stress, which could be attenuated by TLR4 blockade. S100A8/9 expression in mesenchymal cells predicted outcome in myelodysplastic syndromes, the principal human preleukemic condition, independent of known prognostic variables. Collectively, findings reveal a concept of mesenchymal niche-induced genotoxic stress in heterotypic stem and progenitor cells through inflammatory signaling as an actionable determinant of disease outcome in human preleukemia. The data further provide novel conceptual and mechanistic insights into the intimate link between inflammation and cancer.

  Study EGAS00001001926

• 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 involvement of lncRNAs in mediating MYC’s function. Here we have intersected RNA-sequencing data from MYC-inducible cell lines, from a cohort of 91 mature B-cell lymphomas and from sorted germinal-center B-cells. By this approach, we identified 13 lncRNAs differentially expressed in IG-MYC-positive Burkitt lymphoma and regulated by MYC in the model cell lines. Among them we focused on a lncRNA that we named MINCR, showing a strong correlation with MYC expression in MYC-positive lymphomas and in pancreatic ductal adenocarcinomas. RNAi experiments showed that MINCR controls cellular viability by influencing the expression of MYC-regulated 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 acts as a modulator of MYC transcriptional control of cell cycle genes.

  Study EGAS00001001199

• Extensive three-dimensional intratumor proteomic heterogeneity revealed by multiregion sampling in high-grade serous ovarian tumor specimens

  Enriched tumor epithelium, tumor-associated stroma, and whole tissue were collected by laser microdissection from thin sections across spatially separated levels of ten high-grade serous ovarian carcinomas (HGSOCs) and analyzed by mass spectrometry, reverse phase protein arrays, and RNA sequencing. Unsupervised analyses of protein abundance data revealed independent clustering of an enriched stroma and enriched tumor epithelium, with whole tumor tissue clustering driven by overall tumor “purity.” Comparing these data to previously defined prognostic HGSOC molecular subtypes revealed protein and transcript expression from tumor epithelium correlated with the differentiated subtype, whereas stromal proteins (and transcripts) correlated with the mesenchymal subtype. Protein and transcript abundance in the tumor epithelium and stroma exhibited decreased correlation in samples collected just hundreds of microns apart. These data reveal substantial tumor microenvironment protein heterogeneity that directly bears on prognostic signatures, biomarker discovery, and cancer pathophysiology and underscore the need to enrich cellular subpopulations for expression profiling. (Companion proteomic data is available in the ProteomeXchange Consortium, PRIDE: PXD026570).

  Study EGAS00001005786