11801 results for "cancer rna-seq"

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• Reference epigenome IPS01_N_Fibroblast_mRNA-Seq data generated from KEP study

  A IPS01_N_Fibroblast_mRNA-Seq paired end data for iPSC(Oct4)

  Dataset EGAD00001003488

• STAG1-ChIP-Seq of STAG2-mutated and cohesin wildtype adult AMLs

  ChIPseq targeting the cohesin subunit STAG1 in STAG2-mutated AMLs or cohesin wildtype AMLs

  Dataset EGAD00001011206

• Reference epigenome IPS04_X_Fibroblast_smRNA-Seq data generated from KEP study

  A IPS04_X_Fibroblast_smRNA-Seq single end data for iPSC(Oct4)

  Dataset EGAD00001003504

• ATAC-Seq datasets in human islets

  13 ATAC-Seq datasets of human pancreatic islets from 13 donors

  Dataset EGAD00001005201

• RNA Fusion Panel

  RNA extracted from FFPE tumour samples 368, 455, 503, and 521, sequenced using the TruSight RNA Fusion Panel

  Dataset EGAD50000000272

• 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

• Whole genome sequencing of adult glioblastoma nuclei

  Nuclei were extracted from three primary adult glioblastoma samples and processed for scATAC-seq, and residual nuclei left over from these same samples were used to extract DNA and processed and sequenced for WGS. This WGS data was then used to cross-validate assessment of large-scale copy number alterations with scATAC-seq using the Copy-scAT tool.

  Study EGAS00001005256