7193 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

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• BLUEPRINT Epigenetic characterization of megakaryocytes and erythroblasts

  Megakaryocytes and erythroblasts derive from the same progenitor cell type but carry out very different functions. In order to understand how the different functional phenotypes arise we have characterised the epigenetic landscape of these cells.

  Dataset EGAD00001001871

• BBMRI - BIOS project - Freeze 1 - Bam files

  BBMRI - BIOS project - Freeze 1 - Bam files

  Dataset EGAD00001001623

• BBMRI - BIOS project - Freeze 1 - Fastq files

  BBMRI - BIOS project - Freeze 1 - Fastq files

  Dataset EGAD00001001622

• EUROBATS RNAseq BAM files for the Skin samples

  RNAseq BAM files for the Skin samples of the EUROBATS project.

  Dataset EGAD00001001087

• RNA bam files of Renal Cell Carcinoma patients

  the dataset contains RNA bam files of Renal Cell Carcinoma patients, which belongs to "An Empirical Approach Leveraging Tumorgrafts to Dissect the Tumor Microenvironment in Renal Cell Carcinoma Identifies Missing Link to Prognostic Inflammatory Factors"

  Dataset EGAD00001003895

• 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

• Genomic Landscape of Chordoid Glioma

  This data set consist genomic information of 10 Chordoid Glioma samples: - Exome sequencing: 10 tumors and matched normal DNA for four of them (BAM files) - RNAseq : 10 tumors (fastq files) - CNV array: 9 tumors (IDAT files)

  Dataset EGAD00001004112

• Raw BulkRNA sequencing data

  BulkRNA sequencing Human Strand Specific mRNA (WOBI) 40M reads was performed by Novogene (Netherlands) using the NovaSeq X Plus Series (PE150, Q30≥85%) sequencing platform and strategy. 24 samples were included in the study, requiring 12 G of raw data per sample.

  Dataset EGAD50000001848

• CEBP-Beta/IL-1-Beta/ TNF-alpha Feedback Loop Drives Drug Resistance to BCL2 and MDM2 Inhibitors in Monocytic Leukemia Cells

  To uncover the mechanisms of MDM2 inhibitor resistance that are mediated by IL-1, we performed RNAseq on three primary AML patient cells treated with idasanutlin in the presence or absence of IL-1β. These three leukemia samples were chosen because they exhibit high blast counts and are protected by IL-1β when treated with idasanutlin, as determined by apoptosis assay. We observed that a majority of the major p53 pathway targets remained upregulated in the presence of IL-1β. We next performed differential expressed gene (DEG) analysis following IL-1β treatment with and without idasanutlin. IL-1β treatment upregulated 3295, 1353, and 680 genes with ≥1 Log2FC, in each of the three patient samples, and a significant majority of these genes (82%, 62.4%, and 47.6%) remained upregulated in the presence of idasanutlin. Pathway analysis showed that IL-1β upregulated genes were associated with NF-κB, Interleukin-1 family signaling pathways, immune and inflammatory associated genes and myeloid maturation markers. To identify downstream targets that contribute to the protective effect of IL-1β during idasanutlin treatment, we performed DEG analysis on IL-1β + idasanutlin treatment compared to idasanutlin treatment alone. Interestingly, IL-1β induces its own expression and other pro-survival cytokines including TNF, CSF2 (GMCSF), IL-6, CSF3 (GCSF), as well as their respective receptors and/or coactivators, including IL1RL1 and multiple TNF receptors. We verified that IL-1β and TNF-α induce the upregulation of their own membrane-bound forms, their corresponding receptors, CSF2RB, and monocytic markers, as determined by flow cytometry immunophenotyping. Furthermore, IL-1β upregulated a number of pro-inflammatory chemokines, including CXCL13, CXCL2, etc. These findings highlight a pleiotropic role of IL-1β. The RNA expression of these three samples in the presence and absence of IL-1β and idasanutlin treatment will be deposited in dbGaP.

  Study phs003479

• Whole exome and RNA sequencing of organoid samples derived from TRACERx patients

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘hot’) and non-evading (‘cold’) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008092