10146 results for "cancer rna-seq"

in 29.20 milliseconds.

• WES, sWGS and RNA-seq of Asian breast cancer

  The dataset contains a full genomics characterization of 527 Asian breast tumours. This includes whole-exome sequencing of tumour tissue at 80X, whole-exome sequencing of matched normal (blood) tissue at 40X, shallow-whole genome sequencing at 0.1X for copy number analyses, and RNA-seq of tumour tissue at 40X coverage (>15 million reads). Whole-exome libraries were prepared using the Nextera Rapid Capture Exome Kit; exome capture was performed in pools of 3 and subjected to paired end 75 sequencing on a HiSEQ4000 platform. RNA libraries were prepared using the TruSeq Stranded Total RNA HT kit with Ribo-Zero Gold as per manufacturer’s instructions and also subjected to paired end 75 sequencing on a HiSEQ4000 platform. Uploaded bam files have been mapped to the hs37d5 human genome and processed using the standard GATK pipelines. Paired clinical, demographic, genotyping, and overall survival data for these patients are available from the associated publications or by request.

  Dataset EGAD00001006399

• SF11979 scRNA-Seq Primary GBM IDHR132H Wild-type Female

  Single Cell-RNA Seq IDHR132H Wild-type Primary GBM Female, 76. Single Cell RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through cellranger count (10xGenomics.)

  Dataset EGAD00001005390

• SF11977 scRNA-Seq Primary GBM IDHR132H Wildtype Female

  SF11977 single cell RNA-seq IDHR132H Wild-type GBM Female, 61 Single Cell RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

  Dataset EGAD00001005391

• SF11964 scRNA-Seq Low Grade Glioma IDHR132H mutant Male

  Single cell RNA-Seq Low Grade Astrocytoma IDHR132H mutant. Male, 64. Single Cell RNA seq from primary astrocytoma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

  Dataset EGAD00001005396

• RNA-seq, ChIP-seq, ATAC-seq files for PCGP SJERG

  RNA-seq, ChIP-seq, and ATAC-seq files for PCGP SJERG paper titled "Deregulation of DUX4 and ERG in acute lymphoblastic leukemia"

  Dataset EGAD00001002681

• Lung Adenocarcinoma Promotion by Air Pollutants

  A complete understanding of how environmental carcinogenic exposures promote cancer formation is lacking. Over 70 years ago, tumour formation was proposed to occur in a two step process: an initiating step which induces mutations in normal tissue, followed by a promoter step which triggers cancer development. Recent evidence has revealed healthy human tissue contains a patchwork of clones harbouring oncogenic mutations.This led us to hypothesise that environmental particulate matter measuring PM2.5, known to be associated with lung cancer risk, might promote lung cancer by acting on pre-existing cells harbouring oncogenic mutations in normal lung tissue. Here we use a combination of WGS and RNA-seq of mouse tumours from pollution-exposed mice to examine the impact of particulate matter on mutagenesis and gene expression respectively.

  Study EGAS00001006951

• Heterogeneous metabolic signatures are linked to cancer cell differentiation in colorectal cancer

  Colorectal cancer (CRC) is characterized by functional intratumor heterogeneity that shares many similarites with the hierarchical organization of the normal intestinal epithelium. In order to relate transcriptional subtypes to functional tumor cell heterogeneity we applied scRNA-seq to 12 patient-derived CRC spheroid cultures. We identified shared expression programs that relate to intestinal lineages and revealed metabolic signatures that are linked to cancer cell differentiation. In addition, we validated and complemented sequencing results by quantitative microscopy using live-dyes and multiplexed RNA fluorescence in situ hybridization, thereby revealing metabolic compartmentalization and potential cell-cell interactions. FInally, we demonstrate functional differences between metabolically distinct lineage subtypes that might have strong implications for future treatment strategies of CRC.

  Study EGAS00001004064

• RNAseq from 6 organotypic co-cultures (OC cells bulk/OCSC with or without TME)

  The dataset contains samples of 6 organotypic co-cultures, assembled with patient-derived material from ovarian cancer (OC) patients. Tumor cells, both as bulk and as cancer stem cells-enriched (OCSC) populations, are cultured or not with in vitro peritoneal TME (for details see Battistini C et al, Tumor microenvironment-induced FOXM1 regulates ovarian cancer stemness, CDDis 2024). Dataset is composed by fastq file (paired end) type from bulk RNA-Seq.

  Dataset EGAD50000000523

• BELOB: Ribo-minus RNA-seq data corresponding to 96x GBM samples from the BELOB trial.

  Ribo-minus RNA-seq data corresponding to 96x GBM samples from the BELOB trial.

  Study EGAS00001004570

• Bulk and single cell RNA-seq analysis of keratinocytes and human skin

  106 bulk RNA-seq samples of primary human keratinocytes 8 single cell RNA-seq samples of human epidermis

  Dataset EGAD00001005998