15016 results for "cancer studies using rna-seq"

in 24.43 milliseconds.

• High-throughput 3D engineered paediatric tumour models for precision medicine

  Paired fastqs for DNA and RNA from Illumina TSO500 targeted sequencing from PDX.

  Dataset EGAD00001015753

• Carcinoid study - RNASeq dataset

  Fernandez-Cuesta et al, 2014, Nature Communication, RNA Sequencing data set

  Dataset EGAD00001000795

• SNF_RNAseq_CD138p_20

  TPM matrices of counts from RNA sequencing (RNAseq) from baseline CD138+ enriched BM fractions.

  Dataset EGAD00001011148

• TXT_CD138P_15

  TPM matrices of counts from RNA sequencing (RNAseq) from longitudinal CD138+ enriched BM fractions.

  Dataset EGAD00001011144

• Phylogenetic reconstruction of breast cancer

  The aim of this study was to identify the evolutionary trajectories of metastatic breast cancer. We present whole genome sequencing data (primary tumours, axillary lymph nodes, distant metastasis and matched normal tissues) from 16 breast cancer patients. This work sheds light on the routes on which tumour cells metastasize and their role in disease progression in ER-positive breast cancer.

  Study EGAS00001004356

• whole-genome sequencing of gastric cancer

  Gastric cancer is one of the most common cancers. Genome-wide analysis of genomic signatures might reveal novel mechanisms for gastric cancer tumorigenesis. Here, we analyzed structural variations and mutational signatures via whole-genome sequencing of 168 gastric cancer samples. Our data demonstrates diverse models of complex structural variations operative in GC, which lead to high-level amplification of oncogenes.

  Study EGAS00001003512

• LICA-CN project - 116 liver cancer cases

  LICA-CN project - 116 liver cancer cases

  Study EGAS00001002300

• Using iPSC-derived neurons to explore cellular phenotypes associated with schizophrenia Data Access Committee.

  Dac EGAC00001000870

• EGAD00010000508

  Matched control samples using SNP 6.0 Array

  Dataset EGAD00010000508

• UM_GWAS

  Genotype cases using Illumina HumanOmni5

  Dataset EGAD00010001463

• Sahel

  Sahel population study using 2.5M

  Dataset EGAD00010000943

• DNA methylation

  CASE AND CONTROL SAMPLES USING Infinium MethylationEPIC

  Dataset EGAD00010001805

• GEPs

  Gene Expression Profiles measured using Affymetrix HGU133plus2.0 Array

  Dataset EGAD00010002543

• SWEPIC_methylation_cases

  CASE SAMPLES methylation data using Illumina EPIC technology

  Dataset EGAD00010002639

• Lineage Plasticity and Immune Cell Heterogeneity Are Coordinately Dysregulated Through Changes in FOXA1 Expression in Bladder Cancers with Squamous Differentiation

  We performed whole exome sequencing (WES) of paired, macrodissected regions of urothelial carcinoma (UC), not otherwise specified (NOS-UC) and squamous differentiation (SqD) from 21 bladder tumors in which distinct and separable NOS-UC and SqD regions were present (total 42 exomes, in addition to matched normal exomes). Mean tumor mutational burden (TMB) was higher in the SqD versus the NOS-UC regions. Consistent with the higher TMB, the SqD regions also had a higher neoantigen burden than the patient-matched NOS-UC regions. The SqD regions also exhibited higher karyotypic complexity with a higher median ploidy relative to the paired NOS-UC regions. Phylogenetic analysis of the WES data confirmed that the morphologically distinct regions of all 21 tumors arose from a shared precursor with a median of 68 (range 16 – 852) non-synonymous mutations shared between the NOS-UC and SqD regions, and the overall data were indicative of early branched evolution. As whole exome sequencing did not identify a shared mutational alteration or genomic signature unique to the SqD or NOS-UC components, we therefore performed expression profiling of separable SqD and NOS-UC regions of 12 bladder tumors from the WES cohort with RNA quality sufficient for whole transcriptome RNA-sequencing (RNAseq, total of 24 regions). Based on centroid clustering analysis of expression data, all 12 regions of SqD were basal-squamous subtype based on the TCGA molecular classification schema. Notably, 8 of the NOS-UC regions were also basal-squamous subtype, with only four pairs exhibiting discordant transcriptional subtypes (three NOS-UC regions were luminal-infiltrated, one luminal-papillary). To better quantify differences in the transcriptional profiles of the paired NOS-UC and SqD regions, we used single sample gene set enrichment analysis (ssGSEA) to assess for enrichment of luminal or basal-squamous gene expression. ssGSEA analysis revealed that the SqD regions expressed higher levels of basal-squamous genes based on the BASE47 gene set and UPK/KRT gene sets; whereas the matched NOS-UC regions expressed higher levels of luminal genes. These differences in the levels of expression of basal and luminal genes were observed even in cases in which both the NOS-UC and SqD regions were basal-squamous subtype based the TCGA molecular classification schema. Exomes from eight patients in this study have previously been deposited in dbGaP: accession number phs001783 as part of the study "Exome Recapture and Sequencing of Prospectively Characterized Clinical Specimens From Cancer Patients".

  Study phs002357