15075 results for "cancer studies using rna-seq"

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• Transfer Learning Associates CAFs with EMT and Inflammation in Tumor Cells in Human Tumors and Organoid Co-Culture in Pancreatic Ductal Adenocarcinoma

  This study examined the transcriptional changes induced by cancer associated fibroblasts (CAFs) in pancreatic ductal adenocarcinoma patient-derived tumor organoids. We hypothesized that cancer associated fibroblasts impacted tumor cell transcription to promote tumorigenic behavior. Using patient-matched cells from 3 patients, we compared the transcriptional profiles of patient-derived organoids in monoculture to patient-derived organoids co-cultured with CAFs. Similarly, we looked at the transcriptional changes in matched patient-derived cancer associated fibroblasts grown in monoculture or co-cultured with patient-derived organoids. With a focus on intercellular crosstalk, we identified crosstalk between cancer associated fibroblasts and patient-derived organoids through VEGFA and NRP1. This was identified by bulk RNA sequencing and examined dynamically in organoid-CAF co-culture. This dbGaP deposit is the bulk RNA sequencing data for these 3 patients.

  Study phs003563

• Single-cell transcriptomic analyses of peripheral blood mononuclear cells from patients with colorectal cancer metastasized to the peritoneum

  The data published here contains single-cell RNA-sequencing (scRNAseq) data as obtained using the 3' scRNAseq using Chromium Single Cell 3’ Reagent from 10X Genomics on peripheral blood mononuclear cells (PBMC) from patients with colorectal cancer (CRC) and peritoneal metastases (PM). Sequencing was performed in a paired-ended fashion on the NovaSeq6000.

  Dataset EGAD50000000247

• Exploring the heterogeneity of sarcoma using single cell sequencing

  Multi region samples are collected from patients, with consent, immediately after resection of the tumour. Samples are digested and sorted using FACS as single cells into lysis buffer. Cells are then stored until further processing for G&T-seq. After sequencing, we will explore intra-tumour heterogeneity using computational approaches to integrate RNA and DNA data onto the tumour phylogeny This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ .

  Dataset EGAD00001006786

• Single-cell transcriptomic analyses of peripheral blood mononuclear cells, peritoneal fluid, and peritoneal metastases from patients with colorectal cancer

  The data published here contains single-cell RNA- sequencing (scRNAseq) on peripheral blood mononuclear cells (PBMC), peritoneal fluid (PF), and peritoneal metastases (PM). PBMC, PF and, where possible, PM was acquired from patients with colorectal cancer (CRC) and subjected to 3' scRNAseq using the 10X Genomics (Chromium Single Cell 3’ Reagent). Sequencing was performed in a paired-ended fashion on either the HiSeq4000 or the NovaSeq6000.

  Study EGAS50000000173

• CASCADE tumour transcriptome data

  RNA-Seq data from 20 fresh-frozen postmortem samples from three patients who participated in the CASCADE rapid autopsy program and died of metastatic castration resistant prostate cancer.

  Dataset EGAD00001009492

• Kidney Two-Hit Mapping

  Germ-line genetic variants identified thus far generally account for only part of the genetic risk predicted for most cancers. A component of the remaining risk may be explained by functionally consequent genetic variants that are individually very rare (or private to that individual's family). While their identification may be highly informative for cancer etiology and biological knowledge, strategies that allow for agnostic (genome-wide) identification of such genes are not straight forward. This is particularly true for rare cancers where sufficient numbers of patients may simply not be available for appropriate statistically powered studies. In this project we have explored a study design based around the concept of "two-hit mapping" using the co-occurrence of germ-line and somatic mutations in the same gene to assist in the identification of susceptibility genes. The dataset includes 54 kidney cancer patients selected for enrichment of genetic disease, that is patients with: early age of onset and/or family history and/or bilateral disease. Germ-line and somatic (kidney cancer) tumor sequencing was carried out. These data may improve our understanding of kidney cancer.

  Study phs001971

• BLUEPRINT EpiVar RNA-seq for Naive naive CD4+ T-cells

  BLUEPRINT EpiVar RNA-seq for Naive naive CD4+ T-cells

  Study EGAS00001000752

• Asian Immune Diversity Atlas (AIDA) sQTL

  Current efforts within the Human Cell Atlas (HCA) are largely focused on defining reference human cell types using a relatively small number of samples of predominantly European origin. However, the next phase of the HCA is likely to address the topic of human diversity by comprehensively characterizing variation in cell states across age, sex, population groups, diseases and environments. To spur this next phase, and also expand the geographical scope of the HCA, we propose an HCA-Asia seed network to generate an Asian Immune Diversity Atlas (AIDA). AIDA will generate transcriptome variation datasets from 5 major Asian population groups (Chinese, Japanese, Korean, Indian, Malay), define an atlas of Asian cell types and states, and characterize their variation associated with ethnicity, age and sex. We will also formalize a study design based on common controls that can in principle reduce technical artifacts in a broad range of comparative single cell studies. This study design will be complemented with novel algorithms designed to normalize datasets of interest against the common controls, to increase the robustness of biological inferences. In addition to providing new tools and resources to the HCA, this seed network will serve as a template for future comparative studies in the single cell field.The AIDA dataset consists of scRNA-seq (10x 5′ v2 scRNA-seq) and genotype (Illumina Infinium Global Screening Array v.3) data. In the AIDA splicing quantitative trait loci (sQTL) project, we identified 11,577 independent cis-sQTLs, 607 trans-sQTLs, and 107 dynamic sQTLs. The post-imputation genotype for the Japanese and Korean cohort will be available through dbGaP. The Singaporean (ethnically Chinese, Indian and Malay) genotypes require a data access application to the HELIOS Data Access Committee (helios_science@ntu.edu.sg). European samples are used as control.

  Study phs003848

• Single cell transcriptomics of hESC-derived midbrain dopaminergic neurons generated by a new human development-based protocol

  Single cell RNA-seq from D0,D11,D16,D21,D28 of dopamingeric differentiation from hESCs cell lines H9 and HS980 using current protocols. Different time points along the differentiation for each cell line were multiplexed using BD™ Single-Cell Multiplexing Kit for use with the 10x Chromium™ Single Cell 3’ Reagent Kit v2.

  Dataset EGAD00001008834

• Leiomyosarcoma Cancer Transcriptome Sequencing

  RNA-Seq data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 78 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 75bp paired-end protocol to a minimum mean reads of 50 million.

  Dataset EGAD00001003192