12214 results for "cancer rna-seq"

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• RNA-Seq datasets in human islets cultured in low glucose conditions

  7 RNA-Seq datasets in human pancreatic islets from 7 donors, where islets were using low (4mM) glucose conditions.

  Dataset EGAD00001005208

• Human tumour bulk RNA-seq

  We profiled 18 high-grade gliomas patient tumor samples by bulk RNA-seq. The raw fastqs are provided.

  Dataset EGAD00001006098

• Smart-seq2 single-cell RNA-seq of human liver non-parenchymal cells

  Smart-seq2 single-cell RNA-seq of human liver non-parenchymal cells from lean and obese individuals

  Dataset EGAD00001010301

• RNA-Seq of pancreatic neuroendocrine tumors mutated in MEN1/DAXX/ ATRX

  RNA-Seq of of 11 primary pancreatic neuroendocrine tumors mutated in MEN1/DAXX/ ATRX used to identify molecular subtypes

  Dataset EGAD00001015695

• RNA-seq as a tool for evaluating human embryo competence

  The majority of embryos that are created through IVF do not implant. It seems plausible that rates of implantation would improve if we had a better understanding of molecular factors affecting embryo competence. Currently, the process of selecting an embryo for uterine transfer utilizes an ad-hoc combination of morphological criteria, the kinetics of development, and genetic testing for aneuploidy. However, no single criterion can ensure selection of a viable embryo. In contrast, RNA-sequencing of embryos could yield highly dimensional data, which may provide additional insight and illuminate the discrepancies among current selection criteria. Indeed, recent advances enabling the production of RNA-sequencing (RNA-seq) libraries from single cells have facilitated the application of this technique to the study of some transcriptional events in early human development. However, these studies have not assessed the quality of their constituent embryos relative to commonly used embryological criteria. Here, we perform proof-of-principle advancement to clinical selection procedures by generating high quality RNA-seq libraries from a trophectoderm biopsy as well as the remaining whole embryo. We combine state-of-the-art embryological methods with low-input RNA-seq to develop the first transcriptome-wide approach for use in future predictive embryology studies. Specifically, we demonstrate the capacity of RNA-seq as a promising tool in preimplantation screening by showing that biopsies of an embryo can capture valuable information content available in the whole embryo from which they are derived. Furthermore, we show that this technique can be used to generate a RNA-based digital karyotype, and to identify candidate competence-associated genes. Together, these data establish the foundation for a future RNA-based diagnostic in IVF.

  Dataset EGAD00001005044

• CPTAC: Molecular Dissection of Chemotherapy Response in Triple Negative Breast Cancer

  Sporadic Triple Negative Breast Cancer (TNBC) represents 10-15% of breast cancers (BC) worldwide. Non-specific chemotherapy remains the standard of care as there are no targeted agents. In 50% of cases, pathological complete response (pCR) is not achieved, and these individuals experience poor survival. Predictive markers for chemotherapy have proved elusive, and patients can receive up to five different chemotherapy agents to optimize outcomes. Microscaled proteogenomics (PMID: 31988290) is a discovery technique that integrates DNA and RNA sequencing with mass spectrometry based proteomics. This approach was applied to snap-frozen biopsies obtained before TNBC treatment on a clinical trial of carboplatin and docetaxel. Proteogenomic profiling included whole exome sequencing (WES), RNA-seq, and tandem mass tag based proteomics and phosphoproteomics.The study was approved by the IRB at both participating sites: Washington University in St. Louis and Baylor College of Medicine (BCM), and followed the Declaration of Helsinki and Good Clinical Practice guidelines. The protocol and informed consent documents were approved by Washington University School of Medicine (WUSM) and BCM.

  Study phs002505

• Comparison Between qPCR and RNA-Seq Reveals Challenges of Quantifying HLA Expression

  Human leukocyte antigen (HLA) class I and HLA class II loci are essential elements of innate and acquired immunity. Their exceptional influence on disease outcome is well documented by GWAS and candidate gene studies. The impact of HLA allelic variation on human disease through allele-specific presentation of antigenic peptides to T cells has been the main focus to determine HLA effects on disease susceptibility/pathogenesis. However, HLA expression levels have also been implicated in disease, adding another dimension to the extreme diversity of HLA that impacts variability in immune responses across individuals. HLA expression levels routinely rely on quantitative PCR (qPCR). An alternative is adoption of high throughput technologies such as RNA-Seq. This provides the opportunity to quantify HLA expression in large datasets, but also allows comparison between RNA-Seq and qPCR. In this study, we analyze expression data for HLA Class I genes for a matched set of individuals (N = 96) by RNA-Seq, qPCR and cell surface expression. Samples were obtained from the Research Donor Program (NCI-Frederick). We observed a moderate correlation between RNA-Seq and qPCR. We suggest technical and biological factors that might contribute to differences in the techniques.

  Study phs003177

• Single cell sequencing of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis

  The quantity of tumor infiltrating lymphocytes (TILs) in breast cancer (BC) is a robust prognostic factor for improved patient survival particularly in triple negative and HER2-overexpressing BC subtypes. Whilst T cells are the predominant TIL population, the relationship between quantitative and qualitative differences in T cell subpopulations and patient prognosis remains unknown. We performed single-cell RNA sequencing (scRNA-seq) of 6311 T cells isolated from human BCs, and show for the first time that significant heterogeneity exists in the infiltrating T cell population. We demonstrated that high TIL BCs contained significant numbers of CD8+ T cells with features of tissue-resident memory T (TRM) cell differentiation and that these CD8+ TRM cells expressed high levels of immune checkpoint molecules and effector proteins. A CD8+ TRM gene signature developed from the scRNA-seq data was significantly associated with improved patient survival in early-stage triple negative breast cancer (TNBC) and provided better prognostication compared with CD8 expression alone. Our data suggests that CD8+ TRM contribute to BC immunosurveillance and are the key targets of modulation through immune checkpoint inhibition. Further understanding of the development, maintenance and regulation of TRM cells will be crucial for successful immunotherapeutic development in BC.

  Study EGAS00001002845

• Reference Epigenomes and Regulatory Landscape of CLL

  Analysis of the reference epigenomes and regulatory landscape of CLL as a whole and its major clinico-biological subtypes (with mutated and unmutated IGHV) in the light of the normal B-cell differentiation. We have extensively characterized the reference epigenomes of seven primary chronic lymphocytic leukemia samples (CLLs) with mutated (n=5) and unmutated IGHV (n=2) as well as several mature B-cell subpopulations (naive B cells from blood and tonsil, germinal center B cells, memory B cells and plasma cells from tonsil) using genome-wide maps of six histone marks (H3K4me3, H3K4me1, H3K27ac, H3K36me3, H3K9me3 and H3K27me3), DNA accessibility (ATAC-seq), DNA methylation (whole-genome bisulfite sequencing) and gene expression (RNA-seq). Furthermore, we have mapped the regulatory chromatin landscape of 100 additional CLL cases using chIP-seq of H3K27ac and ATAC-seq and linked these data to additional layers of information (whole-genome and/or whole-exome sequencing (WGS/WES), RNA-seq and DNA methylation microarrays) studied in the context of the International Cancer Genome Consortium (ICGC).

  Dataset EGAD00001004046

• Single-cell RNA and ATAC sequencing data analysis of human postmenopausal fallopian tube and ovary

  In this study, we used a combination of technologies, including Drop-seq, 10X single-cell RNA-seq (scRNA-seq), and single-cell assay on transposase accessible chromatin (scATAC-seq) to generate  a high-quality cell atlas that consists of four tissue sites from the reproductive tract of postmenopausal women. This atlas, by far the most comprehensive map of the postmenopausal female reproductive system to date, will pave the way to a better understanding of the pathophysiology of many diseases affecting older women.

  Study EGAS00001006780