9338 results for "cancer rna-seq"

in 94.16 milliseconds.

• Single-cell RNA-seq of bronchoalveolar lavage (BAL) fluid in severe COVID-19 and SARS-CoV-2 stimulated classical blood monocytes

  We analyzed pulmonary monocyte and macrophage responses as well as and pulmonary pathology in two cohorts of patients with COVID-19 associated ARDS. Monocyte-derived macrophages accumulated in the lung during ARDS and acquired a profibrotic signature, characterized by high expression of known fibrogenic factors like TGFB1, SPP1 and LGMN. COVID-19 associated macrophages showed highly significant transcriptional similarity with profibrotic macrophage populations identified in idiopathic pulmonary fibrosis (IPF). Notably, overnight exposure to SARS-CoV-2, but not influenza A virus or viral RNA analogues, induced a similar phenotype in human monocytes from healthy volunteers in vitro. Patients with severe COVID-19 associated ARDS showed clear clinical, radiographic and histopathological features of scarring and fibrotic tissue remodeling. In conclusion, SARS-CoV-2 triggers profibrotic macrophage responses, fibroproliferative ARDS, and lung fibrosis

  Study EGAS00001004928

• scRNA-seq, scTCR-seq and scBCR-seq of 21 individuals post Covid'19 vaccination.

  This data includes scRNA-seq, scTCR-seq and scBCR-seq of 21 individuals post Covid'19 vaccination. Individuals range from the ages 52 to 75. Samples were genotype multiplexed in an overlapping mixture design, pooled, and sequenced on 16 lanes (10X, 5' GEM).

  Dataset EGAD00001011201

• Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes

  Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. Since 2007, common genetic variants in ~200 loci have been identified in genome-wide association studies (GWAS) in relation to breast cancer risk. However, it is often difficult to translate GWAS findings to disease prevention and treatment since causal genes in the large majority of GWAS-identified loci are unknown. Furthermore, a large fraction of breast cancer heritability remains unexplained. Recent studies suggest that nearly 80% of disease heritability can be explained by genetic variants regulating gene expression. Herein, we propose three well-powered transcriptome-wide association studies (TWAS) to systematically investigate the association of breast cancer risk with gene expression across the transcriptome of African, Asian and European descendants. In Aim 1, we will perform RNA sequencing and high-density genotyping assays using normal breast tissue samples, and build race-specific gene expression prediction models using data from 1000 women of African, Asian and European descent. These models will be applied to the GWAS data generated from approximately 320,000 breast cancer patients and controls to impute gene expression for association analyses of predicted gene expression with risk of breast cancer overall, and by estrogen receptor and HER2 status. In Aim 2, we will select the top 50 genes identified in Aim 1 for in vitro functional assays to assess their influence on major cell functions related to cancer biology. In Aim 3, we will evaluate whether TWAS-identified genes may express differently in normal breast tissues and breast cancer tissues collected from African, Asian, and European descendants to assess whether these genes may contribute to racial differences in breast cancer risk by molecular subtypes. With strong methodology and a large sample size, we believe that this proposed study should be able to identify and characterize a large number of novel genes related to breast cancer risk. Uncovering breast cancer susceptibility genes will greatly improve the understanding of the genetic and biological basis for breast cancer and accelerate the translation of genetic findings to disease prevention and patient care.

  Study phs003535

• The impact of mutational clonality in predicting the response to anti-PD-L1/PD-L1 in advanced urothelial cancer

  The advent of immune checkpoint inhibitors (ICI) has radically changed the management and therapeutic treatment landscape for patients with cancer. It has been shown that the use of these inhibitors can result in long-term complete remissions even in cases with advanced stages of the disease. However, only a small fraction of patients respond to the treatment. A better understanding of which factors could drive this clinical benefit is fundamental to building more accurate predictive biomarkers and developing alternative therapeutic options for patients who are unlikely to benefit. In order to address this issue, we have generated and analyzed whole exome sequencing (WES) and RNA sequencing (RNASeq) data from a cohort of metastatic urothelial carcinoma patients (N = 27) treated with ICI such as anti-PD-(L)1 monoclonal antibodies.

  Study EGAS00001007086

• Integrative analysis of exome-seq, RNA-seq, ATAC-seq (bulk and single-cell), and Hi-C data generated from 3-D spatially mapped samples acquired during surgical resection from 10 patients diagnosed with IDH-WT glioblastoma

  Glioblastoma (GBM), the most common primary brain cancer in adults, remains incurable with no targeted therapies approved despite decades of investigation into its molecular landscape. Treatment failure is attributed to intratumoral heterogeneity in the GBM genome and epigenome, which foster tumor evolution and selection of resistant clones. However, tumor evolution and intratumoral heterogeneity remain poorly understood on the level of the whole tumor as most studies are based on single samples per patient and lack spatial context. Here, we have used 3-D neuronavigation during surgical resection for 10 primary IDH-WT GBM patients to collect 102 samples representing maximal tumor diversity, each mapped by 3-D spatial coordinates. We have applied a strategic set of genomic and epigenomic assays spanning multiple levels of resolution to discover, orthogonally validate, and functionally assess drivers of tumor evolution and intratumoral heterogeneity. These include extrachromosomal DNA amplifications, chromothripsis events, inversions, and translocations that disrupt both the GBM genome and epigenome while generating fusion transcripts and opportunities for therapeutic intervention. We define epigenomic programs that contribute to GBM evolution and intratumoral heterogeneity, revealing their 3-D spatial patterning within whole tumors and their cell type(s) of origin in single-cell data from the same tumor samples. Notably, we distinguish neuronal, glial, and immune programs aberrantly active in tumor cells from their counterparts in normal cells and discover NEUROD1, JUN/FOS, and NF1 transcription factors as key drivers of GBM evolution and growth. Collectively, these data provide unprecedented insight into GBM evolution and intratumoral heterogeneity from single-cell to whole-tumor resolution, redefining current understanding and providing a rich resource of targets for therapeutic investigation.

  Study EGAS00001006785

• Single cell and plasma RNA sequencing

  Single cell and plasma RNA sequencing for RNA liquid biopsy for hepatocellular carcinoma

  Study EGAS00001005194

• RNA-seq data from 224 advanced prostate tumors generated by the West Coast Dream Team

  224 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node.

  Dataset EGAD00001008487

• RNA-seq data from 164 advanced prostate tumors generated by the West Coast Dream Team including 42 paired samles

  164 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node. 42 pairs prior to enzalutamide treatment and at progression from 21 patients are included.

  Dataset EGAD00001009065

• Dataset Plasma-seq

  We performed low coverage whole genome sequencing of plasma DNA from prostate cancer patients to establish copy number profiles on both a genome-wide and a gene-specific level. The data include plasma samples from prostate cacner patients (n=13), non-malignant controls (males, n=10 and females, n=9), plasma samples from pregnancies with aneuploid and euploid fetuses (n=4). Furthermore, we sequenced different tumor samples (n=6) of one patients and a serial dilution of HT29 in a background of normal DNA (n=9).

  Dataset EGAD00001000364

• Detection of ctDNA in Plasma of Patients with Clinically Localised Prostate Cancer is Associated with Rapid Disease Progression

  Whole genome sequencing of tumour-normal pairs in eight patients with clinically localised disease undergoing prostatectomy. A bespoke DNA capture and amplification panel against the highest prevalence, highest confidence aberrations for each individual was designed and used to interrogate ctDNA isolated from plasma prospectively obtained pre- and post- (24 hours and 6 weeks) surgery. Tagged-amplicon deep sequencing (TAm-Seq) across the TP53 gene in ctDNA in a cohort of 189 individuals.

  Dataset EGAD00001006369