12215 results for "cancer rna-seq"

in 24.82 milliseconds.

• WGS and RNA-Seq data from a GBM patient PT-MB9777

  WGS and RNA-Seq data from a GBM patient PT-MB9777

  Dataset EGAD00001004253

• WGS and RNA-Seq data from a GBM patient PT-MD9088

  WGS and RNA-Seq data from a GBM patient PT-MD9088

  Dataset EGAD00001004254

• WGS and RNA-Seq data from a GBM patient PT-RD1291

  WGS and RNA-Seq data from a GBM patient PT-RD1291

  Dataset EGAD00001004256

• WGS and RNA-Seq data from a GBM patient PT-PD6881

  WGS and RNA-Seq data from a GBM patient PT-PD6881

  Dataset EGAD00001004255

• WGS and RNA-Seq data from a GBM patient PT-GC1519

  WGS and RNA-Seq data from a GBM patient PT-GC1519

  Dataset EGAD00001004239

• WGS and RNA-Seq data from a GBM patient PT-GJ3716

  WGS and RNA-Seq data from a GBM patient PT-GJ3716

  Dataset EGAD00001004240

• WGS and RNA-Seq data from a GBM patient PT-HO0394

  WGS and RNA-Seq data from a GBM patient PT-HO0394

  Dataset EGAD00001004243

• WGS and RNA-Seq data from a GBM patient PT-VO7089

  WGS and RNA-Seq data from a GBM patient PT-VO7089

  Dataset EGAD00001004263

• WGS and RNA-Seq data from a GBM patient PT-TM5196

  WGS and RNA-Seq data from a GBM patient PT-TM5196

  Dataset EGAD00001004262

• WGS and RNA-Seq data from a GBM patient PT-SK0976

  WGS and RNA-Seq data from a GBM patient PT-SK0976

  Dataset EGAD00001004260

• WGS and RNA-Seq data from a GBM patient PT-RW9277

  WGS and RNA-Seq data from a GBM patient PT-RW9277

  Dataset EGAD00001004259

• RNA seq of intestinal biopsies and blood cells from patients with celiac disease and controls

  This study presents RNA sequenced from several intestinal phenotypes such as from patients with damaged intestinal mucosa as well as from those without a damaged intestine but still an autoantibody response to tissue transglutaminase (“potential celiac disease”) or those with treated celiac disease. By combining phenotypes in a much larger number of tissue samples from both peripheral blood and mucosal biopsies, we found highly differentially expressed genes, but also identify genes involved in controlling and triggering celiac disease associated changes. This study identifies molecular mechanisms involved in celiac disease and new possible targets for treatment and for identification of individuals at risk.

  Study EGAS50000001104

• Hofer et al., A specific subpopulation of cancer-associated fibroblasts promotes resistance to chemotherapy in triple-negative breast cancer by upregulating G0S2 protein

  Chemotherapy is the standard of care for patients with triple-negative breast cancer (TNBC), but the mechanisms of chemoresistance remain poorly understood. Here, we investigated the role of cancer associated fibroblasts (CAFs) in the chemotherapy response of TNBC, by combining in vivo analyses of TNBC patients with ex vivo cancer modeling, using tumor-on-chip (ToC) technology. Transcriptomic analysis revealed that the proportion of a specific CAF population, the extracellular matrix-producing myofibroblasts (ECM-myCAFs), is reduced after chemotherapy in chemo-sensitive, but not in chemo-resistant TNBC patients. In ToC devices, primary ECM-myCAFs promoted TNBC cell survival under Doxorubicin and Paclitaxel treatment. The mechanism of chemoresistance was elucidated by using single-cell RNA sequencing, advanced cell imaging and functional assays: ECM-myCAFs upregulate the G0/G1 switch 2 (G0S2) protein in TNBC cells, via activation of SRC family kinases. Altogether, our work identifies G0S2 as a new player in CAF mediated chemotherapy resistance in TNBC.

  Study EGAS50000000886

• RNA sequencing and Illumina 2.5M SNP array data collected from 675 commonly used human cancer cell lines.

  Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic response1. Although substantial effort has been directed to defining the genomic constitution of cancer cell line panels2–4, the transcriptome – which represents the active program of a cell – remains understudied. Here, we describe RNA sequencing and SNP array analysis of 675 commonly used human cancer cell lines. We explore numerous transcriptome features including coding and non-coding gene expression, transcribed mutations, gene fusion and expression of non-human sequences. Aside from many known aberrations we find new surprising characteristics, including more than 2200 unique fusion gene pairs representing a vast, testable repertoire of oncogenic fusions, many of which have analogs found in primary human tumors. We show that a combination of multiple genome and transcriptome features in a novel pathway-based approach enhances prediction of response to various targeted therapeutics. Our results provide valuable new insights into these critical pre-clinical models and provide added context for interpreting the numerous studies that employ these widely used cell lines.

  Study EGAS00001000610

• IBD-dysplasia

  This data set concerns DNA copy number alterations and mutation data from 30 IBD-associated dysplastic lesions and 13 IBD-associated cancers. DNA was isolated from formalin-fixed, paraffin-embedded material. Whole-genome shallow seq and Truseq amplicon cancer panel (Illumina) were used for detection of DNA copy number alterations and gene mutations, respectively.

  Dataset EGAD00001005196

• Shallow whole genome sequencing from plasma DNA of BC, CRC and NSCLC patients

  This is the raw data obtained from shallow whole-genome sequencing of plasma DNA (plasma-Seq) for calling of somatic copy number alterations as well as focal amplifications and deletions from patients with breast, colorectal and non-small cell lung cancer.

  Dataset EGAD00001006288

• RNAseq of GEPARSIXTO

  294 formalin-fixed paraffin-embedded (FFPE) tissue samples were sent to the UNC Lineberger Comprehensive Cancer Center Translational Genomics Lab (TGL) for RNA isolation using the Maxwell 16 MDx Instrument (Promega AS3000) and the Maxwell 16 LEV RNA FFPE Kit (Promega AS1260) following the manufacturer’s protocol (Promega 9FB167). 279 total RNA sequencing libraries were prepared at TGL using a Bravo Automated Liquid-Handling Platform (Agilent G5562A) and the TruSeq Stranded Total RNA Library Prep Gold Kit (Illumina 20020599) following the manufacturer’s protocol (Illumina 1000000040499). RNAseq library quality and quantity were measured using a TapeStation 4200 (Agilent G2991AA) and Qubit 3.0 fluorometer (Life Technologies Q33216), pooled at equal molar ratios, and denatured following the manufacturer’s protocol (Illumina 1000000106351). 271 total RNA sequencing libraries were sequenced at TGL on NovaSeq 6000 (Illumina 20012850) S4 flow cells (Illumina 20028313) following the manufacturer’s protocol (Illumina 1000000019358) using a 2x50 bp paired-end configuration and pool sizes of 91 libraries to target a read depth of 110 million clusters per library on average.

  Dataset EGAD00001010201

• Drug-induced epigenomic plasticity reprograms circadian rhythm regulation to drive prostate cancer towards androgen-independence (ChIP-seq)

  Understanding how prostate cancer cells adapt to AR-targeted interventions is critical for identifying novel drug targets to improve the clinical management of treatment-resistant disease. Our study revealed an enzalutamide-induced epigenetic plasticity towards pro-survival signaling, and uncovered circadian regulator ARNTL as an acquired vulnerability after AR inhibition, presenting a novel clinical lead for therapeutic development.

  Study EGAS00001006017

• Sequencing of Coding and Non-coding Regions in Primary Breast Cancers and Patient-matched Controls

  Genomic analysis of tumor samples has led to the identification of hundreds of cancer genes based on the presence of mutations in protein-coding regions. By contrast, much less is known about cancer-causing mutations in non-coding regions. Here, we performed deep sequencing in 360 primary breast cancers and developed computational methods to identify significantly mutated promoters. Clear signals were found in the promoters of four genes. FOXA1, a known driver of hormone-receptor positive breast cancer, harbors a mutational hotspot in its promoter that leads to overexpression through increased E2F binding. RMRP and NEAT1, two non-coding RNA genes, carry mutations that alter protein binding to the promoter and impact expression levels. Overall, our study shows that recurrent mutations in or near gene promoters in cancers have functional consequences. Power analyses indicate that more such genes remain to be discovered through deep sequencing of adequately sized patient cohorts.

  Study phs001250

• Examination of Engineered LINE-1 Integration Events in HeLa Cells

  Long Interspsesed Element-1 (LINE1 or L1) encodes two proteins (ORF1p and ORF2p) required for its mobilization (i.e. retrotransposition) in the human genome. Human ORF2p, a 150kDa protein, has endonuclease (EN) and reverse transcriptase (RT) activities. L1 EN is classified as apurinic/apyrimidin-like endonuclease (APE) and is responsible for initiating target-site primer reverse transcription (TPRT) during the L1 retrotransposition cycle. During canonical TPRT, the L1 EN activity makes a single-strand endonucleolytic nick at a double-strand DNA target sequence in genomic DNA. The endonucleolytic nick is typically made at an L1 EN degnerate consensus cleavage sequence (5'-TTTT/A-3') exposing a free 3' hydroxy group that can be used as a primer by the ORF2p L1 RT activity to reverse transcribe the associated L1 RNA. Here, we characterized over 21,000 de novo engineered L1 retrotransposition events in HeLa cells to determine if L1 exhibits overt integration preferences in the human genome. Bru-seq of HeLa cells to determine actively transcribed regions of the genome was also performed. This Bru-seq data was used to determine if engineered L1 integration events preferentially integrate into transcribed regions of the genome, and to determine which strand during transcription may present itself as preferential during L1 retrotransposition.

  Study phs001669

• Single-cell level characterization of B cell depletion and repopulation following rituximab in systemic lupus erythematosus

  Rituximab, a CD20+ B cell depletion therapy, is frequently used in the treatment of systemic lupus erythematosus (SLE). However, variability in patient response highlights the need for a deeper understanding of the underlying immune cell dynamics of B cell depletion and repopulation. In this study, we conducted longitudinal single-cell profiling of nine SLE patients treated with rituximab from pretreatment to up to 15 months post-treatment. These were compared to eight healthy controls. We profiled PBMCs via 10X Genomics single-cell RNA, surface protein (CITE-seq), B cell receptor (BCR), and T cell receptor (TCR) sequencing and sequenced bulk BCR repertoires in parallel. For single cell sequencing, 10 pools were created with an equal number of cells from 4 samples each. Samples collected at different timepoints from the same patient were distributed across different pools to allow demultiplexing of individuals using genotypes captured from the scRNA-seq data. Libraries were pooled using a ratio of GEX:CITE:TCR:BCR=9:2:1:1 and were sequenced across two lanes of the NovaSeq 6000. For bulk BCR sequencing, individual samples were demultiplexed using primer barcodes and paired-end BCR amplicon reads were merged prior to submission; data are provided as unmapped single-end reads.

  Study EGAS00001006798

• Bulk RNASeq of metastatic colorectal cancer organoids with ATOH1 knockout

  Bulk RNA sequencing was performed on mCRC organoids subjected to cetuximab treatment, comparing ATOH1 knockout and control conditions. The dataset is intended to elucidate the contribution of ATOH1-regulated secretory cell population to cetuximab persistence mechanisms.

  Dataset EGAD50000002060

• Korean Advanced Thyroid Cancer Dataset

  Massively-parallel DNA sequencing of 113 advanced thyroid cancers and Massively-parallel RNA sequencing of 25 advanced thyroid cancers

  Dataset EGAD00001004845

• RNAseq of resident memory T cells from human lung tumor

  This dataset includes the RNA sequencing of 14 samples. Samples are FACS sorted CD8+ T cells expressing or not the integrin CD103. The paired samples (TRM and non-TRM) were sorted from the tumor of 7 lung cancer patients.

  Dataset EGAD00001006812

• PsychENCODE Consortium: Epigenetic and Transcriptional Dysregulation in Autism Spectrum

  Our current understanding of autism spectrum disorders (ASD) delineates a highly heritable, yet etiologically heterogeneous disease. Forward genetic approaches to find disease associated mutations or common variation have been successful and continue to offer considerable power. Yet, given the accumulating evidence for very significant heterogeneity and environmental influences, complementary approaches to classic forward genetics become necessary. Genetic polymorphism and mutation data to date have identified dozens of causal or contributory variants, yet our preliminary data from autism brain suggest that common molecular pathways are involved in a significant subset of cases. This convergence at the tissue level suggests that other mechanisms, specifically epigenetic changes, combined with genetic background, are contributing to such final common pathways. We further tested this hypothesis by taking a comprehensive and integrative genome-wide approach to assessing brain gene-expression, miRNA levels and the related, causal epigenetic mechanisms in ASD etiology. We performed RNA-seq analyses of four cerebral cortical regions and cerebellum from ASD cases and controls, to assess mRNA, miRNA, and splicing isoform regulation. In parallel, we identified key differences in chromatin state and DNA methylation across multiple brain regions in the same ASD and control individuals used in the expression analyses using ChIP-Seq and MeDIP. We assessed the mechanisms by which changes in DNA methylation, histone modification, and DNA sequence contribute to the observed differences in gene expression. This work, which represents an unprecedented effort to unify these often disparate data (usually produced without integration in mind), delineates potential shared molecular pathways in ASD and the underlying mechanism of these differences at the level of miRNA, the chromatin regulatory apparatus, and DNA methylation. The following substudies are part of the PsychENCODE release at dbGaP and offer additional molecular data: PsychENCODE: RNA-Sequencing - SRRM4 Splicing Study phs000872 PsychENCODE: Global Changes in Patterning, Splicing and lncRNAs phs001061 PsychENCODE: Chromatin Contact Map in Fetal Cortical Laminae phs001190 PsychENCODE: Epigenetic Dysregulation in Autism Spectrum Disorder phs001220

  Study phs001022