14970 results for "cancer studies using rna-seq"

in 15.55 milliseconds.

• Complex-I stratification of Parkinson's disease - single nucleus RNAseq

  Single nucleus RNA seq dataset for CI stratification of Parkinson's disease Single nucleus RNA seq dataset of prefrontal cortex tissue from a total of N=18 samples. Tissue samples correspond to patients with idiopathic Parkison's disease (PD) with varying levels of Complex-I activity (N=12) and neurologically healthy controls (N=6). Single nucleus RNA seq was carried out using 10X Genomics Chromium. This dataset corresponds to a subset of the samples sequenced using conventional bulk tissue RNA seq and available within this Study as a separate Dataset.

  Dataset EGAD50000000432

• Deciphering RBP - alternative splicing networks in ALS iPSC-MN: NOVA1 gain and loss of function systems

  We produced NOVA1 and EGFP over-expression RNA-seq datasets in three healthy control individuals using lentivirus-mediated gene transfer to model NOVA1 gain of function. Additionally, we produced a NOVA1 loss of function RNA-seq dataset by generating iPSC-MN with NOVA1 knock out produced by CRISPR/Cas9 in the CV-B iPSC line.

  Study EGAS00001005881

• NKI-AvL CRC-OVC RNA-seq

  The dataset “NKI-AvL CRC-OVC RNA-seq" includes 4 FASTQ files from single-end total RNA sequencing on Illumina HiSeq2500 for 2 colorectal cancer and 2 ovarian cancer patients.

  Dataset EGAD00001004341

• Whole exome sequencing and RNA-seq of esophageal squamous cell carcinoma

  We perform integrative genome-wide analyses such as whole-exome sequencing, copy number variant(CNV) analysis, and gene expression analysis using next-generation sequencing and other methods to elucidate driver genes and signaling pathways causing tumorigenesis and cancer progression, leading novel molecular diagnostics and molecular therapies.

  Study JGAS000367

• RNA seq data of 2 lung cancer samples prepared using 2 different RNA-seq library preparation protocols

  Raw data used for generation of the results in the Vardetector manuscript – “.bam” files of RNA-seq data of tumor samples of 2 patients prepared with 2 different library preparation protocols (exome-capture and ribodepletion –> 4 “.bam” files in total). The submission also contains the somatic mutations “.vcf” files (4 in total, however 2 unique). Moreover, also an output of the Vardetector module (“.csv” file with the number of reads above the mutations of interest) is present in the submission (4 “.csv” files in total).

  Study EGAS50000001419

• RNA-seq

  Bulk RNA-seq data of 8 RNA samples were generated. Libraries were prepared using the Stranded mRNA Library Prep, Ligation Kit (Illumina) following manufacturer’s recommendations and sequenced on a NextSeq 2000 (2x50 bp, Illumina).

  Dataset EGAD00001010308

• Functional Analysis of Genetic Variants in African Americans with Breast Cancer

  The goal of this study is to identify and characterize novel genetic variants associated with a predisposition to breast cancer (BCa) in African Americans (AAs) using a family case-family control study design. Variants of unknown clinical significance (VUS) were characterized using bioinformatics tools. Future studies will further characterize select VUSs using in vitro genomic editing methods and functional assays to determine the functional consequences. The targeted sequencing data is made available for 85 actionable cancer genes. These genes have been previously classified with deleterious mutation(s) and whose phenotype results in a specific, defined medical recommendation(s).

  Study phs002977

• Genomic characterization of Malignant Pleural Mesothelioma.

  Genomic characterization of Malignant Pleural Mesothelioma using RNA-seq, Exome and Illumina 2.5 M array.

  Study EGAS00001001563

• Targeted gene fusion sequencing (Fus-seq) in mesothelioma

  This is a small pilot data set to test the feasibility of cDNA exomes across 1200 cancer cell line panel. cDNA exomes or Fus-seq is further explained in this studies Abstract.

  Dataset EGAD00001000361

• Single nucleus RNA-seq of human epiglottis and subglottis

  This dataset contains single nucleus RNA-seq of human epiglottis and subglottis tissue performed using the 10X platform

  Dataset EGAD50000001279

• DDX50 Cooperates With STAU1 to Effect Stabilization of Pro-Differentiation RNAs

  This study was undertaken to determine the role of DDX50 in epidermal homeostasis. Primary neonatal foreskin keratinocytes were obtained from discarded surgical samples at a California hospital. Samples were anonymous and not selected. DDX50, which was associated with STAU1, was found to promote epidermal differentiation and transcript stability using the methods of RNA-seq, CLIP-seq and DMS-MaP-seq.

  Study phs003766

• RNA-seq study of a Princess Margaret Cancer Centre human acute myeloid leukemia patient cohort

  The PMCC AML RNAseq dataset consists of 81 AML patient samples (clinical data in Supplemental Table 11 of manuscript), processed in two batches. These patient samples are able to engraft in the NSG (NOD.Cg PrkdcscidIl2rgtm1Wjl /SzJ) mouse model. Five patients (90543, 598, 90240, 110484, 100500) were included in both batches. Viaably frozen material from the Leukemia Tissue Bank at Princess Margaret Cancer Centre/ University Health Network were thawed by dropwise addition of X-VIVO + 50% fetal calf serum supplemented with DNase (100μg/mL final concentration, Roche). RNA was extracted from bulk peripheral blood mononuclear cells (PBMC) using the RNeasy Micro Kit (Qiagen Inc.). A paired-end 76 base-pair flow-cell lane Illumina High seq 2000 yielded an average of 240 million sequence reads aligning to genome per sample at the Genome Sciences Centre, BC Cancer Agency for cohort 1. Cohort 2 was subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Centre for Applied Genomics, Sick Kids Hospital.

  Study EGAS00001004792

• Ewings Sarcoma RNA-seq drug sensitivity

  Illumina RNA-Seq will be performed on four Ewing's sarcoma cell lines and two control cell lines. RNA was extracted from all the lines using a basic Trizol extraction protocol.

  Dataset EGAD00001000337

• Prostate cancer datasets RNA Seq

  Total RNA Seq: 15 Samples (2 patients (MF1 and MF3)) (HiSeq) and Poly A RNA Seq: 27 Samples (4 patients Normal and Tumour ) (HiSeq)

  Dataset EGAD00001004468

• Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

  Genetic and non-genetic heterogeneity within cancer cell populations represents a major challenge to anti-cancer therapies. We currently lack robust methods to determine how pre-existing and adaptive features affect cellular responses to therapies. Here, by conducting clonal fitness mapping and transcriptional characterization using expressed barcodes and single-cell RNA-sequencing, we have developed TraCe-seq, a method that captures at clonal resolution the origin, fate, and differential early adaptive transcriptional programs of cells in a complex population in response to distinct treatments. We used TraCe-seq to benchmark how next-generation dual EGFR inhibitors-degraders compare to standard EGFR kinase inhibitors in EGFR-mutant lung cancer cells. To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

  Study EGAS00001005405

• Comprehensive Transcriptional Analysis of Early Stage Urothelial Carcinoma using whole transcriptome sequencing

  The expression profile and sequence variants of 476 early stage urothelial carcinoma were studied using whole transcriptome sequencing. RNA-Seq libraries were prepared by Ribo-Zero treatment of total-RNA followed by library preparation using ScriptSeq (both Epicentre/Illumina). RNA-Seq libraries were paired-end sequenced (2x 101 bp) on Illumina HiSeq 2000 and the resulting fastq files were processed using tools from the Genome Analysis Toolkit (GATK and from the Tuxedo suite. Access to the sequence data (mapped and un-mapped bam and vcf files), containing person identifying information, needs signature on a controlled access form, and can be accessed at The European Genome-phenome Archive (EGA) following request. An expression matrice of FPKM values are available without restriction at ArrayExpress (E-MTAB-4321).

  Study EGAS00001001236

• RNA-seq

  RNA sequencing files that were used in our study. The cohort was composed of 39 cases of RNA sequencing data. RNA-seq library was prepared with rRNA depletion method, and the sequence was performed using DNBSEQ sequencer.

  Dataset EGAD50000000971

• Raw sequencing data from chromosome conformation capture, RNA sequencing and chromatin assays in human primary monocytes

  This dataset contains raw sequencing data from eQTL Capture Hi-C, ATAC-seq and RNA-seq experiments in monocytes isolated from 34 healthy male donors, as well as from Hi-C, 4C-seq and CTCF ChIP-seq in subsets of individuals. The data are released as paired-end Illumina FASTQ files. Hi-C and Capture Hi-C used DpnII digestion and Tn5-based low-input library preparation. In Capture Hi-C, this was followed by targeted capture with custom-designed biotinylated RNA probes targeting ~1100 eQTL regions. ATAC-seq was performed on PFA-fixed cells using a digitonin-based protocol. 4C-seq and CTCF ChIP-seq were performed using standard protocols.

  Dataset EGAD50000001116

• Dana-Farber Cancer Institute (DFCI) Wu Lab/Avicenne CLL RNA-Seq Study

  Chronic Lymphocytic Leukemia (CLL) is a hematological malignancy characterized by accumulation of CD5+ B cells in peripheral lymphoid organs, bone marrow and blood. Recently, the advent of large-scale whole-exome sequencing of hundreds of CLL samples has led to gain a comprehensive understanding of the mutational landscape of this clonal B cell malignancy, but the functional effects of the putative driver mutations thus discovered are largely unknown. In this study, we analyze RNA-seq data from CLL patients to characterize dysregulated biological pathways regarding the presence of recurrent mutations. Source of tumor is patients' PBMC isolated from peripheral blood using the Ficoll method. Purity was confirmed using flow cytometry flow (>80% in all cases).

  Study phs002335

• LuCaP cell line RNA-seq

  RNA-seq of LuCaP 189.4 cell line. Treatment with DCC DMSO (n=3 replicates) or 1nm R1881 (n=3 replicates). All 6 samples were sequenced using cDNA oligo-dT using paired-end reads on Illumina NovaSeq 6000. Each sample has 2 fastq files, one for the forward and reverse read, respectively.

  Dataset EGAD50000001344

• The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia

  Acute lymphoblastic leukaemia (ALL) is the most common childhood malignancy, and implementation of risk-adapted therapy has been instrumental in the dramatic improvements in clinical outcomes. A key to risk-adapted therapies includes the identification of genomic features of individual tumors, including chromosome number (for hyper- and hypodiploidy) and gene fusions, notably ETV6-RUNX1, TCF3-PBX1 and BCR-ABL1 in B-cell ALL (B-ALL). RNA-sequencing (RNA-seq) of large ALL cohorts has expanded the number of recurrent gene fusions recognized as drivers in ALL, and identification of these new entities will contribute to refining ALL risk stratification. We used RNA-seq on 126 ALL patients from our clinical service to test the utility of including RNA-seq in standard of care diagnostic pipelines to detect gene rearrangements and IKZF1 deletions. RNA-seq identified 86% of rearrangements detected by standard of care diagnostics. KMT2A-rearrangements (MLL), whilst usually identified, were the most commonly missed by RNA-seq as a result of low expression. RNA-seq identified rearrangements that were not detected by standard of care testing in nine patients. These were found in patients who were not classifiable using standard molecular assessment. We developed an approach to detect the commonest IKZF1 deletion from RNA-seq data and validated this using a RQ-PCR assay. We applied an expression classifier to identify Ph-like B-ALL patients. T-ALL proved a rich source of novel gene fusions which have clinical implications or provide insights into disease biology. Our experience shows that RNA-seq can be implemented within an individual clinical service to enhance the current molecular diagnostic risk classification of ALL.

  Study EGAS00001004212

• Paired RNA seq of wild type VDH15 cells (3 replicates) - a cell line of oral squamous cell carcinoma (OSCC)

  Paired RNA seq of wild type VDH15 cells (3 replicates) - a cell line of oral squamous cell carcinoma (OSCC). RNA was extracted and sequencing libraries were prepared using TruSeq Stranded mRNA Library Prep Kit following manufacturer's protocol. The sequencing was done using Illumina Novaseq 6000.

  Dataset EGAD00001010172

• Benchmarking V(D)J Repertoire Reconstruction: Bulk RNA-Seq vs PCR-Based RepSeq Validated by SMRT Sequencing

  The aim of this study is to benchmark methods for immunoglobulin repertoire profiling using human B-cell samples. We compare targeted VDJ mRNA sequencing and repertoire reconstruction from bulk RNA-seq data to PCR-independent full-length transcript sequencing using Single-Molecule Real-Time technology. The objective is to assess methodological biases and establish a robust reference framework for immunoglobulin repertoire analysis.

  Study EGAS50000001541

• RNA-Seq of patient-derived fibroblast cell lines with inborn errors of cobalamin (vitamin B12) metabolism and controls

  RNA sequencing of 31 patient-derived fibroblast cell lines from patients with inborn errors of cobalamin (vitamin B12) metabolism, and 7 control samples. The RNA seq library was prepared using the TruSeq Stranded Total RNA Sample Preparation Kit (Illumina RS-122–2301) including Ribo-Zero Gold depletion to remove ribosomal RNA. Sequencing was done via llumina Hi-Seq2000 sequencer, using 100bp paired end reads.

  Dataset EGAD00001003142

• RNA-seq data from primary AML samples with t(3;8)

  RNA-seq was generated to investigate differences in gene expression between t(3;8) AML and other primary AMLs. Briefly, sample libraries were prepared using 500 ng of input RNA according to the KAPA RNA HyperPrep Kit with RiboErase (HMR) (Roche) using Unique Dual Index adapters (Integrated DNA Technologies, Inc.). Amplified sample libraries were paired-end sequenced (2x100 bp) on the Novaseq 6000 platform (Illumina

  Dataset EGAD00001006819

• National Cancer Institute Cancer Genome Characterization Initiative (CGCI)

  The Office of Cancer Genomics at the National Cancer Institute sponsored a series of studies as part of the Cancer Genome Characterization Initiative (CGCI) to assess novel emerging sequencing technologies in cancer. The CGCI program included comprehensive characterization of the genetic aberrations found in different pediatric and/or adult tumors. CGCI characterized a number of B-cell non-Hodgkin lymphomas (including diffuse large B-cell lymphoma (DLBCL) from patients with and without HIV+ infection, follicular lymphoma (FL), as well as adult and pediatric Burkitt lymphomas), and additional HIV-associated tumors (including DLBCL, lung, and cervical cancers). All data from these projects is available at the NCI Genomic Data Commons. Individual project descriptions are available by disease on the substudy pages (links are included at the top of this page). Brief summaries are as follows: Non-Hodgkin Lymphoma (NHL) - CGCI investigators probed genomic alterations more deeply than had previously been possible by using state-of-the-art RNA sequencing (mRNA-seq) and whole genome shotgun sequencing (WGS) coupled with leading edge bioinformatics, data management and analysis approaches. The project sequenced tumor DNA and/or RNA from 117 NHL tumor samples and 10 cell lines. This included the genomes or exomes of 1 Follicular Lymphoma (FL) and 13 diffuse large B-cell lymphoma (DLBCL) cases, all with matched constitutional DNA sequenced to comparable depths, RNA-sequencing (mRNA-seq) of 92 DLBCL, 12 FL and 8 B-cell NHL cases with other histologies and 10 DLBCL-derived cell lines. The DLBCL cases and cell-lines are from the two major subtypes of DLBCL: germinal center B-cell (GCB) and activated B-cell (ABC). HIV+ Tumor Molecular Characterization Project (HTMCP) - This project was a joint effort of the Office of Cancer Genomics (OCG) and the Office of HIV and AIDS Malignancy (OHAM). Its goals were to characterize HIV-associated cancers (obtained from HIV-infected patients) and compare them to the same types of cancers from patients without HIV infection. Investigators performed 30X genome sequencing of 100 cases of paired tumor and germline DNA, along with transcriptome sequencing in each of 3 types of HIV+ tumors (DLBCL, lung and cervical cancers). These platforms allow discovery of mutations both in coding and non-coding genomic regions, gene expression and genomic alterations (including translocations, insertions and deletions). Comparing tumors of cancer patients both with and without HIV-infection provides insight into the potential function of this virus in certain cancers. Burkitt Lymphoma Genome Sequencing Project (BLGSP) - This project was a collaborative effort between the National Cancer Institute and the Foundation for Burkitt Lymphoma Research to develop a databank of the many alterations found in Burkitt lymphoma (BL), an uncommon type of Non-Hodgkin lymphoma that occurs most often in children and young adults. The goal of the BLGSP was to explore potential genetic changes in patients with BL that could lead to better prevention, detection and treatment of the cancer. The project characterized the alterations of the tumors' genomes (with matched normal as control) and transcriptomes by sequencing the DNA and RNA of each case. Using the data generated, the ultimate goals of the project was to discover the molecular changes that are present in BL patients and then determine how those changes correlate with treatment regimen and outcome. CGCI data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the CGCI Publication Pages at the GDC (Please see the "Supplemental Links" section of any CGCI publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original CGCI research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data), as well as higher level data generated by the GDC. Please see the CGCI Use and Publication Guidelines for updated details on the sharing of any CGCI substudy data, including how to cite CGCI.To learn more about the CGCI studies, please visit the CGCI Program website.

  Study phs000235

• Regulatory Changes in Glioblastoma Brain Tumors and Xenografts Wave 1

  Non-coding elements in our genomes that play critical roles in complex disease are frequently marked by highly unstable RNA species. Sequencing nascent RNAs attached to an actively transcribing RNA polymerase complex can identify unstable RNAs, including those templated from gene-distal enhancers (eRNAs). However, nascent RNA sequencing techniques remain challenging to apply in some cell lines and especially to intact tissues, limiting broad applications in fields such as cancer genomics and personalized medicine. Here we report the development of chromatin run-on and sequencing (ChRO-seq), a novel run-on technology that maps the location of RNA polymerase using virtually any frozen tissue sample, including samples with degraded RNA that are intractable to conventional RNA-seq. We used ChRO-seq to develop the first maps of nascent transcription in 23 human glioblastoma (GBM) brain tumors and patient derived xenografts. Remarkably, >90,000 distal enhancers discovered using the signature of eRNA biogenesis within primary GBMs closely resemble those found in the normal human brain, and diverge substantially from GBM cell models. Despite extensive overall similarity, 12% of enhancers in each GBM distinguish normal and malignant brain tissue. These enhancers drive regulatory programs similar to the developing nervous system and are enriched for transcription factor binding sites that specify a stem-like cell fate. These results demonstrate that GBMs largely retain the enhancer landscape associated with their tissue of origin, but selectively adopt regulatory programs that are responsible for driving stem-like cell properties. We also identified enhancers and their associated transcription factors that regulate genes characteristic of each known GBM subtype, and discovered a core group of transcription factors that control the expression of genes associated with clinical outcomes. This study uncovers new insights into the molecular etiology of GBM and introduces ChRO-seq which can now be used to map regulatory programs contributing to a variety of complex diseases.

  Study phs001646

• A Genome-Wide Association Study of CALGB 90401: Randomized, Double-Blind, Placebo-Controlled Phase III Trial Comparing Docetaxel and Prednisone with or without Bevacizumab in Men with Metastatic Castration-Resistant Prostate Cancer

  The Cancer and Leukemia Group B (CALGB) 90401 trial compared docetaxel and prednisone with or without bevacizumab in men with metastatic castration-resistant prostate cancer. A genome-wide association study using clinical outcomes and toxicities was conducted on the basis of data from CALGB patients who provided consent for pharmacogenomic studies and usable DNA

  Study phs001002

• Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

  Dac EGAC00001000891

• Blood plasma and FFPE derived total RNA seq dataset from DLBCL and PMBCL patients

  Blood plasma samples (n=168) and matched diagnostic formalin-fixed paraffin-embedded (FFPE) tissue samples (n=69) of DLBCL patients, PMBCL patients and healthy controls were collected between 2016-2021. Plasma samples were collected at diagnosis, at interim evaluation, after treatment, and in case of refractory or relapsed disease. RNA was extracted from 200 µl plasma using the miRNeasy serum/plasma kit and from FFPE tissue using the miRNeasy FFPE kit. RNA was subsequently sequenced on a NovaSeq 6000 instrument using the SMARTer Stranded Total RNA-seq pico v3 library preparation kit.

  Dataset EGAD00001011679