15056 results for "cancer studies using rna-seq"

in 27.61 milliseconds.

• Whole-transcriptome characterization of cell-free RNA (cfRNA) in cancer and non-cancer patients

  Whole-transcriptome characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Dataset includes collapsed BAM files for plasma cfRNA from each patient, as well as collapsed BAM files for RNA from matched tumor tissue (when available).

  Dataset EGAD00001006484

• CIDR: The Role of Rare Coding Variation in Prostate Cancer in Men of African Ancestry - RESPOND Project 2

  In RESPOND Project 2, we seek to identify rare genetic factors that are associated with prostate cancer (PCa) risk and aggressiveness in men of African ancestry (AA). We will conduct exome sequencing of 15,000 prostate cancer cases and 5,000 controls from the RESPOND cohort and the African Ancestry Prostate Cancer Consortium (AAPC) with cases selected based on risk categories: high-risk (stage T3/T4 or Gleason 8+ or PSA>20 ng/ml), intermediate-risk (stage T2b/T2c or Gleason 7 or PSA 10-20 ng/ml) and low-risk disease (stage T1/T2a and Gleason ≤ 6 and PSA<10 ng/ml). We expect the findings from this Project to significantly advance knowledge of susceptibility to aggressive PCa and racial/ethnic disparities in PCa risk, and to guide the development of future preventive, early detection and prognostic measures for AA men. The first phase of the study will include exome sequence data for approximately 7,500 cases and 5,000 controls from AAPC. The second phase of the study will include exome data for 5,000 cases from RESPOND and AAPC.ACKNOWLEDGMENTS and CONTRIBUTING SITES Multiethnic Cohort (MEC): The MEC and the genotyping in this study were supported by National Institutes of Health (NIH) grants CA63464, CA54281, CA1326792, CA148085, and HG004726. Cancer incidence data for the MEC and Los Angeles Study of Aggressive Prostate Cancer (LAAPC) studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with federal funds from the National Cancer Institute (NCI)/NIH/Department of Health and Human Services (DHHS) under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the Centers for Disease Control and Prevention (CDC). Ghana Prostate Study (GPS): The Ghana Prostate Study was funded by the Intramural Program of the NCI/NIH/DHHS under Contract No. HHSN261200800001E. Men of African Descent and Carcinoma of the Prostate (MADCaP): We thank all MADCaP study participants. This work is a product of the MADCaP network. This work was supported by NCI/NIH grant U01CA184374 to Timothy Rebbeck and National Institute of General Medical Sciences (NIGMS) MIRA grant R35GM133727 to Joseph Lachance. Additional funding includes a seed grant from the Integrated Cancer Research Center at Georgia Institute of Technology. UGANDA: The UGANDA study was supported by NIH grant R01CA165862. Southern Community Cohort (SCCS) is funded by NIH grant CA092447. SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt Ingram Cancer Center (CA68485). Data on SCCS cancer cases were provided by Alabama Statewide Cancer Registry, Kentucky Cancer Registry, Office of Cancer Surveillance at Tennessee Department of Health, Florida Cancer Data System, Central Cancer Registry at North Carolina Division of Public Health, Georgia Comprehensive Cancer Registry, Louisiana Tumor Registry, Mississippi Cancer Registry, South Carolina Central Cancer Registry, Virginia Cancer Registry at Virginia Department of Health, and Cancer Registry at Arkansas Department of Health. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries (NPCR)/Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the NPCR/CDC. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. Karuprostate: The Karuprostate study was supported by the French National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la Prostate. Séverine Ferdinand, Marc Romana. The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. We would also like to acknowledge the UNC BioSpecimen Facility and the LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). Gene-Environment Interaction in Prostate Study (GECAP) was supported by NIH grant ES011126. King County Prostate Cancer Study (KCPCS) was supported by NIH grants CA056678, CA082664, and CA092579, with additional support from the Fred Hutchinson Cancer Research Center. We thank the participants in these studies, and Ms. Suzanne Kolb for help with study management. The Los Angeles Study of Aggressive Prostate Cancer (LAAPC) was funded by grant 99-00524V-10258 from the Cancer Research Fund, under Interagency Agreement #97-12013 (University of California contract #98-00924V) with the Department of Health Services Cancer Research Program. Cancer incidence data for the MEC and LAAPC studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with Federal funds from the NCI/NIH/DHHS under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the CDC. Prostate Cancer Studies at MD Anderson (MDA) was supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388.

  Study phs002637

• RNA-seq data of CRC-PDX tumors

  We obtained bulk RNAseq data of CRC-PDX tumors and performed molecular subtype classification.

  Dataset EGAD50000000850

• Single-cell RNA sequencing of human IL-18R supported CAR T cells targeting oncofetal Tenascin C

  scRNA-seq raw data

  Dataset EGAD50000001134

• RNA-Seq of human stimulated and cultured CD4+ Treg cells

  This dataset includes whole transcriptome data of human stimulated and cultured CD4+ Treg cells (39 samples).

  Dataset EGAD00001005964

• Follicular T cell lymphoma

  Paired-end RNA-seq of follicular T cell lymphoma for the discovery of fusion transcripts

  Dataset EGAD00001006379

• Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas: RNAseq variants

  Variants called from RNA-seq data of meningioma tumors.

  Dataset EGAD00001002649

• Sequence analysis of colorectal serrated lesions

  Recent studies have shown that colorectal serrated lesions, which include sessile serrated adenomas (SSAs) and traditional serrated adenomas (TSAs), are precursors of colorectal cancer. However, the molecular mechanisms underlying the carcinogenesis, particularly in TSAs, remain largely uncharacterized. To clarify their molecular and clinicopathological characteristics, we performed mutation and methylation analyses of cancer-associated genes in 78 serrated lesions, including TSAs, SSAs and microvesicular hyperplastic polyps. Target exon sequence analysis was performed with 39 genes, including genes known to be frequently mutated in colorectal cancers and/or serrated lesions. We also used bisulfite pyrosequencing to assess the methylation status of various cancer-associated genes and marker genes of the CpG island methylator phenotype (CIMP). The prevalence of mutations in genes associated with Wnt signaling was significantly higher in TSAs than SSAs (65% vs. 28%, p < 0.01). Among those, RNF43 mutations were observed in 38% of TSAs and 17% of SSAs. In immunohistochemical studies of 39 serrated lesions, the prevalence of abnormal nuclear ?-catenin accumulation was significantly higher in TSAs (57%) than SSAs (8%) (P = 0.01). SMOC1 methylation was detected in 54% of TSAs but in no SSAs (p < 0.01). Additionally, SMOC1 methylation was more prevalent among TSAs with KRAS mutation (82%) than with BRAF mutation (38%, p = 0.03). Lesions with CIMP-high or RNF43 mutations were detected only in TSAs with BRAF mutation, suggesting two distinct carcinogenic pathways in TSAs. Mutations in genes associated with Wnt signaling play a greater role in the carcinogenesis of TSAs than SSAs.

  Study JGAS000217

• scRNA-seq of human follicular lymphoma and lymph node

  Cryopreserved cells from human nodal follicular lymphoma and lymph node samples were thawed and processed for scRNA-seq analysis. CD3+ CD19− 7-AAD− live T cells (six FL samples from the Original cohort) or 7-AAD− whole live hematopoietic cells (five lymph node and nine FL samples from Validation cohort 1) were sorted using a FACS Aria II or III instrument (BD Biosciences). To generate single-cell emulsions, 6,000–10,000 live cells were loaded into the 10X Genomics Chromium Controller for single-cell partitioning, along with the reverse transcriptase reagent mixture and 3' or 5' gel beads. Sorted T or whole hematopoietic cells were converted to barcoded scRNA-seq libraries using 10X Genomics Chromium single cell 3' reagent kits (v3) for the Validation cohort 1, 5' reagent kits (v1) for the Original cohort, according to the manufacturer’s instructions. The libraries were sequenced on an Illumina HiSeq X Ten or NovaSeq X Plus system, mapped to the human genome (build GRCh38), and demultiplexed using CellRanger pipelines (v3.1.0, 10x Genomics).

  Dataset EGAD50000001143

• Gene expression by RNAseq in bronchial biopsies of asthmatics, asthma in remission and healthy subjects

  The study focus was differential expression in bronchial biopsies between persistent asthma, asthma in remission and healthy controls using RNAseq. There were 184 samples that passed QC. RNA samples were processed using the TruSeq Stranded Total RNA Sample Preparation Kit (Illumina, San Diego, CA), using an automated procedure in a Caliper Sciclone NGS Workstation (PerkinElmer, Waltham, MA). In this procedure, all cytoplasmic and mitochondria rRNA was removed (RiboZero Gold kit). The obtained cDNA fragment libraries were loaded in pools of multiple samples unto an Illumina HiSeq2500 sequencer using default parameters for paired-end sequencing (2 × 100 bp). Data are available as 221 pairs of FASTQ-files. Note that several samples are associated with multiple sequence runs.

  Dataset EGAD00001005112

• Prostate Cancer Genome Sequencing Project

  Prostate cancer is a prevalent cause of cancer morbidity and mortality in men. In order to characterize the full range of somatic mutations in protein-coding genes that may drive the growth of prostate cancer, we sequenced the exonic regions of genomic and tumor DNA from over 100 patients with high-risk primary prostate cancer. Using hybrid capture and paired end DNA sequencing, we identified mutations in several novel putative prostate cancer genes. We interrogated copy number changes across tumor genomes using high-density SNP arrays, and identified a molecular subtype of cancer characterized by mutation of the ubiquitin ligase subunit SPOP and copy number loss at specific genomic loci.

  Study phs000447

• Single-cell RNA seq-derived signatures define response patterns to atezolizumab + bevacizumab in advanced hepatocellular carcinoma

  FASTq files and normalised gene expression counts from bulk RNA-sequencing of pre-treatment tumour (n=39) and adjacent non-tumour tissue samples (n=13) from advanced hepatocellular carcinoma (HCC) patients treated with atezolizumab plus bevacizumab.

  Study EGAS50000000838

• 10X single-cell Multiome (RNA+ATAC) of bone marrow-derived HSPC

  10X genomics chromium single-cell ATAC+RNA (Multiome) was use to prepare single-nucleus RNA- and ATAC-seq libraries, sequenced on an Illumina NovaSeq 6000 platform. BAM files are provided. Samples from 6 donors were sequenced after sorting for primitive HSPCs in 5 libraries; each library comprises a single donor, except one with cells from 1 male and 1 female donor.

  Dataset EGAD50000002326

• Transcriptional profiles of Kleefstra syndrome (EHMT1 and EHMT2) and healthy iPSCs

  This dataset contains FASTQ files from RNA sequencing (RNA-seq) of induced pluripotent stem cells (iPSCs) derived from a healthy donor (control), a patient with Kleefstra syndrome (KSP), and two patients carrying pathogenic variants in EHMT2 (P1 and P2). Poly(A)-selected RNA was used for library preparation, and strand-specific libraries were generated for paired-end sequencing on the MGI DNBSEQ PE100 platform.

  Dataset EGAD50000002344

• RNA seq before and after cold pressor test

  The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. Twenty-two females were phenotypically assessed before and after a CPT, and blood samples were taken for RNA-sequencing.

  Study EGAS00001006690

• Characterization of chromatin accessibility in metastatic prostate cancer

  The development of resistance to second-generation AR-signaling inhibitors (ARSIs) and progression to metastatic castrate-resistant prostate cancer (mCRPC) represents a huge obstacle to the improvement of patients’ clinical outcomes. Lineage plasticity is a common mechanism that drives the development of mCRPC by changing chromatin conformation at regulatory elements affecting downstream gene activity. ATAC-seq is a popular technique that measures accessible chromatin regions. To better understand of potential epigenomic mechanisms of ARSI resistance in prostate cancer, in this study, we performed ATAC-seq on 70 mCRPC tissue biopsies from the SU2C/PCF West Coast Dream Team (WCDT) cohort.

  Study EGAS00001006698

• RNA-seq datatset of primary human thymocyte subsets

  FASTQ-files of RNA-seq experiments of 8 primary human thymocyte subsets, isolated by flow-cytometry (FACS) from neonatal thymus biopsies. All samples were sorted to be negative for the expression of the lineage surface markers CD11c, CD19, CD56, CD141 and CD303 and additionally had the following surface phenotypes: DN1 (CD4-CD8-CD7+CD1a-CD161-CD38-); DN2 (CD4-CD8-CD7+CD1a-CD161-CD38+CD3-TCRab-); DN3 (CD4-CD8-CD7+CD1a+); ISP (CD4+CD8-CD3-TCRab-CD1a+); DPE (CD4+CD8+TCRab-CD69-); DPL (CD4+CD8+TCRab+CD69+); SP4 (CD4+CD8-); SP8 (CD4-CD8+). Samples were sorted from 2-4 pediatric patients undergoing heart surgery.

  Dataset EGAD50000001599

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  RNA-Seq data for 197 CD14-positive, CD16-negative classical monocyte sample(s). 197 run(s), 197 experiment(s), 197 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002674

• Transcriptome profiling of three giant cell tumour of bone (GCTB) cell lines

  This dataset contains RNA-seq data of giant cell tumour of bone (GCTB) cell lines (n=3). Cell lines consist of neoplastic "stromal" cells harboring a heterozygous H3F3A p.G34W mutation. RNA-seq was performed on the BGISEQ-500 platform (PE100) and uploaded data contains fastq files, vcf files, and gene expression values (TPM). Cell lines, data generation, and data analysis are described in the following publication: Venneker et al., Histone deacetylase inhibitors as a therapeutic strategy to eliminate neoplastic “stromal” cells from giant cell tumors of bone, 2022.

  Dataset EGAD00001009074

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD4-positive, alpha-beta T cell, on genome GRCh37)

  RNA-Seq data for 212 CD4-positive, alpha-beta T cell sample(s). 212 run(s), 212 experiment(s), 212 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002671

• Paired RNA-Seq was performed on 125 samples of low grade pediatric glioma

  Paired RNA-Seq was performed on 125 samples of low grade pediatric glioma. The sequencing was done with Illumina Novaseq 6000 and the Illumina TruSeq stranded mRNA kit.

  Dataset EGAD00001010171

• BLUEPRINT release August 2016, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  RNA-Seq data for 6 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 24 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002339

• BLUEPRINT release August 2014, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  RNA-Seq data for 4 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 22 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000903

• BLUEPRINT release January 2015, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  RNA-Seq data for 5 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 23 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001165

• BLUEPRINT release August 2015, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  RNA-Seq data for 5 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 23 run(s), 5 experiment(s), 5 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001534

• Epigenome cohort 30 Patient DNA and RNA

  This dataset includes RNA-seq, DNA and Chip-Seq data of samples from our paper.

  Dataset EGAD00001009041

• scRNA-seq of HSPC treated with gemcitabine and carbplatin

  The study used cryopreserved hematopoietic stem and progenitor cells (HSPCs) harvested from one patient with chronic myelogenous leukemia (CML). The cells were thawed and acclimatized for 48 hours in StemMACS HSC Expansion Media XF (Miltenyi Biotec) supplemented with StemMACS HSC Expansion Cocktail (Miltenyi Biotec) at 37°C in a humidified atmosphere containing 5% CO2. 4 samples of 2000000 HSPCs in 2 ml media each were then prepared and treated for 24 hours: carboplatin-high: 150 µg/ml carboplatin carboplatin-low: 18.75 µg/ml carboplatin gemcitabine: 25 ng/ml gemcitabine control: no drug Single-cells were subsequently extracted using the ddSEQ™ Single-Cell Isolator (Bio-Rad) and later sequenced using the SureCell™ Whole Transcriptome Analysis 3' Library Prep Kit (Illumina) on the NextSeq 500 System (Illumina) using the NextSeq 500/550 High Output Kit v2.5 150 Cycles (Illumina) all following the manufacturer's instructions. FASTQ-files were then processed following the ddSeeker (Romagnoli, D., et al., BMC Genomics 2018, doi:10.1186/s12864-018-5249-x) and Drop-seq (Macosko, E.Z., et al., Cell 2015, doi:10.1016/j.cell.2015.05.002) protocols for processing scRNA-seq data to yield the final digital gene expression for each cell.

  Study EGAS00001004381

• Single-cell RNA-seq of bronchoalveolar lavage (BAL) fluid of late stage severe COVID-19 patients

  COVID-19-induced ‘acute respiratory distress syndrome’ (ARDS) is associated with prolonged respiratory failure and high mortality, but the mechanistic basis of lung injury remains incompletely understood. Here, we analyzed pulmonary immune responses and lung pathology in two cohorts of patients with COVID-19 ARDS using functional single cell genomics, immunohistology and electron microscopy. We describe an accumulation of CD163-expressing monocyte-derived macrophages, that acquired a profibrotic transcriptional phenotype during COVID-19 ARDS. Gene set enrichment and computational data integration revealed a significant similarity between COVID-19-associated macrophages and profibrotic macrophage populations identified in idiopathic pulmonary fibrosis. COVID-19 ARDS was associated with clinical, radiographic, histopathological, and ultrastructural hallmarks of pulmonary fibrosis. Exposure of human monocytes to SARS-CoV-2, but not Influenza A virus or viral RNA analogs, was sufficient to induce a similar profibrotic phenotype in vitro. In conclusion, we demonstrate that SARS-CoV-2 triggers profibrotic macrophage responses and pronounced fibroproliferative ARDS.

  Study EGAS00001005634

• Expression profiling of pediatric brain tumors Embryonal Tumor with Multilayered Rosettes (ETMR)

  RNA was prepared using the IlluminaTruSeq RNA sample preparation kit for poly-adenylated mRNA with an average of 97.64 million reads per sample respectively

  Dataset EGAD00001004803

• RNA-sequencing (Illumina HiSeq 4000) of tumor-stage mycosis fungoides

  This dataset contains RNA-sequencing data of tumors from 8 patients with mycosis fungoides. The data was generated using the Illumina HiSeq 4000 platform.

  Dataset EGAD00001003983

• Whole Genome Sequencing in the Inner City Asthma Consortium (ICAC) Cohorts

  We performed whole-genome sequencing on individuals from the Asthma Phenotypes in the Inner City (APIC) and Urban Environment and Childhood Asthma (URECA) study cohorts, which consist of children with asthma who live in low-income neighborhoods across 10 U.S. cities. APIC was a one-year, prospective, observational study of children ages 6-17 with asthma. URECA was a prospective, observational study featuring a birth cohort of children with a high risk of developing asthma based on family history. We performed whole-genome sequencing on 1,035 individuals (ages 5-17 yrs; 67% Black, 25% Hispanic; 66% with MD-diagnosed asthma; APIC=508, URECA=527). Sequence read processing, quality control, and variant calling were performed using the Genome Analysis Toolkit suite (GATK v4). Variant call sites were annotated according to the filters applied in our common variant (minor allele frequency &#8805; 1%) association studies, based on predicted false positive rates, genotype quality and depth, and population-adjusted Hardy-Weinberg equilibrium. Principal components of ancestry were calculated using high quality, linkage-disequilibrium-pruned single-nucleotide variants, accounting for subject relatedness, using PC-Air and PC-Relate.

  Study phs002921

• WTCCC case-control study for Breast cancer

  WTCCC genome-wide case-control association study for Breast cancer (BC) using the 1958 British Birth Cohort collection as controls.

  Study EGAS00000000024