14982 results for "cancer studies using rna-seq"

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• Type 1 Diabetes Genetics Consortium (T1DGC): Case-only RNA-Seq Study

  Peripheral blood mononuclear cells (PBMC) from 82 T1D cases from the T1DGC study were fractionated by positive selection on magnetic beads into CD4+ T cells, CD8+ T cells and CD19+ B cells. RNA purification, library preparation and sequencing to an average of 50 million reads per sample were performed by the HudsonAlpha Genome Services Laboratory. The resulting dataset includes 82 subjects with data from at least one cell type; sequence data from all 3 cell types is available from 79 subjects. The individuals in this study can be linked to the phs000911 T1DGC ImmunoChip study via subject ids to obtain both genotypic and phenotypic information, including genotypes used for expression quantitative trait locus analysis.

  Study phs001426

• DAC for BillionToOne

  This is the Data Access Committee for studies published by BillionToOne.

  Dac EGAC50000000418

• Recalibrated whole-exome sequencing alignment data of papillary thyroid cancer of Saudi Arabia

  The dataset consists of samples from papillary thyroid cancer patients. A total of 11 DNA samples from blood/normal and cancer tissue are subjected to whole exome sequencing using Illumina. The fastq files generated were aligned with reference genome ‘hg19’, duplicates were marked, realignment around indels and quality recalibration were performed to produce good quality variants. The recalibrated “.bam” files are included with this dataset.

  Dataset EGAD00001004490

• Targeted sequencing of cell-free DNA and white blood cells from 24 men with metastatic prostate cancer

  This dataset consists of aligned DNA sequencing data in BAM file format from cell-free DNA and white blood cells from 24 men with metastatic prostate cancer. One cell-free DNA sample and one white blood cell sample is available for each patient, resulting in 48 total BAM files in this dataset. The sequencing was performed using a hybrid capture-based targeted panel of 73 prostate cancer driver genes.

  Dataset EGAD00001004486

• Recalibrated whole-exome sequencing alignment files of Saudi papillary thyroid cancer

  The dataset consists of samples from papillary thyroid cancer patients. A total of 181 DNA samples from blood/normal and cancer tissue are subjected to whole exome sequencing using Illumina. The fastq files generated were aligned with reference genome ‘hg19’, duplicates were marked, realignment around indels and quality recalibration were performed to produce good quality variants. The recalibrated “.bam” files are included with this dataset.

  Dataset EGAD00001003358

• Custom long non-coding RNA capture enhances detection sensitivity in different human sample types.

  Long non-coding RNAs (lncRNAs) are a heterogeneous group of transcripts that lack protein coding potential and display regulatory functions in various cellular processes. As a result of their cell- and cancer-specific expression patterns, lncRNAs have emerged as potential diagnostic and therapeutic targets. The accurate characterization of lncRNAs in bulk transcriptome data remains challenging due to their low abundance compared to protein coding genes. To tackle this issue, we describe a unique short-read custom lncRNA capture sequencing approach that relies on a comprehensive set of 565,878 capture probes for 49,372 human lncRNA genes. This custom lncRNA capture approach was evaluated on various sample types ranging from artificial high-quality RNA mixtures to more challenging formalin-fixed paraffin-embedded tissue and biofluid material. The custom enrichment approach allows the detection of a more diverse repertoire of lncRNAs, with better reproducibility and higher coverage compared to classic total RNA-sequencing.

  Study EGAS00001005418

• Dataset for soft_tissue_tumor-WHOLE_GENOME

  Rare cancer sequencing data of 142 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008900

• The Oral Microbiome and Head and Neck Cancer

  Oral microbiota may influence head and neck squamous cell carcinoma (HNSCC) development, potentially related to carcinogen metabolism. The human oral cavity hosts a diverse microbiota, including bacteria and fungi. We performed shotgun sequencing and ITS1 sequencing on 236 HNSCC case participants who developed HNSCC during a mean follow-up of 5.1 years and 458 matched controls who remained HNSCC-free. Oral samples were obtained from a prospective nested case-control study within three epidemiological cohorts: the American Cancer Society Cancer Prevention Study II Nutrition Cohort (ACS CPS-II), the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), and the Southern Community Cohort Study (SCCS). Control participants were selected using 2:1 frequency matching based on cohort, age, sex, race and ethnicity, and time since oral sample collection.

  Study phs004018

• Patient-derived organoids as a novel tool to study cervical cancer

  Cervical cancer is the most prevalent gynecological malignancy worldwide, often caused by infection with a high-risk human papillomavirus. Currently, there are only limited number of human-derived culture systems available that enable to study the viral infection for short-term. Here, we report on establishment of long-term human-derived organoid cultures from both healthy ecto- and endocervical epithelia that closely recapitulate the tissues of origin by maintaining the authentic histological and tissue-specific gene expression profiles. Additionally, using material from patients’ Pap-brush material, a successful panel of long-term patient-derived cancer organoids was established that maintain the causative viral infection in vitro and show differential response to common chemotherapy regimens. This study provides a promising platform for cervical cancer research and studying direct virus-host interactions.

  Study EGAS00001004439

• Whole-Genome sequencing of hepatocellular carcinomas

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome and whole exome sequencing together with CGH-SNP, methylome and transcriptomic profiling. For this purpose, a series of 500 liver tumors are collected through the French National Liver Collection and these samples will be analyzed using the different omics technologies. The data will be deposited in the ICGC and EGA database to be publically available for the scientific community. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before. The dataset will include 50 whole genome sequencing tumor/germline pairs, of which 6 are deposited in February 2014.

  Study EGAS00001000706

• Genetic Aberrations and Subclonal Structure Impact Chronic Lymphocytic Leukemia

  Large-scale whole-exome sequencing (WES) of primary tumor samples enables the unbiased discovery of recurrent putative driver events and patterns of clonal evolution. We report the identification of 44 recurrently mutated genes and 11 recurrent CNVs through the WES of 538 chronic lymphocytic leukemia (CLL) and matched germline DNAs. These include previously unrecognized cancer drivers (e.g., RPS15, IKZF3), and collectively identify nuclear export, MYC activity and MAPK signaling as central pathways affected by somatic mutation in CLL. A clonality analysis of this large dataset further enabled the reconstruction of temporal relationships between these driver events. Several drivers were associated with shorter progression-free survival (PFS) in 280 samples that were collected prior to uniform treatment with front line chemo-immunotherapy, with mature follow up of greater than 10 years. Direct comparison between matched pretreatment and relapse CLL from 59 samples demonstrated marked clonal evolution occurring in more than 95% of these patients. Distinct patterns of clonal evolution in relationship to specific gene alteration were observed, suggesting a hierarchy of fitness amongst mutations. Thus, large WES datasets of clinically informative samples enable the discovery of novel driver genes as well as the network of relationships between the drivers and their impact on disease relapse and clinical outcome.Additionally, we performed RNA-seq for 268 CLL samples (including 26 follow-up samples) and used them to identify expression subtypes of CLL. RRBS for 30 of these samples was also generated. In an integrative analysis of genetic, transcriptomic, and epigenetic data, incorporating known and newly identified subtypes of CLL, we built new models to improve patient prognostication.

  Study phs000922

• CCDG CVD: VIRGO - Variation in Recover-Role of Gender on Outcomes of Young Acute Myocardial Infarction (AMI) Patients

  The VIRGO study is a four year research project funded by the NHLBI to study young women and men with heart attacks. A total of 2,000 women who are 18 - 55 years of age and a smaller comparison group of 1,000 similarly aged men will be enrolled in this multi-site observational study from approximately 120 different hospitals across the country. Young women have a much greater risk of dying after an acute myocardial infarction (AMI) than similarly aged men. Their mortality risk is markedly higher than that of young men, and limited data on young minority women suggest that they may have the highest risk of any young subgroup. Findings from the small number of published studies of young women with ischemic heart disease suggest that the biology, epidemiology, care, and outcomes of this group are distinct from those of men. To date, there have been no large studies of this population, even as the death toll is comparable to that from breast cancer in this country. This study will help researchers identify key factors that influence recovery from a heart attack and potentially improve the care and outcomes of young women and men with AMI. Specific Aims: To investigate the excess risk in young women with AMI and to identify key demographic, clinical, metabolic, psychosocial, health care delivery, and biological determinants of prognosis, we propose a national, prospective, observational study of 2,000 women who are 55 years or younger with AMI and a smaller comparison group of 1,000 men. Our prior work and preliminary studies indicate that the sex differences are most prominent in this age group and suggest that by 1 year after discharge, there are substantial sex differences in outcomes. We will also develop risk stratification tools that will help clinicians to identify young women with the highest and lowest risk. Specific Aim 1: Determine sex differences in outcomes following AMI. Specific Aim 2: Determine sex differences in the prevalence and prognostic importance of demographic, clinical, and psychosocial risk factors. Specific Aim 3:Determine sex differences in quality of care. Specific Aim 4: Determine sex differences in the prevalence and prognostic importance of selected biochemical biomarkers following AMI. These samples have been whole genome sequenced as part of the NHGRI's Center for Common Disease Genetics at the Broad Institute.

  Study phs001259

• Analysis of Recurrently Protected Genomic Regions in Urine Cell-Free DNA

  This study investigated fragmentation patterns in urine and plasma cell-free DNA and evaluated the relevance of such analysis for cancer diagnostics using urine samples. Specifically, we performed whole-genome sequencing at variable depths and evaluated genome-wide coverage in urine and plasma samples, relative to known genome annotation features. Tumor/germline exome sequencing data included was used to identify genome-wide copy number changes and their effect on cfDNA fragmentation in corresponding genomic regions in urine samples. Data included in this submission is whole-genome sequencing of urine and/or plasma cell-free DNA from healthy volunteers and/or cancer patients, and whole-exome sequencing of tumor DNA and germline DNA (peripheral blood cells) from cancer patients. 

  Study phs002273

• DAC for Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  Ovarian cancer is a leading cause of death from gynecological malignancies worldwide. No effective screening methods exist resulting in tumor detection at advanced stages where treatment is less effective. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women, mostly post-menopausal, from the European Union or the United States with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model that incorporated multi-analyte fragmentome data and protein measurements, we evaluated the detection of ovarian cancer in two clinical settings, detection of ovarian cancers among a healthy population, and classification of adnexal masses as benign or malignant. The combined approach detected ovarian cancer with specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I–IV, respectively (AUC=0.96, 95% CI: 0.94-0.99), including 90% of high grade serous ovarian cancers. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100% of ovarian cancers for stages I–IV (p=0.001, two-sided test of equal proportions). Additionally, our approach differentiated benign masses from ovarian cancers with high accuracy (AUC of 0.88, 95% CI=0.83-0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation.

  Dac EGAC50000000332

• Molecular investigation of BCC HHI-ICI combination therapy

  We collected skin biopsies and PBMCs of patients with advanced BCC who underwent HHI-ICI combination therapy. We analyzed the skin biopsies with STx and the PBMCs with scRNA-seq to characterize the response of the immune cells, tumor cells and the tumor microenvironment to this therapy. We were interested in immune activation upon HHI and how that synergises with subsequent ICI.

  Study EGAS50000001481

• Longitudinal genome-wide analysis of progressive chronic lymphocytic leukemia under uniform front-line therapy of pentostatin, cyclophosphamide, and rituximab

  Samples from two-center prospective phase 2 clinical trail conducted at Ohio State University (Columbus, OH) and Mayo Clinic (Rochester, MN) were analyzed in 12 cases. All patients had progressive CLL as defined by National Cancer Institute (NCI) Working Group criteria. Patients provided written informed consent for correlative studies according to the Declaration of Helsinki on an institutional review board approved protocol for the collection and use of samples for research purposes from both participating institutions. Eligible patients received a regimen consisting of pentostatin (2 mg/m2), cyclophosphamide (600 mg/m2), and rituximab (375 mg/m2) provided intravenously on day 1 of a 21-day cycle for a maximum of 6 cycles. Responses were assessed by NCI Working Group criteria and included a bone marrow evaluation and two-color flow cytometry 2 months after completion of therapy. Peripheral blood samples from these patients collected longitudinally before (Pre-Baseline), at (Baseline) and after therapy (Relapse) were analyzed for genomic heterogeneity and clonal complexity by high throughput Exome sequencing.

  Study phs000794

• Cancer cell and tumor microenvironment biomarkers associated with disease-free survival with adjuvant nivolumab in the phase 3 CheckMate 274 trial

  In the CheckMate 274 trial, adjuvant nivolumab versus placebo demonstrated an improvement in the primary endpoint of disease-free survival (DFS) in patients with high-risk muscle-invasive urothelial carcinoma after radical resection. An extensive analysis of tumor biomarkers, including their associations with DFS, was performed. Analysis of genome-wide differential gene expression and known gene signatures found that immune-related genes and pathways, in particular an IFNγ signature, were predictive of DFS in nivolumab-treated patients. Predictive and prognostic associations, respectively, were found for tumor-infiltrating CD4 and CD8 T cells. Analysis of a composite predictive model suggested that CD4 gene expression and tumor cell PD-L1 expression had the greatest contributions to predicting outcomes in nivolumab-treated patients. These results reinforce recent studies establishing the importance of biomarkers of adaptive immunity, and in particular CD4 T cells, in influencing response to PD-1/PD-L1 blockade and establish the potential predictive rather than solely prognostic nature of such findings.

  Study EGAS50000000560

• Coagulation and Fibrinolysis in a Pediatric Insulin Titration Trial

  Summary of the Design and Aims: The Coagulation and Fibrinolysis in a Pediatric Insulin Titration Trial (CAF-PINT) is an ancillary study to the HALF PINT (NCT01565941) randomized, controlled trial that was originally designed to study changes in inflammatory and thrombosis pathways in the setting of an interventional trial. The parent HALF PINT study was designed to study the impact of tight glycemic control (TGC) using an explicit insulin titration algorithm to safely achieve a normal glucose in target range of 80-110 mg/dL versus 150-180mg/dL on clinical outcomes among critically ill hyperglycemic children with Heart and Lung Failure. The CAF PINT study collected blood samples pre randomization and at 2 and 4 days after randomization. Blood samples collected in EDTA tubes were centrifuged at local sites to separate the plasma from cell pellets and frozen prior to shipment. In addition, 0.5 mL of whole blood collected in PAXgene tubes modified for use in pediatrics frozen 24 hours after collection prior to shipment.Population Information: Setting: Twenty-one academic children's hospitals (HALF-PINT) and 1 academic children's hospital (IIT-SBPP). Participants: Critically ill hyperglycemic children requiring mechanical ventilation/vasoactive support (n=293).Interventions and Exposures: Patients in HALF PINT were randomized to achieve a low target glucose (80-110 mg/dL) vs. a higher target (150-180 mg/dL). The primary trial was stopped early due to low likelihood of achieving a statistically significant difference in the primary outcomes. Molecular Technologies Employed: Plasma biomarkers were assayed on thawed plasma using a Luminex panel. RNA was extracted from PAXgene Blood RNA Kits modified for pediatric use. Extracted RNA was sequenced with the Novaseq S4 system (Illumina) to generate 2 x 150 base paired end reads to a target depth of 50 million read-pairs per sample.Principal Findings of the Study: We tested for heterogeneity of treatment effects according to baseline blood inflammatory proteins using logistic regression with individual biomarkers as interaction terms and Cox regression analysis using biomarker-derived latent classes. Children with higher inflammatory proteins including TNFR-1, IL-6, IL-8, and IL-10 had lower mortality when treated with insulin to a target glucose of 80-110 mg/dL as compared to 150-180 mg/dL (interaction p<0.05). Causal forest estimates ranged from a 40% mortality reduction to a 15% mortality increase with TGC, depending on each patient’s individual biomarker profile. Latent class categorization strongly interacted with TGC with respect to mortality (Cox regression interaction p=0.005). Specifically, patients with higher inflammation benefited from TGC (6% mortality with TGC vs. 48% mortality, p=0.004) whereas hypoinflamed patients showed a trend towards harm (14% mortality with TGC vs. 7% mortality, p=0.055).Data available through dbGaP: Transcriptomic (Gene Counts) and phenotype data

  Study phs003016

• RNA-sequencing of ex vivo exhausted human antigen-specific T cells

  Tumor-specific T cells are frequently exhausted by chronic antigenic stimulation. To explore new pathways for reinvigoration of anti-tumor immune functions, we developed a human ex vivo exhaustion model by repetitive antigenic stimulation of primary CD8 T cells. This results in T cells that resemble patient-derived T cells in tumors on a phenotypic and transcriptional level. Four human healhy donor CD8+ T cells were isolated, transduced with an NY-ESO-1 TCR lentivirus construct, stimulated in four different conditions (Trested, Ttumor, Tex, Teff) with T2 tumor cells and specific peptides over 12 days. Cells were then sorted for TCR Vbeta 13.1+ (NY-ESO-1 TCR) CD8+ CD3+ CD56- CD4- DAPI- cells. RNA-seq TruSeq libraries were generated from polyA-enriched mRNA isolated from the samples, and sequenced in paired-end mode (2x51bp) on 2 lanes of an Illumina NovaSeq 6000 flow-cell. FASTQ sequence files were generated with the Illumina RTA version 3.4.4 and Base-calling Version bcl2fastq-2.20.0.422.

  Dataset EGAD00001009754

• ScRNA-seq of PBMC and whole blood samples reveals a dysregulated myeloid cell compartment in severe COVID-19

  In a dual-center, two-cohort study, we performed single-cell RNA-sequencing of whole blood and peripheral blood mononuclear cells to determine changes in immune cell composition and activation in mild vs. severe COVID-19 over time. This study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.

  Study EGAS00001004571

• Targeted sequencing data on sequential liquid biopsy samples from CSPC patients

  Sequencing data from newly diagnosed high emtastatic burder prostate cancer patients receiving an AR pathway inhibitor (ARPI) or docetaxel. Targeted sequencing data of prostate cancer relevant genes using the PCF-SELECT capture panel. cfDNA from PreADT, baseline, on-treatment (Cycle1 to 6) taken on ARPI or Docetaxel were sequenced as well as patient-matched WBC DNA

  Dataset EGAD50000001960

• HipSci_RNASEQ_Congenital_hyperinsulinia

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Congenital hyperinsulinia patients.

  Study EGAS00001001988

• HipSci_RNASEQ_Battens

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Battens patients.

  Study EGAS00001001987

• HipSci_RNASEQ_Ataxia

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from hereditary cerebral ataxia patients.

  Study EGAS00001001992

• HipSci_RNASEQ_BPD

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Blood platelet disorders patients.

  Study EGAS00001001993

• HipSci_RNASEQ_Hypertrophic_Cardiomyopathy

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Hypertrophic Cardiomyopathy patients.

  Study EGAS00001001994

• HipSci_RNASEQ_Alport

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Alport syndrome patients.

  Study EGAS00001001986

• HipSci_RNASEQ_Macular_Dystrophy

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Macular Dystrophy patients

  Study EGAS00001001995

• HipSci_RNASEQ_Spastic_paraplegia

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Spastic paraplegia patients

  Study EGAS00001001991

• HipSci_RNASEQ_Kabuki

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from kabuki patients

  Study EGAS00001001989