15130 results for "cancer studies using rna-seq"

in 20.47 milliseconds.

• Genome-wide Association Study and Meta-Analysis of Ewing Sarcoma

  We combined a set of 122 French Ewing sarcoma (EWS) cases from the Institut Curie, 19 EWS cases from the National Cancer Institute (NCI) Center for Cancer Research (CCR), and 29 EWS cases from the NCI Bone Disease and Injury Study. All EWS cases were confirmed by medical record review and the presence of a specific EWSR1-ETS translocation were noted when data was available. Each participant provided informed consent and each participating study was approved by the Institutional Review Boards of their study center. DNA was extracted using standard methods from blood, saliva (Oragene), or buccal cells. All de novo genotyping of EWS cases was performed at the NCI CGR on the Illumina OmniExpress-24 v1.1 array. Genotyping was performed according to manufacturer's guidelines using the Infinium HD Assay automated protocol.

  Study phs001549

• Scottish High Grade Serous Ovarian Cancer

  Scottish HGSOC samples were collected via local Bioresource facilities at Edinburgh, Glasgow, Dundee and Aberdeen and stored in liquid Nitrogen until required. HGSOC patients were determined from pathology records and were included in the study where there was matched tumour and whole blood samples. On receipt of tumour material the tumour was processed as follows: firstly, the tumour sample was divided into two for DNA and RNA extraction. Slivers of tissue were cut from the front and rear faces of the DNA sample, then fixed in formalin and embedded in paraffin wax. Sections from the front and rear tissues from all samples were examined by H&E staining supplemented by WT1/p53 immunohistochemistry if required. Following pathology review, samples were only included if they met the following criteria: they were confirmed as HGSOC and there was greater than 40% tumour cellularity throughout the tumour, determined using the H&E sections. Somatic DNA was extracted using the Qiagen DNeasy Blood and tissue kit (cat no 69504). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including RNase digestion step). Germline DNA was extracted from 1-3ml whole blood using the Qiagen FlexiGene kit (cat no 51206) following the manufacturers recommended protocol. The resulting DNA underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as surrogate measures of DNA purity. A260/280 had to be 1.8 or greater and A260/230 had to be 2.0 or greater. Then, DNA was quantified using LifeTechnologies Qubit dsDNA BR kit (cat no Q32850) and we required a minimum of 50ul at 25ng/ul for WGS. Thirdly, DNA was diluted to 25ng/ul and a representative sample was loaded onto a 0.8% TAE gel, ran at 100v for 60mins and then imaged using a BioRad ChemiDoc imaging system to visualise the DNA quality. Only when all 4 quality control requirements were satisfied was the DNA sequenced. The DNA was sequenced at the Glasgow Precision Oncology Laboratories.

  Study EGAS00001004410

• CNCD Recall by Genotypes

  This is a DAC to handle recall by genotype studies by the conducted by the Center for Non-Communicable Disease Karachi, Pakistan.

  Dac EGAC50000000937

• Chromatin profiling of baseline and Notch inhibitor treated HCC PDX model

  We generated chromatin accessibility profiles for anti-Notch2 (n=3) and anti-gD (n=3) treated LIV78 tumors. Tumors were isolated, snap frozen in liquid nitrogen and stored at -80C. Tumor tissue was pulverized using a Covaris CP02 CryoPrep Pulverizer. Flash frozen pulverized tumor samples were sent to Active Motif to perform the ATAC-seq assay. Resulting material was quantified using the KAPA Library Quantification Kit for Illumina platforms (KAPA Biosystems), and sequenced with PE42 sequencing on the NextSeq 500 sequencer (Illumina) to produce FASTQ sequencing files.

  Dataset EGAD50000000735

• BAM files ChIP-Seq

  Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  Dataset EGAD00001001669

• Prostate cancer datasets WGS

  Low pass WGS: 48 samples (5 blood samples from 6 patient data): 22 Tumour cores and 26 normal/benign cores (Next Seq )

  Dataset EGAD00001004466

• CIDR: Genome Wide Association Study in Familial Parkinson Disease (PD)

  This proposal brings together the two largest NIH funded genetic studies focused on the identification of novel genes that influence the risk of PD. These two studies, PROGENI (PI: Tatiana Foroud; R01NS037167) and GenePD (PI: Richard Myers; R01NS036711) have been evaluating and recruiting families with two or more PD affected members for more than 8 years and represent the largest such cohorts world-wide. The combined sample has more than 1,000 PD families. Each study has used rigorous clinical criteria to assess their study participants. Unlike previous genome wide association studies (GWAS) in PD, all the PD cases in this proposal have a positive family history of disease. In the vast majority of these families, the index PD case has at least one sibling with the disease. Thus, the sample is unique for having substantial evidence for a genetic contribution to disease. The control group for this study consists of samples previously collected and maintained by the NINDS Repository. Genome-wide, single nucleotide polymorphism (SNP) genotyping services were provided by the Center for Inherited Disease Research (CIDR). Data analyses will focus on the identification of SNPs associated with PD susceptibility and the age of onset of disease.

  Study phs000126

• Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA)

  The OPPERA project has two sub-studies investigating effects of genetic, physiological, psychological and clinical factors on the risk of developing painful temporomandibular disorder (TMD). OPPERA I baseline case-control study of chronic TMJD (dbGaP study accession phs000762). This sub-study uses a case-control study design to investigate characteristics associated with chronic TMD. The parent OPPERA phenotype file contains an indicator variable (PHASE1CASECONTROL) identifying participants in this sub-study. Data users should use the relevant case-classification variable (CHRNONICTMDCASE) and apply statistical methods appropriate for case-control studies when analyzing TMJD in this sub-study. OPPERA I prospective cohort for first onset of TMJD (dbGaP study accession phs000850). This sub-study uses a prospective cohort study design to investigate characteristics that predict risk of developing first-onset TMD. The parent OPPERA phenotype file contains an indicator variable (PROSPECTIVECOHORT) identifying participants in this sub-study. Data users should use the relevant case-classification variable (INCIDENTCASE) and the relevant time-in-study variable (FOLLOWUPYEARS) when analyzing TMJD in this sub-study. It is recommended that data users apply statistical methods appropriate for cohort studies of a dynamic population (for example, Cox regression models, where INCIDENTCASE is the censoring variable and FOLLOWUPYEARS is time in study).

  Study phs000761

• Transcriptome data of WS patients and controls

  Fibroblasts of 4 WS patients and 4 sex matched controls were transformed into iPSCs, which were then differentiated to Neuroepithelial Stem Cells (NESCs), and further differentiated into neurons. RNA sequencing was performed at the NESC stage and after 4 and 8 weeks of neural development for 3 replicates per individual using the Illumina TruSeq stranded library polyA method on the NovaSeq6000 platform at NGI Stockholm. The data was preprocessed using the nf-core/rnaseq (https://nf-co.re/rnaseq) that includes quality control, data cleaning, and read alignment to GRCh38 (STAR, v2.6.1d)

  Dataset EGAD50000001728

• scRNAseq of ALS patients

  The data set contains information from 9 individuals (5 ALS + 4 controls) using single cell RNA sequencing in combination with TCR V(D)J sequencing to study the immune profile of the central nervous compartment (CSF). Sequencing was done using 10x Genomics platform (5’ scRNAseq & V(D)J Reagent Kits v1.1). 5P and TCR libraries were then pooled and for sequencing on the NovaSeq sequencer. Provided files are in .fastq.gz format and per individual four files are available (Read 1&2 and Lane 1&2).

  Dataset EGAD00001009623

• Point-of-care monitoring of head and neck cancer treatment response and recurrence development using nanopore-based ctDNA consensus sequencing

  Study EGAS00001007090

• Genomic DNA of tumor tissues, adjacent normal tissues, and peripheral blood were extracted using QIAamp DNA mini Kit (QIAGEN, cat. #51306)

  Although genomic instability, epigenetic abnormality, and gene expression dysregulation are hallmarks of colorectal cancer, these features have not been simultaneously analyzed at single cell resolution. Using optimized single cell multiomics sequencing together with multiregional sampling of the primary tumor, lymphatic and distant metastases, we provide insights beyond intratumoral heterogeneity. Genome wide DNA methylation levels were relatively consistent within a single genetic sublineage. The genome-wide DNA demethylation patterns of cancer cells were consistent in all 10 sequenced patients. The cancer cells’ DNA demethylation degrees clearly correlated with the densities of the heterochromatin-associated histone modification H3K9me3 of normal tissue, and those of repetitive element Long Interspersed Nuclear Element 1. Our work demonstrates the feasibility of reconstructing genetic lineages, and tracing their epigenomic and transcriptomic dynamics with single cell multiomics sequencing.

  Study EGAS00001003242

• An Empirical Approach Leveraging Tumorgrafts to Dissect the Tumor Microenvironment in Renal Cell Carcinoma Identifies Missing Link to Prognostic Inflammatory Factors

  We undertook an empirical approach to dissect the tumor microenvironment by developing a bulk tumor dissection algorithm, DisHet, and leveraging RNA-Seq data of tumorgrafts (patient-derived tumors implanted in mice), in which only the tumor cell component expands. We found that approximately 65% of previously defined immune signature genes are not abundantly expressed in the Renal Cell Carcinoma (RCC) microenvironment, and we identified more than two times as many novel immune/stromal transcripts. By using refined immune/stroma-specific genes and genomics, electronic medical record data and imaging data of 1084 RCC patients, we discovered a highly-inflamed pan-RCC subtype enriched for Treg cells, NK cells, Th1 cells, neutrophils, macrophages, B cells, and CD8+ T cells. This inflamed subtype (IS) is enriched for aggressive RCCs, including BAP1-deficient clear-cell and type 2 papillary tumors. Interestingly, IS is correlated with systemic manifestations of inflammation in patients such as thrombocytosis and anemia, whose pathogenesis were poorly defined and have been predictors of poor prognosis in RCC. Indeed, we discovered that IS is a strong predictor of poor survival. Lastly, our analyses show that tumor cells may drive stromal immune response. Overall, these data provide a missing link between the tumor cells, the tumor microenvironment, and systemic factors.

  Study EGAS00001002786

• National Cancer Institute (NCI) Head and Neck Cancer Study

  Head and neck cancers have well-documented associations with tobacco and alcohol exposure, but the disease develops in only a small fraction of users, which implies an important role for genetic susceptibility. Therefore, head and neck cancers are an excellent model for studying genetic susceptibility to environmental carcinogens. The primary goal of this study is to perform a comprehensive two-stage, high-density, genome-wide single-nucleotide polymorphism (SNP) analysis of head and neck cancer cases and corresponding frequency matched controls to identify novel genetic risk factors for head and neck cancer. In the study, we genotyped 2242 head and neck cancer cases and 1198 controls using Illumina HumanOmniExpress-12v1 BeadChip.

  Study phs001173

• A Population Genomics Study Using a Disease-Targeted Cell model: Integration of

  The common genetic variants associated with complex traits typically lie in non-coding DNA and may alter gene regulation in a cell type-specific manner. Consequently, the choice of tissue or cell model in the dissection of disease associations is important. We carried out an expression quantitative trait loci (eQTL) study of primary human osteoblasts (HOb) derived from 95 unrelated donors of Swedish origin, each represented by two independently derived primary lines to provide biological replication. We combined our data with publicly available information from a genome-wide association study (GWAS) of bone mineral density (BMD). The top 2000 BMD-associated SNPs were tested for cis-association of gene expression in HObs and in lymphoblastoid cell lines (LCLs) using publicly available data and showed that HObs have a significantly greater enrichment (threefold) of converging cis-eQTLs as compared to LCLs. The top 10 BMD loci with SNPs showing strong cis-effects on gene expression in HObs were selected for further validation using a staged design in two cohorts of Caucasian male subjects. All 10 variants were tested in the Swedish MrOS Cohort (n = 3014), providing evidence for two novel BMD loci (SRR and MSH3). These variants were then tested in the Rotterdam Study (n = 2090), yielding converging evidence for BMD association at the 17p13.3 SRR locus. The cis-regulatory effect was further fine-mapped to the proximal promoter of the SRR gene (rs3744270). Our results suggest that primary cells relevant to disease phenotypes complement traditional approaches for prioritization and validation of GWAS hits for follow-up studies. Reprinted from Grundberg E, Kwan T, Ge B et al., Genome Res Nov 2009, with permission from Genome Research, Cold Spring Harbor Press, PMID:19654370.

  Study phs000225

• Exploration of predictive biomarkers for postoperative recurrence of stage II/III colorectal cancer using genomic sequencing

  To identify biomarkers that can predict treatment outcomes, we compared the mutational profiles of surgically resected specimens from patients with recurrent cancer with those from patients with non-recurrent cancer. Target sequencing, whole-exome sequencing (WES), or whole-genome sequencing (WGS) was perfomed.

  Study JGAS000335

• Single-cell RNA sequencing of pediatric Hodgkin Lymphoma to study the inhibition of T cell subtypes

  Here, we applied single-cell RNA-sequencing (scRNA-seq) on isolated HRS cells and the immune cells from the same cHL tumors. This allowed us to identify genes of cell surface proteins that are consistently overexpressed in HRS cells and can potentially be used as targets for antibody-drug conjugates or CAR T cells. Finally, we identify potential interactions by which HRS cells inhibit T cells, among which the Galectin-1/CD69 and HLA-DRA/LAG3 interactions. However, high levels of inter-patient heterogeneity of the interaction strength were observed. In conclusion, this study identifies new potential therapeutic targets for cHL and highlights the importance of studying heterogeneity when identifying therapy targets.

  Study EGAS50000000432

• Transcriptome sequencing of Gingivo-buccal Cancer - ICGC India Project YR03

  This dataset pertains to transcriptome sequencing of paired RNA samples.RNA was isolated from the tumor and adjacent normal tissues of 12 patients (24 samples). We have performed rRNA removal followed by total RNA sequencing in Illumina HiSeq platform.We have uploaded TopHat2 aligned BAM files.

  Dataset EGAD00001003981

• Low T cell diversity is associated with poor outcome in bladder cancer - Single cell RNAseq and TCRseq data

  T cells are crucial effector cells in the endogenous defense against cancer, yet the clinical impact of their quantity, diversity, and dynamics remains underexplored. In this study we performed single cell RNAseq paired with single cell TCR-seq on tumor and blood samples from 4 patients (n samples = 8). The goal was to investigate T cell subtypes of expanded and non-expanded T cell clones in blood and in tumors.

  Study EGAS50000000938

• Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation

  Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expressions in unmeasured regions and tissues can enhance biologists��� histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region that is difficult to identify using raw data of spatial transcriptome alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

  Study JGAS000290

• Center for Common Disease Genomics [CCDG] - Cardiovascular: PEGASUS-TIMI 54

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules. Source: ccdg.rutgers.eduFor this study, The Broad Institute of MIT and Harvard generated genetic data for 7,481 individuals from the PEGASUS-TIMI 54 clinical trial run by Brigham and Women's Hospital TIMI study group using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all samples serving as controls.  

  Study phs002243

• Center for Common Disease Genomics [CCDG] - Cardiovascular: ENGAGE Atrial Fibrillation-TIMI 48

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1. Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfFor this study, The Broad Institute of MIT and Harvard generated genetic data for 13,667 individuals from the ENGAGE AF-TIMI 48 clinical trial run by Brigham and Women's Hospital TIMI study group using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all cases with atrial fibrillation.

  Study phs002774

• POPRES: Population Reference Sample

  POPRES version 1 and 2 Technological and scientific advances, stemming in large part from the Human Genome and HapMap projects, have made large-scale, genome-wide investigations feasible and cost-effective. These advances have the potential to dramatically impact drug discovery and development by identifying genetic factors that contribute to variation in disease risk as well as drug pharmacokinetics, treatment efficacy, and adverse drug reactions. In spite of the technological advancements, successful application in biomedical research would be limited without access to suitable sample collections. To facilitate exploratory genetic research, we have assembled a DNA resource from a large number of subjects participating in multiple studies throughout the world. This resource was initially genotyped using the Affymetrix 500K SNP panel. This project includes nearly 6,000 subjects of African American, East Asian, South Asian, Mexican, and European origin. POPRES version 3 The discovery and development of novel drugs is challenging and with high attrition rates. Selection of the right target and optimal indications for novel therapeutics represent key decision points in this process, and are often hampered by our limited understanding of the biology of the target in humans. Building a robust body of knowledge of variation within drug target genes has in several cases increased the probability of success for novel therapeutics. Our knowledge of variation within drug target genes and their influence on traits of medical interest is still very limited. In an effort to fill this gap, we resequenced the exons of 202 known or suspected drug target genes in over 16,000 well-phenotyped individuals. A total of 863,883 bases were targeted, including 351 kb of coding and 323 kb of untranslated exon regions. The sequenced subjects included 3,381 from two studies that were part of the Population Reference Sample (POPRES) project: CoLaus (N = 2,059) and LOLIPOP (N = 1,322). Genotyping data generated through the targeted next generation sequencing is available through the dbGaP.

  Study phs000145

• H3Africa - Genomic and Environmental Risk Factors for Cardiometabolic Disease in Africans

  The long-term vision of the AWI-Gen Collaborative Centre (CC) is to build sustainable capacity in Africa for research that leads to an understanding of the interplay between genetic, epigenetic and environmental risk factors for obesity and related cardiometabolic diseases (CMD) in sub-Saharan Africa. The CC will be consolidated under the auspices of the University of the Witwatersrand (Wits) and the International Network for the Demographic Evaluation of Populations and Their Health in Developing Countries (INDEPTH). It will capitalize on the unique strengths of existing longitudinal cohorts, including the urban Soweto and rural Agincourt studies in South Africa (Wits based), and the well established INDEPTH demographic health and surveillance centers in Kenya, Ghana, Burkina Faso and South Africa. The centers offer established infrastructure, trained fieldworkers, long-standing community engagement, and detailed longitudinal phenotypic data, focusing on obesity and cardiometabolic health. Key strengths are harmonized phenotyping across sites, building on strong existing cohorts, and representation of the geographic and social variability of African populations. We aim to: 1. Build sustainable infrastructure (biobanks and laboratories) and capabilities (well characterized population cohorts, genotyping and bioinformatics) for genomic research on the African continent; 2. Understand the genomic architecture of sub-Saharan populations from west, east and south Africa to guide genomic studies (genome sequencing and high throughput SNP and CNV arrays using unrelated individuals and family trios to improve the accuracy of haplotype analyses) and; 3. Investigate the independent and synergistic genomic contributions to body fat distribution (BMI, hip/waist circumference, subcutaneous and visceral fat) in these populations considering the relevant environmental and social contexts (rural/urban communities, quickly transitioning obesity prevalence, differential HIV, TB, and malaria infection histories). We will investigate the effect of obesity and fat distribution on the risk for CMD in the longitudinal cohorts.

  Study EGAS00001002482

• ctDNA quantification in Ewing sarcoma patients

  Background. Treatment stratification and response assessment in pediatric sarcomas has relied on imaging studies and surgical/histopathological evidence of vital tumor cells. Such studies and evidence collection processes often involve radiation and/or general anesthesia in children. Cell-free circulating tumor DNA (ctDNA) detection in blood plasma is one available method of so-called liquid biopsies that has been shown to correlate qualitatively and quantitatively to some extent with the existence of vital tumor cells in the body. Our clinical observational study focused on the utility and feasibility of ctDNA detection in pediatric Ewing sarcoma (EWS) as a marker of minimal residual disease (MRD). Patients and Methods. We performed whole genome sequencing to identify the exact breakpoints in tumors known to carry the EWS-FLI1 fusion gene. Patient-specific fusion breakpoints were tracked in peripheral blood plasma using digital droplet PCR (ddPCR) before, during, and after therapy in six consecutive children and young adults with EWS. Presence and levels of fusion breakpoints were correlated with clinical disease courses. The genetic changes in the tumors were defined, and inter- and intra-individual changes in the tumor DNA copy loads were observed over time. Results. We show that the detection of ctDNA in the peripheral blood of EWS patients i) is feasible in the clinical routine and ii) allows for the longitudinal real-time monitoring of MRD activity in children and young adults. Although changing ctDNA levels correlated well with clinical outcome within patients, between patients, a high variability was observed (inter-individually) for the six patients described here. Conclusions. ctDNA detection by ddPCR is a highly sensitive, specific, feasible, and highly accurate method that can be applied in EWS for follow-up assessments as an additional surrogate parameter for clinical MRD monitoring and, potentially, also for treatment stratification in the near future.

  Study EGAS00001006433