12216 results for "cancer rna-seq"

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• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003085

• Genome and transcriptome sequence data from a pancreatic neuroendocrine cancer patient

  Genome and transcriptome sequence data from a pancreatic neuroendocrine cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003087

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003088

• Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

  Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

  Dataset EGAD00001005035

• Whole-genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from long-term survivors.

  Whole-genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from long-term survivors performed as part of the Multidisciplinary Ovarian Cancer Outcomes Group (MOCOG) study. The dataset includes fastq files from 58 HGSC tumours (53 primary tumours and 5 recurrent tumours) and 53 matched normals from 53 long-term survivor patients. Sequence libraries were generated from tumour and matched normal genomic DNA using the KAPA HyperPrep PCR-free library preparation kit (Roche) according to manufacturer’s instructions. Sequencing was carried out by the Kinghorn Centre for Clinical Genomics Sequencing Laboratory (Sydney, Australia) on the HiSeq X Ten System (Illumina) to a minimum base coverage of 30-fold for normal DNA and 60-fold for tumour DNA samples.

  Dataset EGAD00001009398

• CRUK-ICGC Prostate DNA Methylation Sequencing Dataset (Prostatectomy Batches 1-6)

  This dataset includes Illumina EPIC Capture Sequencing Data of 376 samples from 188 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy, with matched pathologically assessed non-cancer control material. This DNA methylation data includes donors and samples included in previously published WGS datasets (from CRUK-ICGC batches 1 to 3 [EGAD00001001116] and batches 4 to 6 [EGAD00001003225]; including the majority of donors used in Wedge et al, Nature Genetics 2018 [PMID: 29662167]). The targeted DNA methylation sequencing data in this EGA dataset were generated using the Illumina TruSeq methyl capture method (EPICseq), covering over 3.3 million CpGs in the human genome, representing a total targeted hybridisation capture panel of 107Mbp. According to the EPICseq protocol, DNA samples extracted from prostatectomy tissue samples were enriched for target regions using hybridisation capture, prior to bisulfite conversion, amplification and sequencing in pools of 12 samples (150 single end reads over two Illumina HiSeq4000 lanes). This approach generated DNA methylation profiles from prostate cancer and control samples at base-pair resolution across millions of CpGs in the human genome.

  Dataset EGAD00001010184

• Common Fund (CF) Genotype-Tissue Expression Project (GTEx)

  Lay Description The aim of the Genotype-Tissue Expression (GTEx) Project is to increase our understanding of how changes in our genes affect human health and disease with the ultimate goal of improving health care for future generations. GTEx will create a database that researchers can use to study how inherited changes in genes lead to common diseases. GTEx researchers are studying genes in different tissues obtained from many different people. The GTEx project also includes a study of the GTEx donor consent process - this study will help ensure that the consent process and other aspects of the project effectively address the concerns and expectations of participants in the study. GTEx is a pioneering project that uses state-of-the-art protocols for obtaining and storing a large range of organs and tissues, and for testing them in the lab. Until now, no project has analyzed genetic variation and expression in as many tissues from the same person in such a large population as planned for GTEx. Scientific Description Understanding the role of variation in the human genome is crucial to elucidating genetic contributions to human health and disease. Despite the results of genome-wide association studies (GWAS) documenting strong statistical associations between genetic variation and human traits, the functional role for most of these variants is largely unexplained. Nearly 90% of these GWAS-implicated sites lie outside of protein-coding sequences, suggesting that these variants might regulate gene expression. The goal of the Genotype-Tissue Expression (GTEx) project is to establish a resource database and tissue biobank in which to study the relationship between genetic variation and gene expression and other molecular phenotypes in reference/non-diseased tissues. The ultimate resource will include approximately 960 post-mortem donors with several dozen tissues from each, a resource large enough to study both cis- and trans- gene expression quantitative trait loci (eQTLs). Some tissue will also be banked for additional molecular analyses. To request biosamples, please see the Biobank page for more information. GTEx was initially funded as a 2-year pilot project by the NIH Common Fund (CF) in 2010, and has been scaled up after demonstration of feasibility. The project will collect and analyze RNA levels in many different human tissues and each donor will be characterized for germline genetic variation through dense genotyping arrays and sequencing of either whole exomes or whole genomes. By treating RNA expression levels as quantitative traits, eQTLs will be identified as sites containing genetic variation that correlate with changes in RNA expression. Such eQTLs have been associated with 4%-12% of expressed human genes, and with common complex human diseases, including obesity, atherosclerosis, type 2 diabetes, Crohn's disease, and asthma. Additionally, few studies have examined the tissue specificity of eQTLs. A subset of banked tissue samples will also be analyzed for other molecular phenotypes, such as DNA methylation, DNaseI hypersensitivity sites, and proteomics. The GTEx project will thus serve as a resource database and tissue bank for many future studies, especially for understanding the functional basis of inherited susceptibility to disease. All GTEx releases since Version 5 follow the NIH Genomic Data Sharing (GDS) Policy whereby there are no restrictions on use or publication after release. Additional information about the GTEx Data Release and Publication policy can be found on the GTEx Data Portal at www.gtexportal.org.

  Study phs000424

• ChIP-seq data in MSC_Pat and EWIma1 (FLI1 & H3K27ac)

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic and epigenetic hallmarks of EwS.

  Study EGAS50000001172

• Transcriptome and epigenome characterization of BMP signaling effects on H3.3K27M DIPG

  We profiled transcriptome and epigenome of BMP signaling effects on H3.3K27M DIPG.

  Dataset EGAD00001007768

• WGBS Discovery Samples

  The dataset contains valuable genomic data from a discovery cohort consisting of 29 individuals. This cohort is comprised of 8 healthy individuals (control), 8 patients with ST-segment elevation myocardial infarction (STEMI), 7 patients with non-ST-segment elevation myocardial infarction (NSTEMI), and 6 patients with unstable angina (UA). The genomic data was obtained by isolating cell-free circulating DNA (ccfDNA) and subjecting it to bisulfite conversion using a low-input BS-seq (PBAT) protocol. Sequencing was done on the Novaseq 6000 platform.

  Dataset EGAD00001010935

• Single-Cell Multiomics of the Immune Microenvironment in T-Cell Acute Lymphoblastic Leukemia

  We present single-cell transcriptome and surface protein expression (CITE-seq) data from four healthy donors and fifteen pediatric T cell acute lymphoblastic leukemia (T-ALL) patients at diagnosis and at different treatment timepoints (days 1 – 6 and at time of remission). Mononuclear cells from peripheral blood (PB; longitudinal) or bone marrow (BM; diagnosis only) were isolated and CD45high immune cells and CD45dimCD7+ malignant cells were sorted and subsequently pooled to enrich for immune cells. For comparison,CD45high immune cells from four healthy donors were also sorted. Single-cell sequencing of the transcriptome and surface protein expression (204 antibodies) was performed using the 10x Genomics platform.Multiomics analyses resulted in the identification of a T-ALL subgroup characterized by a remodeled immune microenvironment at initial diagnosis. This immune landscape is dominated by the presence of non-malignant CD4-CD8-TCRab T cells that interact with CXCL16 expressing non-classical monocytes. Leukemia cell intrinsic transcriptional rewiring in these patients is associated with activation of Rap1 signaling.

  Study phs004269

• TGF-β signaling mediates microglial resilience to spatiotemporally restricted myelin degeneration

  Microglia survey and regulate central nervous system myelination during embryonic development and adult homeostasis. However, whether microglia-myelin interactions are spatiotemporally regulated remains unexplored. By examining spinal cord white matter tracts, we found that myelin degeneration was particularly prominent in the dorsal column (DC) during normal aging. This was accompanied by molecular and functional changes in DC microglia as well as an upregulation of TGF-β signaling. Disrupting TGF-β signaling in microglia led to unchecked microglial responses and myelin loss in the DC, accompanied by neurological deficits exacerbated with aging. snRNA-seq revealed the emergence of a TGF-β signaling-sensitive microglial subset and a disease-associated oligodendrocyte subset, both spatially restricted to the DC. We further discovered that microglia rely on a TGFβ autocrine mechanism to prevent damage of myelin in the DC. These findings demonstrate that TGF-β signaling is indispensable for maintaining microglial resilience to myelin degeneration in the DC during the aging process. This highlights a previously unresolved checkpoint mechanism of TGF-β signaling with regional specificity and spatially restricted microglia-oligodendrocyte interactions.

  Study EGAS50000001413

• Sequencing_Acute_Myeloid_Leukaemia_

  This project will aim at sequencing and analysing three samples from a patient with acute myeloid leukaemia (AML) with t(15;17) translocation (acute promyelocytic leukaemia). The patient was treated with standard chemotherapy and samples (blood and bone marrow) taken for minimal residual disease measured during and after chemotherapy. 2-3years later the patient presented a second AML containing inv (16).In this project we will sequence both AML and normal genomes to find associated mutations This will allow unprecedented insights into the dynamics of appearance of secondary AML, since we will be able to use the MRD samples to track the emergence of the inv(16) leukaemia. We will also be able to distinguish whether the 2 leukaemias are clonally related or not. This project will entail sequencing and analysis of three samples (whole genome 30x coverage) using Hi-Seq. The funds from this grant will cover the cost of sequencing 9 lanes from the AML t(15;17) sample, 9 lanes from AML inv(16) sample and 8 lanes from the normal genome.

  Study EGAS00001000035

• Genes associated with pancreas development and function maintain open chromatin in iPSCs generated from human pancreatic beta cells

  Current in-vitro islet differentiation protocols suffer from heterogeneity and low efficiency. Induced-pluripotent stem cells (iPSCs) derived from pancreatic beta-cells (BiPSCs) preferentially differentiate towards endocrine pancreas-like cells versus those from fibroblasts (FiPSCs). We interrogated genome-wide open chromatin in BiPSCs and FiPSCs via ATAC-seq, and identified ~8.3k significant, differential open chromatin sites (DOCS) between the two iPSC subtypes (FDR<0.05). DOCS where chromatin was more accessible in BiPSCs (Bi-DOCS) were significantly enriched for known regulators of endodermal development, including bivalent and weak enhancers, and FOXA2 binding sites (FDR<0.05). Bi-DOCS were associated with genes related to pancreas development and beta-cell function, including transcription factors mutated in monogenic diabetes (PDX1, NKX2-2, HNF1A; FDR<0.05). Moreover, Bi-DOCS correlated with enhanced gene expression in BiPSC-derived definitive endoderm and pancreatic progenitor cells. Bi-DOCS therefore highlight genes and pathways governing islet-lineage commitment, which can be exploited for differentiation protocol optimisation, diabetes disease modelling, and therapeutic purposes.

  Study EGAS00001002591

• DMET Genes, Nicotine Metabolism and Prospective Abstinence

  This study (DA033813; PI: Andrew W Bergen; PMID:26132489) includes samples from two laboratory studies of nicotine metabolism. The Pharmacokinetics of Nicotine Metabolism in Twins study (PKTWIN; PI: Gary E Swan; PMID: 15527659) was based on recruitment from a twin registry (PMID: 23084148). The Integrated Research Project on Tobacco Use and Dependence (IRP; PI: Gary E Swan; PMID: 14578134) was based on recruitment from a pedigree-based longitudinal study of risk factors for substance use, the Smoking in Families study (SMOFAM; DA03706; PI: Hy Hops). These two laboratory studies (PKTWIN and IRP/SMOFAM) served as the Stage I dataset to interrogate Drug Metabolizing Enzyme and Transporter genes with a targeted SNP array for association with the Nicotine Metabolite Ratio (NMR, ratio of trans-3'-hydroxycotinine and cotinine), an established biomarker of nicotine metabolism. In addition to the laboratory studies, samples from eight RCTs (PMID: 23249876) with the NMR and smoking-related measures used to test SNPs identified in Stage I (PMID: 26132489). In a third stage, a lung cancer meta-analysis database (PMID: 24880342) was used to assess association of SNPs identified in Stage II with lung cancer. The objectives of the study were to identify novel genes and SNPs contributing to nicotine metabolism (Stage I), and to validate PK SNPs associated with the NMR from individuals participating in a clinical laboratory protocol with the NMR obtained from treatment-seeking smokers, and then to investigate association with prospective smoking cessation (Stage II). This study built upon existing studies of nicotine metabolism and randomized trials of smoking cessation therapies. Enhanced knowledge of the genes influencing nicotine metabolism and prospective abstinence may help personalize smoking cessation treatment and risk assessment for smoking-related diseases. For Stage I, both subject [fixed-dose NMR, covariates (age, BMI, ethnicity, sex, smoking status, and hormone use), and pedigree relationships] and sample (common DMET SNP genotype, genotyping quality control) data are available in this accession. The analysis protocol, quality control summaries, summary genotype, summary phenotype, and analysis results are available for Stage I, II and III samples (PMID: 26132489). Extensive discussion of the prior CYP2A6 association literature with the NMR, abstinence, smoking heaviness and lung cancer risk is available (PMID: 26132489). The NMR has previously been associated with CYP2A6 activity, response to smoking cessation treatments, and cigarette consumption. We searched for drug metabolizing enzyme and transporter (DMET) gene variation associated with the NMR and prospective abstinence in 2,946 participants of laboratory studies of nicotine metabolism and of clinical trials of smoking cessation therapies. Stage I was a meta-analysis of the association of 507 common single nucleotide polymorphisms (SNPs) at 173 DMET genes with the NMR in 449 participants of two laboratory studies. Nominally significant associations were identified in ten genes after adjustment for intragenic SNPs; CYP2A6 and two CYP2A6 SNPs attained experiment-wide significance adjusted for correlated SNPs (CYP2A6 PACT=4.1E-7, rs4803381 PACT=4.5E-5, rs1137115, PACT=1.2E-3). Stage II was mega-regression analyses of 10 DMET SNPs with pretreatment NMR and prospective abstinence in up to 2,497 participants from eight trials. rs4803381 and rs1137115 SNPs were associated with pretreatment NMR at genome-wide significance. In post-hoc analyses of CYP2A6 SNPs, we observed nominally significant association with: abstinence in one pharmacotherapy arm; cigarette consumption among all trial participants; and lung cancer in four case:control studies. CYP2A6 minor alleles were associated with reduced NMR, CPD, and lung cancer risk. We confirmed the major role that CYP2A6 plays in nicotine metabolism, and made novel findings with respect to genome-wide significance and associations with CPD, abstinence and lung cancer risk. Additional multivariate analyses with patient variables and genetic modeling will improve prediction of nicotine metabolism, disease risk and smoking cessation treatment prognosis.

  Study phs000931

• NRG-GY017: Atezolizumab before and/or with Chemoradiotherapy in Immune System Activation in Patients with Node Positive Stage IB2, II, IIIB, or IVA Cervical Cancer

  Locally advanced cervical cancer remains an area of high therapeutic unmet need, with ~50% of patients developing disease recurrence despite treatment with chemotherapy combined with radiation. Combination of immune checkpoint blockade with chemoradiation has been explored in this setting, but optimal sequencing of these modalities is unknown. To address this question, we developed and conducted the NCI sponsored trial “Anti PD-L1 (Atezolizumab) as an Immune Primer and Concurrently with Extended Field Chemoradiotherapy for Node Positive Locally Advanced Cervical Cancer”, randomizing patients to atezolizumab administration prior to and concurrent with chemoradiation therapy (CRT) vs. concurrent with CRT (NRG-GY017; N=40, ClinicalTrials.gov Identifier: NCT03738228). Patients were randomized to atezolizumab neoadjuvant and concurrent (Arm A) or concurrent with CRT (Arm B). The study closed to successful accrual of 36 evaluable patients in June 2020. Out of 40 patients consented patients, 4 were never treated. The reasons for that are: 2 were screen failures, 1 withdrew consent, and 1 was not treated due to physician preference. The study incorporated comprehensive collection of pre- and on-treatment tumor biopsies as well as multitime point blood collections. T cell receptor (TCR) sequencing was performed on the tumors as well as pre- and on-treatment peripheral blood, and the data are included with dbGaP submission. Among the 36 eligible and treated patients, there were 30 (17 on Arm A and 13 on Arm B) with pre- and on-treatment peripheral TCR sequencing data. Twenty-five patients (14 in Arm A and 11 in Arm B) had additional tumor TCR sequencing data available, which enabled tracking of tumor-associated TCR clones in peripheral blood. We demonstrate that neoadjuvant atezolizumab administration results in peripheral expansion of higher proportion of tumor-associated TCR clones in Arm A than in Arm B and is associated with favorable 2-year disease-free survival (DFS). No new safety signals were identified. These findings support further evaluation of the neoadjuvant IO and CRT sequencing strategy in locally advanced cervical cancer.

  Study phs003833

• Whole genome analysis of liver cancer by long-read sequencing

  Aberrant integration of Hepatitis B virus DNA promotes major restructuring of human hepatocellular carcinoma genome architecture

  Study JGAS000361

• ICGC Breast Cancer Project

  A comprehensive characterisation and analysis of human breast cancers through genome-wide approaches including genomics, transcriptomics and epigenomics.

  Study EGAS00001001195

• Mosaic_Colorectal_Metastasis

  A comparison of the somatic variation present in a primary colorectal tumour and three different liver metastases from the same patient.

  Study EGAS00001000613

• PREDICT___Whole_Genomes

  PREDICT/Predicting individual response and resistance to VEGFR/mTOR pathway therapeutic intervention using biomarkers discovered through tumour functional genomics.

  Study EGAS00001000934

• Tumor microenvironment-induced FOXM1 regulates ovarian cancer stemness

  RNAseq from patient-derived primary tumor cells, cultured or not on organotypic cultures mimicking the tumor microenvironment

  Study EGAS50000000355

• Targeted sequencing of BRCA1 and BRCA2 genes in a Moroccan breast cancer cohort

  This dataset contains fastq files sequencing with Oxford Nanopore (MK1C) and Ion Torrent S5

  Dataset EGAD50000002560

• Sequenced IDH wildtype, untreated, human glioblastoma samples (GB-UK cohort)

  BAM files for 42 IDH wildtype, untreated, human glioblastoma samples from the GB-UK cohort, published in Noorani & Haughey et al. Cancer Discovery (2025).

  Dataset EGAD50000001649

• ST lobular manuscript dataset

  Spatial transcriptomics analysis for 43 breast cancer lobular samples. Note that there are 2 runs per sample Images and read counts will be made availalble on Zenodo upon publication.

  Dataset EGAD50000001467

• Evolutionary Trajectories of Small Cell Lung Cancer under Therapy

  We performed whole exome sequencing, whole genome sequencing and transcriptome sequencing of multiple tumor regions from 65 patients with SCLC.

  Dataset EGAD50000000243