11795 results for "cancer rna-seq"

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• METSIM (METabolic Syndrome In Men) Study

  The METSIM Study includes 10,197 men, aged from 45 to 73 years, randomly selected from the population register of the town of Kuopio, Eastern Finland, and examined in 2005-2010. The aim of the study is to investigate genetic and non-genetic factors associated with the risk of type 2 diabetes (T2D), cardiovascular disease (CVD), and insulin resistance-related traits in a cross-sectional and longitudinal setting. Study protocol includes collection of data on CVD risk factors (smoking, exercise, diet, history of chronic diseases including coronary heart disease, stroke, cardiac failure, medication, history of diabetes or early onset coronary heart disease in the family), questionnaire on the FINDRISC Score, measurement of height, weight, waist, hip, blood pressure, and bioimpedance for the evaluation of fat percentage. July 2016 - The first study release (v1) included phenotype and whole exome sequencing (WES) data of n=982 participants in substudy: Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: Metabolic Syndrome in Men Study (METSIM) - phs001100.v2.p1. The second study release (v2) included phenotype data for the entire METSIM cohort and made two additional substudies available, phs000919.v1.p1 and phs000752.v1.p1. The third study release (v3) made three subcutaneous adipose biopsy substudies available, phs003385.v1.p1, phs003386.v1.p1, and phs003387.v1.p1.The fourth study release (v4) added phenotype data for the subcutaneous adipose biopsies, made two additional substudies available, phs01579.v1.p1 and phs004033.v1.p1, and is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs000743 METSIM Study. phs000752 METSIM FinMetSeq Exome Sequencing phs000919 METSIM GWAS and Exome Chip phs001100 METSIM T2D-GENES Exome Sequencingphs001579 METSIM CCDG Whole Genome Sequencingphs003385 METSIM Subcutaneous Adipose Needle Biopsy RNA-Seq phs003386 METSIM Subcutaneous Adipose Needle Biopsy ATAC-Seq phs003387 METSIM Subcutaneous Adipose Surgical Biopsy RNA-Seqphs004033 METSIM Metabolomics

  Study phs000743

• Patient-tailored design for selective co-inhibition of leukemic cell subpopulations

  The extensive primary and secondary drug resistance in many cancer types requires rational approaches to design personalized and selective combinatorial therapies that do not only show synergistic effect in overall cancer cell killing but also result in minimal toxic side effects on non-malignant cells. To address the combinatorial explosion in the number of relevant combinations, we implemented a machine learning approach that prioritizes patient-customized drug combinations with a desired synergy-efficacy-toxicity balance by combining single-cell RNA-sequencing with ex vivo single-agent testing in scarce patient-derived primary cells. When applied to two diagnostic and two refractory AML patient cases, each with a different genetic background, our integrated approach accurately predicted patient-specific combinations that were shown to result not only in synergistic cancer cell co-inhibition but were also capable of targeting specific AML cell subpopulations that emerge in differing stages of disease pathogenesis or treatment regimens. Our data-driven approach provides an unbiased means for systematic identification of personalized combinatorial regimens that selectively co-inhibit leukemic cells while avoiding inhibition of non-malignant cells, and highlight the relevance of considering cell heterogeneity for personalized cancer therapy.

  Study EGAS00001004614

• Epigenetic Control of Topoisomerase 1 by MacroH2A1.1

  DNA transactions introduce torsional constraints that pose an inherent risk to genome integrity. While topoisomerase 1 (TOP1) activity is essential for removing DNA supercoiling, aberrant stabilization of TOP1:DNA cleavage complexes (TOP1ccs) can result in cytotoxic single-stranded DNA lesions (SSLs). What protects the genome from aberrant TOP1 activity remains unknown. Using a combination of CUT&RUN and TOP1 Covalent Adduct Detection (CAD) Seq in MDA-MB-231 breast cancer cells (American Type Culture Collection, ATCC), we identified chromatin context as an essential means to ensure TOP1cc resolution at TOP1 hot spots. Through its ability to bind poly(ADP-ribose) (PAR), a protein modification required for TOP1cc repair, the histone variant macroH2A1.1 establishes a TOP1-permissive chromatin environment, while the alternatively spliced macroH2A1.2 isoform is unable to bind PAR or protect from TOP1ccs. MacroH2A1 isoform-specific analyses were based on reconstitution of macroH2A1.1 knockout cells with wild-type or PAR binding-deficient FLAG-tagged macroH2A1.1 in human breast cancer cells. Mechanistically, we find that macroH2A1.1 facilitates the recruitment of the TOP1cc repair factor XRCC1 in response to both endogenous and drug-induced topological stress. Impaired macroH2A1.1 splicing, a frequent cancer feature, was predictive of increased sensitivity to TOP1 poisons in a pharmaco-genomic screen in breast cancer cells, and macroH2A1.1 inactivation mirrored this effect in breast and ovarian cancer cells. Consistent with this, low macroH2A1.1 expression correlated with improved survival in cancer patients treated with TOP1 inhibitors (TOP1i). We propose that macroH2A1 alternative splicing serves as an epigenetic modulator of TOP1-associated genome maintenance and a potential cancer vulnerability.

  Study phs003729

• Integrated Single-Cell Genetic and Transcriptional Analysis Suggests Novel Drivers of Chronic Lymphocytic Leukemia

  Intratumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells leading to increased understanding of driving events in malignancy. Reprinted from Genome Research, with permission from Publisher.

  Study phs001372

• INTEGRATIVE MOLECULAR ANALYSIS OF SKIN TUMORS FROM CYLD CUTANEOUS SYNDROME PATIENTS

  CYLD cutaneous syndrome (CCS) is a rare autosomal dominant disorder characterized by germline CYLD mutations and by multiple benign skin tumors dependent on NF-kB pathway. We assembled a large cohort of CCS rare skin tumors that was profiled with whole exome or genome sequencing, RNA sequencing and methylation arrays to better understand genetic mechanisms of CCS tumorogenesis.

  Study EGAS50000000247

• PD-L1 blockade immunotherapy rewires cancer-induced emergency myelopoiesis

  HSPCs were sorted as CD34+ cells from bone marrow of patients with Hodgkin Lymphoma (HL). Control samples were isolated before initiating treatment.These were compared to samples from two additional HL patients who had relapsed and were being treated with nivolumab. Nivolumab was administered at a dose of 240 mg every two weeks, with BM samples collected the day before the scheduled dose. The patients receiving nivolumab were in remission at the time of BM collection. RNA was extracted using Arcturus™ PicoPure™ RNA Isolation Kit (Thermo Fisher Scientific, #12204-01) ` instructions. Paired-end sequencing was reads were generated for each sample in the Illumina Novaseq 6000 system.

  Dataset EGAD00001015403

• SCANDARE MACARON

  Among gynecological cancers, high-grade serous ovarian cancer has the highest prevalence and more than 75% of patients have advanced stage at diagnosis with a 5-year survival of 40%. When the initial complete surgical removal is not possible (60% of patients), an interval surgery can be considered after three to four cycles of neoadjuvant chemotherapy to reduce the tumor mass. However, in approximately 50% of cases the tumor has little or no response to neoadjuvant chemotherapy. Therefore, identification of potential drug targets, biomarkers and/or pathways whose modulation can help in the prevention, interception, or curing of the disease is essential to address the unmet need. Therefore, MACARON project aims to address these issues through the identification of shared neoantigens arising out of somatic alterations and aberrant transcriptional programs in ovarian cancer DNA/RNA datasets.

  Study EGAS50000000145

• Genomic Characterization CS-MATCH-0007 Arm B

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH clinical trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm B is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with HER2- activating mutations are treated with Afatinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002028

• Genomic Characterization CS-MATCH-0007 Arm Z1I

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1I is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with BRCA1, BRCA2 mutations are treated with AZD1775. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002058

• PDAC Prognosis Biomarkers in Genomic and Transcriptomic Molecular Data

  Our study was designed to identify biomarkers related to the prognosis of Pancreatic Ductal AdenoCarcinoma (PDAC) patients using genomic variants and gene expression in coding regions of the human genome (exome). PDAC is the 7th cause of cancer deaths and is among types of cancer having the poorest prognosis. To improve treatment outcomes of PDAC, biomarkers related to PDAC prognosis are needed. The goals of our study are to find genomic and transcriptomic biomarkers, which can classify prognosis subtype of PDAC patients, and eventually to predict subtypes or prognosis for each patient. In this study, we generated Whole Exome Sequencing (WES) and exome capture RNA sequencing data of 450 tumor and matched normal samples from 150 PDAC patients. Our data may be useful for understanding genomic and transcriptomic features, prognosis prediction, and precision medicine for PDAC.

  Study phs002347