9296 results for "cancer rna-seq"

in 56.08 milliseconds.

• COIN_CRC_GWAS

  Genotype data of 1,950 individuals from the COIN and COIN-B trials of advanced/metastatic colorectal cancer. Data provided in plink format, and has been quality controlled. Control data used was from the WTCCC2 project National Blood Donors (NBS) Cohort (EGAD00000000024).

  Dataset EGAD00010002186

• Target pilot trial

  In vitro and in vivo drug screens of tumor cells identify novel therapies for high-risk child cancer

  Dataset EGAD00001008358

• High-resolution analysis for urinary DNA jagged ends

  consists 17 cases, 7 control cases and 10 cancer cases.

  Dataset EGAD00001008594

• Dataset for breast_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 12 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008867

• Dataset for cancer_of_unknown_primary-WHOLE_GENOME

  Rare cancer sequencing data of 46 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008869

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03211

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009150

• 10x Genomics Single Cell Gene Expression for SA1035X5XB03021

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 5

  Dataset EGAD00001009153

• Single Cell Genome Sequence for DLP+ library A96130A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA609 passage 8 on DLP+ library A96130A

  Dataset EGAD00001009454

• Single Cell Genome Sequence for DLP+ library A96161A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96161A

  Dataset EGAD00001009457

• Single Cell Genome Sequence for DLP+ library A96175A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 7 on DLP+ library A96175A

  Dataset EGAD00001009461

• Single Cell Genome Sequence for DLP+ library A96180A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 6 on DLP+ library A96180A

  Dataset EGAD00001009463

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 0)

  Whole genome sequencing data of 5 High-grade serous carcinoma (HGSC) patients (6 samples) sequenced with BGI.

  Dataset EGAD00001009738

• Single Cell Genome Sequence for DLP+ library A96141A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96141A

  Dataset EGAD00001009513

• Neoadjuvant_Breast_Cancer_Validations

  This study aims to re-sequence findings from whole genome studies using a bespoke pulldown method to validate mutations in those genomes sequenced.

  Study EGAS00001000428

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 6)

  Whole genome sequencing data of 31 high-grade serous carcinoma (HGSC) patients (101 samples) sequenced with HiSeq X Ten and BGISEQ-500

  Dataset EGAD00001010202

• Organoid Derivation Project: WGS (2023-06-22)

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients. . This dataset contains all the data available for this study on 2023-06-22.

  Dataset EGAD00001011090

• Analysis of Multiparametric MR imaging and tumor tissue sampling to identify response and acquired resistance to HIF-2 inhibition in patients with advanced clear cell renal cell carcinoma enrolled in a phase 1, multiple-dose, dose-escalation trial of PT2385, a HIF-2alpha inhibitor

  Study EGAS00001003506

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 8a)

  Whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients (87 samples) sequenced with MGISEQ-2000 and HiSeq X Ten.

  Dataset EGAD00001011304

• Identification of biomarkers for prediction of efficacy of microtubule inhibitors and antifolates in non-small cell lung cancer

  Identification of predictive markers based on transcriptome modules for microtubule inhibitors of lung adenocarcinoma patients

  Study JGAS000267

• RNA Expression in Diverse Donor Derived Dermal Fibroblasts Correlates with Reprogramming to Pluripotency

  The cohort used in this study includes 36 African American (17 female, 19 male) and 36 White American (19 female, 17 male) individuals. The total cohort has a median age of 32 years, with a range of 20-64 years. The African American cohort has a median age of 34, with a range of 21-52 years. The White American cohort has a median age of 31, with a range of 20-64 years. Primary dermal fibroblast lines were derived from skin biopsies obtained from adult individuals at the NIEHS under institutional review board approved protocol human subjects 10-E-0063, "Sample Collection Registry for Quality Control of Biological and Environmental Specimens and Assay Development and Testing protocol" (ClinicalTrials.gov #NCT01087307). All participants gave written informed consent for tissue donation. Donor sex, age, and ancestry were voluntarily self-reported. Fibroblast cells were reprogrammed via lentiviral transduction using six transcription factors contained in three plasmids (ADDGENE/PSIN4-EF2-N2L, ADDGENE/PSIN4-EF2-O2S and ADDGENE/PSIN4-CMV-K2M). Reprogramming efficiency was determined by alkaline phosphatase staining of triplicate 10cm reprogrammed dishes containing colonies, which were then scanned. The saved images were analyzed with ImageJ 1.51h (Wayne Rasband, National Institutes of Health, USA) to count colonies, using color threshold adjusted and binary converted images of each dish. Triplicate plates were averaged and reported as colony counts or percent reprogramming efficiency ((# of colonies/250,000) x100). The African American cohort had reprogramming efficiencies ranging from 0.06-1.37%, with a median of 0.655%. The White American cohort had reprogramming efficiencies ranging from 0.02-1.13%, with a median of 0.455%. Our goal was to define transcriptomic heterogeneity that could be contributing to differences in reprogramming efficiency between individuals and between groups. Total RNA was obtained from dermal fibroblasts and matched iPSCs. For each sample, 500 ng total RNA was used as input for preparation of whole transcriptome rRNA depleted libraries. An adapter-ligated library was prepared with the KAPA HyperPrep Kit (KAPA Biosystems, Wilmington, MA) using Bioo Scientific NEXTflex™ DNA Barcoded Adapters (Bioo Scientific, Austin, TX, USA) according to KAPA-provided protocol. Sequencing was performed using an Illumina HiSeq 2500 following Illumina-provided protocols for 2x150 bp paired-end sequencing. Each transcriptome was sequenced to a target depth of 125 million reads. The following mean raw reads were obtained: African American dermal fibroblasts= 129,571,450; White American dermal fibroblasts= 131,939,505; African American iPSCs= 132,501,335; White American iPSCs= 134,394,164. Raw reads were aligned to hg19 using the STAR alignment tool (https://github.com/alexdobin/STAR). The following mean aligned reads were obtained: African American dermal fibroblasts= 123,315,343; White American dermal fibroblasts= 125,178,035; African American iPSCs= 123,148,312; White American iPSCs= 123,886,992. Reprinted from L. C. Mackey et al., Epigenetic Enzymes, Age, and Ancestry Regulate the Efficiency of Human iPSC Reprogramming. Stem Cells 36, 1697-1708 (2018), with permission from Wiley. Reprinted from L. S. Bisogno et al., Ancestry-dependent gene expression correlates with reprogramming to pluripotency and multiple dynamic biological processes. Science Advances 6 (47) (2020) (PMID: 33219026), with permission from AAAS.

  Study phs002341

• Influence of Genomic Landscape on Cancer Immunotherapy for Newly Diagnosed Ovarian Cancer: Biomarker Analyses from the IMagyn050 Randomized Clinical Trial

  The IMagyn050 trial (NCT03038100), which evaluated the efficacy of Atezo vs placebo (Pla) with carboplatin, paclitaxel and bevacizumab (CPB) in front line ovarian cancer patient (pts), did not meet its co-primary endpoints of PFS in ITT or PD-L1+ (Moore et al. JCO 2021). The aim of this exploratory study was to evaluate whether patients with BRCA1/2-mutated or homologous recombination-deficient (HRD) ovarian cancers benefitted from atezolizumab in the phase III IMagyn050 (NCT03038100) trial. Methods: Patients with newly diagnosed ovarian cancer were randomized to either atezolizumab or placebo with standard chemotherapy and bevacizumab. PD-L1 status of tumor-infiltrating immune cells was determined centrally (VENTANA SP142 assay). Genomic alterations, including deleterious BRCA1/2 alterations, genomic loss of heterozygosity (gLOH), tumor mutation burden (TMB), and microsatellite instability (MSI), were evaluated using the FoundationOne assay. HRD was defined as gLOH ≥16%, regardless of BRCA1/2 mutation status. Potential associations between progression-free survival (PFS) and genomic biomarkers were evaluated using standard correlation analyses and log-rank of Kaplan-Meier estimates. Results Among biomarker-evaluable samples, 22% (234/1050) harbored BRCA1/2 mutations and 46% (446/980) were HRD. Median TMB was low irrespective of BRCA1/2 or HRD. Only 3% (29/1024) had TMB ≥10 mut/Mb and 0.3% (3/1022) were MSI-high. PFS was better in BRCA2-mutated versus BRCA2-non-mutated tumors and in HRD versus proficient tumors. PD-L1 positivity (≥1% expression on immune cells) was associated with HRD but not BRCA1/2 mutations. PFS was not improved by adding atezolizumab in BRCA2-mutated or HRD tumors; there was a trend toward enhanced PFS with atezolizumab in BRCA1-mutated tumors. Conclusion Most ovarian tumors have low TMB despite BRCA1/2 mutations or HRD. Neither BRCA1/2 mutation nor HRD predicted enhanced benefit from atezolizumab. This is the first randomized double-blind trial in ovarian cancer demonstrating that genomic instability triggered by BRCA1/2 mutation or HRD is not associated with improved sensitivity to immune checkpoint inhibitors.

  Study EGAS00001006838

• 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

• Genome-Wide Predictors of Treatment-Related Toxicities in SWOG S0221 Trial

  When undergoing treatment for breast cancer, many women experience severe side effects, some of which result in treatment-related death and some that can persist for years. Little is understood regarding factors that may predict drug toxicities. Pharmacogenetics, the investigation of variants in candidate genes in drug metabolism pathways, has been used to determine susceptibility to treatment-related toxicities, as well as to cancer recurrence. Although there have been some strong and important findings using this approach, such as identification of single nucleotide polymorphisms (SNPs) that predispose to side effects associated with thiopurines and irinotecan, there has been less progress in assessment of genetic variants that predispose to toxicities resulting from the multi-drug regimen commonly used to treat breast cancer, anthracyclines (A), cyclophosphamide (C), and taxanes (T). These difficulties in identification of key gene variants may be due to the complex metabolic pathways of these drugs, the lack of rate limiting enzymes in the processes, or the limitations of single SNP analysis, rather than capturing all of the variability across the genes. In addition to drug metabolism pathways, however, there may be a number of constitutional factors or other processes that affect damage to normal tissues in the course of chemotherapy, some known or hypothesized, such as DNA repair and oxidative stress pathways, and others not yet discovered. However, there have been no clear candidate genes that account for a large part of the variation in drug or treatment response, and there are likely important genes that influence sensitivity of cells to chemotherapy through unknown pathways which have not yet been identified or hypothesized. The present technological capabilities to screen the entire genome for variants that discriminate populations allows the opportunity to identify these as yet unknown pathways, and open the doors to exciting new avenues of research into mechanisms that had not been previously considered. We conducted a genome-wide scan (GWAS) in a clinical trial (S0221), in which women with high risk breast cancer were treated with different dosing schedules of C, A and T. Blood specimens were collected and banked, and DNA extracted for genotyping on the Illumina OMNI 1M platform. The GWAS data were used to examine genetic variants significantly associated with grades 3 and 4 toxicities, including peripheral neuropathy recorded during the T segment. In S0221, toxicities were graded according to the NCI Common Toxicity Criteria for Adverse Events (CTCAE). The neurotoxicity is predominantly a distal sensory neuropathy, which is characterized by pain, numbness, tingling, and reduced functional capacity in the extremities. Other symptoms include parasthesias, ataxia, impaired vibration and joint position sense, and loss of tendon reflexes. By using a GWAS approach, it is likely that important pathways not previously considered can be revealed as important in susceptibility to treatment-related toxicities, identifying those at greatest risk for alternate drugs or dose reduction, and opening new areas of research for prevention of taxanes-related neuropathy among patients receiving chemotherapy for breast cancer.

  Study phs001428

• Monotherapy Breast Cancer

  These samples are from locally advanced breast cancers that have been treated with epirubicin monotherapy before surgery. We will sequence some samples from patients with good response to the therapy and some with poor response to the therapy.

  Dataset EGAD00001000349

• Whole genome sequence of liver cancers displaying biliary phenotype

  RIKEN collection WGS reads for 61 liver cancer and matched blood samples from 30 donors displaying biliary phenotype

  Dataset EGAD00001000809