15028 results for "cancer studies using rna-seq"

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• Differential expression in clear cell renal cell carcinoma

  To investigate the levels of gene expression in clear cell renal cell carcinoma (ccRCC), we performed an RNA-seq analysis in 786-O, A-498, UM-RC-2 clear cell renal carcinoma cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq files and csv files with the differential expression results. Differential expression was calculated by the RNAflow pipeline (DEseq2), and log fold changes are calculated with respect to the normal cell line (HK-2), with separate results between normoxic and hypoxic datasets.

  Dataset EGAD50000001883

• ScRNA-seq of PBMC and whole blood samples reveales 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.

  Dataset EGAD00001006550

• Unravelling the contribution of HIF pathway and its therapeutic potential in human AML leukemia-initiating cells

  We performed single cell RNA sequencing (scRNA-seq) from bone marrow on 11 pediatric (0-14 years-old) and adolescent and young adult (AYA) (15-39 years-old) de novo AML samples (Dx) (4 inv(16), 3 t(8;21) and 4 rMLL). In addition, for some patients also relapse sample was sequenced (2 inv(16), 2 t(8;21) and 3 rMLL). Cells were sorted into CD34+/CD38- and CD34-/CD38+ and sequenced separately.

  Dataset EGAD00001008514

• G-SAM: Transcriptional Evolution of Glioblastomas Treated With Standard of Care

  Collection of mostly matching primary and recurrent glioblastoma RNA-seq sample pairs, also matching with an earlier DNA sequencing study

  Dataset EGAD00001007860

• Genetic Discovery and Application in a Clinical Setting: Continuing a Partnership (eMERGE Phase II)

  The electronic Medical Records and Genomics (eMERGE) Network is a consortium of ten participating sites funded by the NHGRI to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 19,000 individuals using EMR-derived phenotypes and DNA from linked Biorepositories. The eMERGE Network brings together researchers with a wide range of expertise in genomics, statistics, ethics, informatics, and clinical medicine from leading medical research institutions across the country. Each center participating in the consortium is uniquely situated to provide critical resources to this highly collaborative and productive network. Each site combines a biobank or study cohort with extensive genomic data and access to clinical data derived from electronic medical records. Sites are geographically dispersed and have diverse patient populations, including two sites focusing specifically on pediatrics. The eMERGE Network is comprised of 9 sites and one coordinating center. Each site maintains its own biorepository where DNA specimens are linked to phenotypic data contained within EMRs. Children's Hospital of Pennsylvania, PI: Hakon Hakonarson, MD, PhD Cincinnati Children's Medical Center with Boston Children's Hospital, PI: John Harley, MD, PhD - CCHMC and Ingrid Holm, MD, MPH - BCH Geisinger Health System, PI: David Carey, PhD and Marc Williams, MD Group Health Cooperative with University of Washington, PI: Eric Larson, MD, MPH - GHC and Gail Jarvik, MD, PhD - UW Marshfield Clinic with Essentia Institute of Rural Health, PI: Catherine McCarty, PhD, MPH - Essentia and Murray Brilliant, PhD - Marshfield Mayo Clinic, PI: Christopher Chute, MD, DrPH and Iftikhar Kullo, MD Icahn School of Medicine at Mount Sinai, PI: Erwin Bottinger, MD Northwestern University, PI: Rex Chisholm, PhD and Maureen Smith, MS Vanderbilt University, PI: Dan Roden, MD eMERGE Coordinating Center - Vanderbilt University, PI: Paul Harris, PhD Using electronic phenotyping methods, the consortium used DNA samples from all participating sites to explore the genetic determinants of red cell indices, white blood count (WBC) differential, diabetic retinopathy, height, serum lipid levels, specifically total cholesterol, HDL (high density lipoprotein), LDL (low density lipoprotein), and triglycerides, and autoimmune hypothyroidism as well as using the phenome-wide association study (PheWAS) paradigm to replicate and discover relationships between targeted genotypes with multiple phenotypes.

  Study phs000948

• Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR and PEAR-2)

  The primary aim of the Pharmacogenomic Evaluation of Antihypertensive Responses grant (funded by NIH Pharmacogenomic Research Network grant U01 GM074492) was to identify genetic determinants of blood pressure response and adverse events after antihypertensive treatments. Two different clinical trials with genomic information available were included: PEAR-1 and PEAR-2 studies. The PEAR-1 study (clinicaltrials.gov identifier NCT00246519) was a randomized controlled clinical trial evaluating genetic determinants of BP responses and adverse metabolic responses to atenolol and hydrochlorothiazide (HCTZ) monotherapy and in combination (PMID: 19249413). Briefly, PEAR-1 recruited 768 hypertension individuals with uncomplicated hypertension who were randomized to either monotherapy of atenolol 50 mg daily or HCTZ 12.5 mg daily for 3 weeks, followed by dose titration to 100 mg and 25 mg daily, then the combination therapy. BP and metabolic responses to monotherapy and combination therapy were assessed after an average of 9 weeks of antihypertensive treatment. BP was measured using three different methods: home, office and ambulatory. For the BP analysis, a composite weighted average of the office, home, ambulatory daytime and nighttime BP responses was calculated based on the row sums of the inverse of the inter-method covariance matrices. Genomic DNA from PEAR-1 participants was genotyped using the Illumina Human Omni1MQuad BeadChip (Illumina, San Diego, CA, USA). The PEAR-2 study was a multicenter sequential monotherapy clinical trial (clinicaltrials.gov identifier NCT01203852) evaluating genetic determinants of BP response to metoprolol monotherapy and chlorthalidone monotherapy. After a washout period (if necessary), eligible hypertensive patients with uncomplicated hypertension received metoprolol tartrate 50 mg twice daily for 3 weeks and the dose was increased to 100 mg twice daily for an additional six weeks if an inadequate response was observed (>120/70 mm Hg and heart rate >55 beats/min). After second washout period, patients received chlorthalidone monotherapy. Home and office BP measurements were collected in PEAR-2 study. We have previously demonstrated that home BP is the more informative single BP measurement compared to the office BP measurement. Therefore, home BP is the phenotype used for the genome-wide association analysis for PEAR-2. PEAR-2 samples were genotyped using the Illumina Human Omni2.5S Beadchip (Illumina, San Diego, CA, USA).

  Study phs000649

• National Institute of Arthritis and Musculoskeletal and Skin Diseases and Istanbul Faculty of Medicine Genome-wide Association Study of Behçet's Disease (Turkish)

  IntroductionBehçet's disease (BD) is a genetically complex multisystem disease of unknown etiology, characterized by recurrent inflammatory attacks affecting orogenital mucosa, eyes, skin, joints, blood vessels, and less frequently, the central nervous system and gastrointestinal tract. Family studies suggest a genetically complex contribution to BD. With the exception of HLA-B51, which explains less than 20% of the genetic risk, the identities of alleles that are responsible for the complex inheritance of this disease have remained unclear. AimTo identify genes that contribute to BD susceptibility. MethodsA genome-wide association study was undertaken with 311,459 informative and high quality SNPs in a collection of 1215 BD patients and 1278 healthy controls from Turkey using a beadchip microarray assay (Infinium SNP genotype assay, Illumina). HLA-B types were determined with a reverse sequence-specific oligonucleotide method (One Lambda). Regions with evidence for association were fine-mapped using Sequenom iPLEX gold assays. Disease-associated SNPs were genotyped in additional ethnically matched case/control collections from diverse genetic backgrounds, including a total of 2430 cases and 2660 controls, using TaqMan SNP genotype assays. Association data were combined in a meta-analysis of all the collections. ResultsWe confirmed the known association with HLA-B51 and found evidence for a second, independent susceptibility locus in the Class I region of the MHC. In addition, we identified one SNP with genome-wide evidence for disease association (P < 5.0 x 10-8) within the gene encoding the immunoregulatory cytokine, interleukin-10 (IL10). A meta-analysis of the data from all the collections established associations with the IL10 variant (rs1518111, P = 3.54 x 10-18, odds ratio 1.45 with 95% confidence interval 1.34 to 1.58) and with a variant located between the interleukin-23 receptor (IL23R) and interleukin 12 receptor β2 (IL12RB2) genes (rs924080, P = 6.69 x 10-9, odds ratio 1.28 with 95% confidence interval 1.18 to 1.39). The disease-associated IL10 variant was associated with diminished mRNA expression and low protein production by cells obtained from healthy blood donors. ConclusionsThese data suggest that genetically encoded low production of IL-10 increases risk of BD and suggest novel interventional targets in the IL-10 and IL-23 pathways. Note: The submitted data are the genotypes of the 311,459 SNPs in 1215 cases and 1278 controls.

  Study phs000272

• 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

• 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

• Autism Post-Mortem Brain RNA-Sequencing: SRRM4 Splicing Study

  Purpose: The goal of this study was to assess the status of splicing changes in microexons in the cortex of individuals with autism. Methods: We performed RiboZero Gold (rRNA depleted) 50bp PE RNA-seq in a larger set of case and control samples to define 12 autism and 12 control samples showing the greatest global differential gene expression change. These samples, which show differential expression of the splicing regulator SRRM4, were used to evaluate global splicing changes. Results: Within these samples, 126 of 504 (30%) detected alternative microexons display, a mean ΔPSI > 10 between ASD and control subjects of which 113 (90%) also display neural-differential regulation. By contrast, only 825 of 15,405 (5.4%) longer (i.e. > 27 nt) exons show such misregulation, of which 285 (35%) correspond to neural-regulated exons. Notably, we also observe significantly higher correlations between microexon inclusion and nSR100 mRNA expression levels across the stratified ASD samples and controls, for those microexons regulated by nSR100 relative to those microexons that are not regulated by this factor (p=1.4x10-7, Wilcoxon Sum Rank test). Conclusions: These data suggest microexon regulation is a potentially important mechanism underlying ASD and likely other neurodevelopmental disorders.

  Study phs000872

• RNA-seq data from 224 advanced prostate tumors generated by the West Coast Dream Team

  224 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node.

  Dataset EGAD00001008487

• RNA-seq data from 164 advanced prostate tumors generated by the West Coast Dream Team including 42 paired samles

  164 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node. 42 pairs prior to enzalutamide treatment and at progression from 21 patients are included.

  Dataset EGAD00001009065

• TONIC study Whole Exome Sequencing

  Paired-end whole exome sequencing of 50 TNBC breast cancer metastasis samples and matched normal samples obtained from 50 unique patients assayed at study baseline (directly after patient randomization). The included raw sequencing data (fastq-format) were generated using Illumina HiSeq2500 instruments.

  Dataset EGAD00001004857

• CancerSEEK ctDNA FASTQ files

  Sequencing data from 1,005 cancer patients and 812 healthy controls. All samples prepared using Safe-SeqS technology and sequenced on an Illumina MiSeq and/or HiSeq instrument. Paired FASTQ files for correspond to read 1 and the index read present (R and I respectively).

  Dataset EGAD00001003931