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• Profiling RNA Translation in Pediatric Medulloblastoma

  This study provides RNA-sequencing and ribosome profiling data for patient-derived cell lines and patient tissue samples for children with medulloblastoma. Ribosome profiling is a variant protocol of RNA-sequencing that directly sequences ribosome-bound RNA fragments only. Associated RNA-seq and Ribo-seq data obtained separately for some cancer cell lines can be found on the NCBI SRA as PRJNA957428. Samples were processed for poly-A mRNA sequencing using the Roche Kapa Kit. Ribosome profiling was performed as described in the manuscript referenced below (Hofman et al.) and based on the article by McGlincy et al., Methods (2017). Ribo-seq data were analyzed for sample quality using RiboseQC (Calviello, Nat Struct Mol Biol, 2020). These data were used to quantify P-sites of open reading frames. RNAseq and ribo-seq data were integrated and compared to determine translational efficiency values using TPM (Ribo-seq) over TPM (RNA-seq) as the metric. Ribo-seq data on 14 samples and RNAseq data on 21 samples derived from 16 fresh-frozen surgical samples for medulloblastoma and 5 autopsy samples are available through dbGaP. A second cohort of 4 medulloblastoma samples (RNAseq, Ribo-seq) related to this study can be found on the EGA at EGAS00001007426.

  Study phs003446

• PGRN/PAT: The genomic basis for susceptibility to drug-induced long QT syndrome (diLQTS)

  The goal of this study was to search for genetic variants that could be responsible for modifying the risk of drug-induced long QT syndrome (diLQTS). diLQTS is a relatively common adverse drug event and has been a leading cause for drug relabeling and withdrawal from the market. Our hypothesis, that variants in genes which regulate electrical properties in the heart modify the risk of diLQTS, was tested by sequencing approximately 225 patients of European descent using next-generation targeted captured or whole exome sequencing. Data from cases and controls (1:2) were analyzed to identify both rare and common genetic variation.

  Study phs000808

• Cell-free DNA methylation profiling for non-invasive detection and classification of lymphoma

  Compared with traditional tissue biopsies used for lymphoma diagnosis, cell-free DNA methylation profiling offers a minimally invasive approach capable of capturing lymphoma-specific epigenetic alterations. This study investigates genome-wide methylation patterns in plasma using cell-free methylated DNA immunoprecipitation and sequencing (cfMeDIP-seq). Differential methylation analysis of discovery samples identified lymphoma-associated hypermethylated regions that were used to develop classification models for lymphoma detection. Validation analyses demonstrated high accuracy and strong associations between cfDNA methylation scores and independent measures of tumor burden and clinical outcome. These findings support cfDNA methylation profiling as a sensitive approach for non-invasive lymphoma diagnosis.

  Study EGAS50000001463

• This DAC takes care of requests for data for the Swiss epigenetic colorectal cancer cohort study, SWEPIC

  Dac EGAC00001003471

• Dataset for the spanish node

  Dataset for the spanish node

  Dataset EGAD50000000884

• University of Michigan Clinical Sequencing Exploratory Research (CSER)

  Overview. The personalization of therapy for cancer will require molecular characterization of unique and shared genetic aberrations. In particular, patients who have a sarcoma or other rare cancers and are candidates for clinical trials could potentially benefit by identifying eligibility for "targeted" drugs based on the "actionable" genes in their specific tumor. Growing technological advances in genomic sequencing has now made it possible to consider the use of sequence data in a clinical setting. For instance, comprehensive testing that includes whole exome and transcriptome sequencing may identify biomarkers for predictive or prognostic purposes and thereby inform treatment choices and prevention strategies. Thus, the translation of high throughput next generation sequencing would support a "personalized" strategy for cancer. However, the translation of clinical sequencing bears unique challenges including identifying patients who could benefit, developing informed consent and human subjects protections, outlining measurable outcomes, interpreting what results should be reported and validated, and how results should be reported. In addition, we know very little about how patients and clinicians will respond to the potentially confusing and overwhelming amount of information generated by genomic sequencing, and we lack model processes for clinically evaluating and presenting these data. For the promise of our innovative biotechnologies to be realized, "translational genomics" research that evaluates genomic applications within real-world clinical settings will be required. This proposal brings together expertise at the University of Michigan including clinical oncology, cancer genetics, genomic science/bioinformatics, clinical pathology, social and behavioral sciences, and bioethics in order to implement this clinical cancer sequencing project. Three integrated Projects have the following themes: Project 1) "Clinical Genomic Study" will identify patients with a rare cancer (i.e., 15 out of 100,000 individuals per year) who are eligible for clinical trials, consent them to the study, obtain biospecimens (tumor tissue, germline tissue), store clinical data, and assemble a multi-disciplinary Sequencing Tumor Board to deliberate on return of actionable or incidental genomic results; Project 2) "Sequencing & Analysis" will process biospecimens and perform comprehensive sequencing and analysis of tumors to identify point mutations, copy number changes, rearrangements/gene fusions, and aberrant gene expression; Project 3) "Ethics & Psychosocial Analysis" will observe the expert review process for evaluating sequence results and will examine the clinician and patient response to the informed consent process, delivery of genomic sequence results, and use of genomic results.

  Study phs000673

• Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomic Confirmatory Study of Breast, Colon, Lung, and Ovarian Tumors

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.). The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein-protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the second phase of the CPTC initiative in September 2011. Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples. These confirmatory samples contain breast, ovarian, colon, and lung tumors collected via a protocol optimized for proteomics. Specifically, ischemic time of the sample was controlled and restricted to less than 30 minutes. ACGT, Inc. produced whole exome, mRNAseq, and miRNAseq for these samples. Corresponding proteomic data are available at: https://cptac-data-portal.georgetown.edu/cptacPublic/ The study design was to profile colon, breast, ovarian, and lung tumors both genomically and proteomically. Germline DNA was obtained from blood. Normal control samples for proteomics varied by organ site: adjacent colon tissue for colon cases, contralateral breast tissue for some breast cases, and Fallopian tube fimbria for some ovarian cases. Lung cases had no normal control for proteomic analysis. All cancer samples were derived from primary and untreated tumors.

  Study phs000892

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Multi-Ethnic Study of Atherosclerosis (MESA)

  Cohort Description The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (CVD) and the risk factors that predict progression to clinically overt CVD or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Participants of this study are limited to MESA Classic participants. MESA Family and MESA Air Pollution cohorts are excluded from C4R. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 3119 MESA participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 1933 MESA participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 1058 MESA participants in C4R. Derived data includes 43 variables for up to 3283 MESA participants in C4R. Phenotype data includes 113 variables for up to 3136 MESA participants in C4R.

  Study phs003017

• Resequencing (MIPS) of candidate genes for Keratoconus (2020)

  In this study, we selected 34 candidate genes for KC based on previous Whole Exome Sequencing (WES) and the literature, and resequenced them in 745 KC patients and 810 ethnically matched controls. Data analysis was performed using the single variant association test as well as gene-based mutation burden and variance components tests. In our study, we detected enrichment of genetic variation across multiple gene-based tests for the genes COL2A1, COL5A1, TNXB, ZEB1 and ZNF469. The top hit in the Fisher’s exact test was obtained for a common variant in the COL12A1 gene. Interestingly, COL5A1, TNXB, ZNF469 and COL12A1 are all known Ehlers-Danlos Syndrome (EDS) genes. Though the co-occurrence of KC and EDS has been reported previously, this study is the first to demonstrate a consistent role of genetic variants in EDS genes in the etiology of KC. In conclusion, our data show a shared genetic etiology between KC and EDS, and clearly confirm the currently disputed role of ZNF469 in disease susceptibility for KC. Besides the role for EDS genes, we also confirm the previously reported involvement of genetic variation in ZEB1 in KC.

  Study EGAS00001004267

• DAC for present-day Central Asia genotype data at the Centre for GeoGenetics, Natural History Museum of Denmark.

  Dac EGAC00001000894