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• NHLBI TOPMed: Lung Tissue Research Consortium (LTRC)

  Chronic obstructive pulmonary disease (COPD), a disease state characterized by airflow limitation that is not fully reversible, is the third leading cause of death in the U.S. COPD is a heterogeneous syndrome, with affected individuals demonstrating marked differences in lung structure (emphysema vs. airway disease); physiology (airflow obstruction); and other clinical features (e.g., exacerbations, co-morbid illnesses). Multiple genomic regions influencing COPD susceptibility have been identified by genome-wide association studies (GWAS), and rare coding variants can also influence risk for COPD. However, only a small percentage of the estimated heritability for COPD risk can be explained by known genetic loci. Like most complex diseases, COPD is influenced by multiple genetic determinants (each with modest individual effects). Emerging evidence supports the paradigm that complex disease genetic determinants are part of a network of interacting genes and proteins; perturbations of this network can increase disease risk. To identify this network, multiple Omics data will need to be analyzed with methods to account for nonlinear relationships and interactions between key genes and proteins. Our overall hypothesis is that integrated network analysis of genetic, transcriptomic, proteomic, and epigenetic data from biospecimens ranging from lung tissue to nasal epithelial cells to blood in highly phenotyped subjects will provide insights into COPD pathogenesis and heterogeneity. We will leverage the well-phenotyped, NHLBI-funded Lung Tissue Research Consortium (LTRC) to address these questions. We will perform multi-omics analysis in 1548 lung tissue and blood samples from the LTRC. With these multi-omics data, we will utilize a systems biology approach to understand relationships between multiple genetic determinants and multiple types of Omics data. We will begin by performing single Omics analyses in COPD vs. control lung, nasal, and blood samples. Next, we will integrate single Omics data with genetic variants identified by WGS to assist in fine mapping genetic determinants of COPD. We will then perform integrated network analysis of COPD with genetic and multiple Omics data using correlation-based, gene regulatory, and Bayesian networks. Subjects were recruited from Mayo Clinic, Universities of Colorado, Michigan, and Pittsburgh, and Temple University.

  Study phs001662

• Pharmacogenomic Interactions in Glioblastoma Cell Line Models

  Glioblastoma (GBM) is a lethal disease without effective treatments. To advance toward effective therapeutic approaches that are biomarker-driven, there is a need for new targeted agents and to develop accurate preclinical models that encompass its cellular and molecular diversity. Historical cell line models poorly represent molecular diversity of GBMs, so we developed a living tissue bank encompassing 103 patient-derived GBM cell lines (PDGCLs) as a platform for preclinical pharmacogenomic investigation at scale. Thirty-four PDGCLs were submitted to a comprehensive molecular characterization of copy number alterations and mutations using whole exome sequencing (WES) and gene expression (microarrays), and tested against a panel of 390 small molecules at sixteen different duplicated concentrations. After integrating and systematically correlating molecular alterations with drug sensitivities, we yielded 8,083,140 pharmacogenomic interactions, and discovered novel drug and biomarker combinations which help to prioritize highly effective novel candidate treatments in GBM. Our findings demonstrate the utility of deep characterization of large numbers of models from a single disease to detect complex predictors of compound sensitivity, and indicate novel therapeutic approaches for a large fraction of patients with GBM.

  Study phs001793

• Targeted panel DNA sequencing of melanomas, nevi and melanocytic tumors

  This dataset was derived from 360 formalin-fixed paraffin-embedded (FFPE) samples distributed across (i) 118 primary melanomas, (ii) 132 nevi and (iii) 110 melanocytic tumors. Next generation sequencing (NGS) libraries were prepared following the FFPE DNA Archer VariantPlex Somatic Protocol for Illumina. Input DNA was determined by the PreSeq DNA QC assay, with 100 ng of DNA used for samples with high quality scores, 200 ng for low quality scores and 300 ng for samples with bad quality scores as defined by the PreSeq DNA QC assay. NGS libraries were quantified using the KAPA Library Quantification Kit for Illumina (KK4824) and sequencing performed on the Nextseq 500/2000 without custom primers using paired-end sequencing (151bp for Read 1 and Read 2) with index reads (8bp for Index Read 1 and Index Read 2). For each sample, resulting paired-end fastq files are available as part of this dataset. Prefix for each sample name is associated with the the type of sample: NAE: nevi samples. MEL: Melanoma samples. BL: melanocytic tumor.

  Dataset EGAD50000001297

• Genetic Analysis of Substance Use Disorder Using the Indiana Biobank Data

  The goal of this study is to identify genes related to substance use disorders. The study participants were selected from the Indiana Biobank. The Indiana Biobank provides centralized processing and storage of specimens that are linked to participants' electronic medical information. Cases were defined as having any type of substance use disorders by using ICD9/10 codes, including alcohol, cannabis, cocaine, opioid, nicotine, and other substances. Controls were defined as not having any type of substance use disorders. The Indiana Biobank is part of the Indiana Clinical and Translational Sciences Institute (CTSI), a state-wide research partnership among Indiana University, Purdue University, and the University of Notre Dame.

  Study phs003025

• Determination_of_cell_specific_regulatory_enhancers_in_hematopoetic_models

  The BLUEPRINT project is a large-scale project investigating epigenetic mechanisms involved in blood formation, in health and disease. The human variation workpackage (WP10) of the project seeks to characterize the effect of common sequence variation on the epigenome status of a cell. To do this, the project will use highly purified blood cells to minimise “experimental noise” and therefore enhance the power to discover modest effects. Two peripheral blood cell types, the CD14+CD16- monocyte (an important central orchestrator of adaptive immunity and a bridge between innate and adaptive immunity) and the CD65+CD9- neutrophilic granulocyte (the frontline cell for innate immunity) have been selected for this purpose. The two types of cells will be obtained at high purity from adult blood (AB) of 200 healthy males and females, respectively. Cells will be purified by using already validated and fully operational protocols that are based on density gradient centrifugation of the buffy coat obtained from whole blood, followed by magnetic bead-based purification using monoclonal antibodies against Cluster of Differentiation (CD) lineage-specific cell surface markers. This data set contains functional genomics data for gene expression and chromatin state.

  Study EGAS00001000586

• scRNA-seq of total bone marrow and T cells from multiple myeloma long-term survivors

  scRNA This dataset contains 50 scRNA-seq samples from bone marrow aspirates of 11 multiple myeloma patients experiencing long-term survival and 3 healthy donors. For each donor, total bone marrow and CD3+ T cells were sequenced. For multiple myeloma patients, paired samples were collected at initial diagnosis and between 7-17 years after first-line therapy. Bone marrow mononuclear cells were isolated by Ficoll density gradient centrifugation. For sorting of total bone marrow cells singlet, live cells were gated and sorted, for sorting of T cells CD45+, CD3+ cells were gated and sorted on either FACSAria Fusion or FACSAria II. Single-cell RNA sequencing were generated using 10x Genomics single-cell RNAseq technology (Chromium Single Cell 3’ Solution v2) according to the manufacturer’s protocol and sequenced on an Illumina HiSeq4000 (paired end, 26 and 74 bp). Bulk RNA Singlet, live CD3+CD4- CXCR3+CD8+ and CD3+CD4- CXCR3-CD8+ cells were sorted from 7 bone marrow and 3 peripheral blood samples of 7 multiple myeloma patients using a FACSAria Fusion machine. Bulk-RNA sequencing libraries were generated using the SMART Seq Stranded Total RNA-Seq kit (Takara) and sequenced using the Illumina NovaSeq 6000 platform (2 x 100 bp).

  Dataset EGAD00001010025

• Epigenetic landscape reorganization and reactivation of embryonic development genes are associated with malignancy in IDH-mutant astrocytoma

  Accurate grading of IDH-mutant gliomas is crucial for determining patient prognosis and guiding treatment decisions. However, histological grading can be challenging, so we aimed to identify objective molecular markers. To this end, we conducted bulk RNA sequencing on primary IDH-mutant astrocytomas (n=138) from the prospective CATNON trial, which evaluated the prognostic impact of adjuvant and concurrent temozolomide. Using this data, we sought to identify molecular markers linked to increased malignancy in IDH-mutant astrocytomas to establish objective grading criteria.

  Study EGAS50000000381

• RNAseq of 76 samples from Uveal Melanoma tumors

  Hotspot mutations in the spliceosome gene SF3B1 are reported in 20% of uveal melanomas. SF3B1 is involved in 3'-splice site (3'ss) recognition during RNA splicing; however, the molecular mechanisms of its mutation have remained unclear. Here we show, using RNA-Seq analyses of uveal melanoma, that the SF3B1 R625/K666 mutation results in deregulated splicing at a subset of junctions, mostly by the use of alternative 3'ss

  Study EGAS00001002932

• Whole exome sequencing of an invasive diffuse intrinsic pontine glioma sampled from different sites

  The lateral ventricle subventricular zone (SVZ) is a frequent site of high-grade glioma (HGG) spread and tumor invasion of the SVZ is a predictor of a worse clinical prognosis. A range of HGG types invade the stem cell niche of the SVZ, including both adult glioblastoma and pediatric high-grade gliomas such as diffuse intrinsic pontine glioma (DIPG). The cellular and molecular mechanisms mediating this frequent invasion of the SVZ are poorly understood. Here we demonstrate that neural precursor cell (NPC):glioma cell communication underpins the propensity of glioma to colonize the SVZ. SVZ NPCs secrete chemoattractant signals toward which glioma cells home. Biochemical and proteomic analyses of factors secreted by SVZ NPCs revealed a discrete list of candidate proteins. Necessity and sufficiency testing implicated the neurite outgrowth-promoting factor pleiotrophin, along with three required binding partners (secreted protein acidic and rich in cysteine (SPARC), SPARC-like protein 1, and heat shock protein 90B), as key mediators of this chemoattractant effect. Pleiotrophin protein expression is strongly enriched in the SVZ, and knockdown of pleiotrophin expression starkly reduced glioma invasion of the SVZ in the adult murine brain. Pleiotrophin, in complex with the three binding partners, activated the Rho/ROCK pathway in DIPG cells, and inhibition of ROCK resulted in decreased DIPG invasion toward SVZ neural precursor cell-secreted factors. These findings demonstrate a pathogenic role for neural precursor cell – glioma interactions and potential therapeutic targets to limit glioma invasion.

  Study EGAS00001002326

• Circumventing intratumoral heterogeneity to identify potential therapeutic targets in hepatocellular carcinoma. Details please contact lifuqiang@genomics and zhaoxin@genomics.cn.

  Background and aims: Intratumoral heterogeneity (ITH) challenges identifying mutations with target therapy potential whereas circulating cell-free DNAs (cfDNAs) could reflect nearly the entire mutation spectrum in given tumors. We investigated how to minimize the limit of ITH for profiling hepatocellular carcinoma (HCC).Methods: Thirty-two multi-regional HCC samples from five patients were subjected to whole exome sequencing (WES) and targeted deep sequencing (TDS). ITH extent was measured by the average percentage of non-ubiquitous mutations (present in parts of tumor regions). Matched cfDNAs were also analyzed by WES and TDS. Profiling efficiencies of single tumor specimen and cfDNA were compared and the one better depicted mutational landscape was selected to screen therapeutic targets.Results: We found variable extents of ITH in HCCs and observed branched and parallel evolution patterns. ITH level decreased at higher sequencing depth of TDS than that measured by WES (28.1% vs 34.9%, P < 0.01) but it remained unchanged upon additional samples analyzed. TDS of single tumor specimen detected an average of 70% the total mutations in HCC. Although more mutations were detected in cfDNA under TDS than WES, an average of 47.2% total HCC mutations uncovered by cfDNA suggested tissue outperform cfDNA and the latter may serve as alternative in profiling HCC genome. Consequently, TDS of single tumor tissue in 66 patients and cfDNAs in four unresectable HCCs identified 38.6% (26/66 and 1/4) patients bearing therapeutic targets.Conclusions: TDS of single tumor specimen could largely circumvent ITH to uncover mutations indicative of target therapy in HCC.

  Study EGAS00001002207