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• Automated machine-learning approach for next generation profiling of sequence alterations, mutation burden, microsatellite instability, and structural variants in human cancers

  Sequence and structural alterations together with tumor mutation burden (TMB) and microsatellite instability (MSI) have been identified as biomarkers for the determination of response to targeted and immune checkpoint inhibitor therapies. However, widespread clinical adoption of these biomarkers has historically been limited due to barriers such as evidence of clinical utility and reimbursement. We have developed 2.2 Mb targeted NGS system and an automated machine-learning analysis approach (PGDx elio™ tissue complete, ETC) that has been FDA cleared for examination of 500+ cancer-related genes and 68 mononucleotide repeats for identification of sequence and structural alterations, TMB, and MSI in solid cancers in a clinical setting. We designed and trained this approach using sequence data from 4,174 cancers and >124,000 in silico alterations and evaluated the methodology in >2,550 tumor or non-cancerous normal samples. Independent analyses of ETC sequence changes in 440 formalin fixed paraffin embedded (FFPE) tumor or cell line samples using MSK-IMPACT™, FoundationOne®, and ddPCR revealed a positive percent agreement (PPA) >97% with high sensitivity as low as 3% mutant allele fraction. We observed high concordance between panel-wide and whole-exome TMB for 307 pan-cancer FFPE tumors (Pearson r=0.95, p < 0.0001) using samples with ≥20% tumor cellularity. Comparison of the mutation context and repeat-based MSI approach in ETC with a multiplex MSI PCR assay in 223 samples revealed a PPA of 99% and negative predictive agreement (NPA) >99%. We confirmed the accuracy and precision of TMB and MSI measurements across three independent laboratories (CV of <5% and average PPA >99%, respectively). Finally, evaluation of amplifications and translocations against DNA and RNA-based approaches exhibited >98% NPA and PPA of 86% and 82% respectively. These results demonstrate high analytical performance for determination of sequence and structural changes, TMB, and MSI using a targeted NGS panel and provide a scalable and facile approach for evaluating these biomarkers in a clinical laboratory.

  Study EGAS00001005556

• University of Washington Developmental Single Cell Atlas

  We set out to generate a human cell atlas of both gene expression and chromatin accessibility using tissues obtained during development. In this study, we applied an assay for single cell profiling of gene expression based on three-level combinatorial indexing (sci-RNA-seq3) to 121 fetal tissue samples representing 15 organs, altogether profiling transcription in over 4 million single cells. In parallel, we devised an improved assay for single cell profiling of chromatin accessibility also based on three-level combinatorial indexing (sci-ATAC-seq3). We applied this method to 53 fetal tissue samples representing 15 organs, altogether profiling on the order of one million single cells. From these data, we identify and characterize diverse human cell types and annotate them with respect to marker genes, expression and regulatory modules. These data comprise a rich resource for the exploration of human biology.

  Study phs002003

• Genomic Analysis of Low Grade B-Cell Lymphoma

  We included tumors from 64 newly diagnosed or untreated Low Grade B-Cell Lymphoma (LGBCL) patients, consisting of SMZL (n = 48), NMZL (n = 6), EMZL (n = 2), LPL (n = 5), and B-NOS (n = 3) in this study. Samples were selected from cases consented to the Molecular Epidemiology Resource (MER) of the University of Iowa and Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). RNA or DNA were extracted from 64 frozen LGBCLs tumors (with available matched germline DNA for N=61. For RNA sequencing, library preparation was done using the Illumina TruSeq RNA Exome Kit and sequenced with 100 nucleotide paired-end reads using the HiSeq 4000. For WES, library preparation was done using the Agilent SureSelect XT kit and sequenced with 100 nucleotide paired-end reads using the Illumina HiSeq 4000.

  Study phs002552

• HuBMAP: KULMAP - Human Kidney, Urinary Tract, and Lung Mapping Center

  The major goal of the Human Kidney, Urinary Tract, and Lung Mapping Center (KULMAP) is to generate multi-omic and spatially resolved molecular anatomical maps of the human bladder, ureter and kidneys (BUKMAP) and the lung airways and parenchyma (LAPMAP) at a single cell resolution. This entails sequencing of the transcriptomes and epigenomes of dissociated single cells in a massively parallel manner. These profiles will then inform on highly multiplexed RNA in situ imaging for spatial mapping of hundreds of molecular targets in the tissue sections, at a subcellular resolution. These spatial molecular maps will serve as scaffolds for computational registration of cell types and the associated transcriptome/chromatin maps to the tissue space. The combination of sequencing single dissociated cells and multiplexed in situ mapping will allow the construction of detailed spatial maps for these large organs.

  Study phs002249

• Genome-Wide Analysis of Splenic Marginal Zone Lymphoma

  Splenic Marginal Zone Lymphoma (SMZL) is a B-cell malignancy of unknown pathogenesis and thus orphan of targeted therapies. By integrating whole-exome sequencing and copy-number analysis of 8 paired tumor-normal DNAs from patients with SMZL, we show that the typical SMZL exome carries ~30 genetic alterations. Targeted resequencing of selected candidates in an extended panel of 40-117 samples revealed activating mutations of NOTCH2, a gene required for marginal-zone (MZ) development, as the most frequent and SMZL-specific lesion, accounting for approximately 20% of cases. Additional altered genes suggest that deregulation of signaling pathways normally involved in MZ development (NOTCH, NF-kappa B, and B-cell receptor) represents a critical event in SMZL pathogenesis. These findings have direct implications for the treatment of SMZL patients since drugs are available which can target NOTCH as well as other pathways deregulated in this disease.

  Study phs000502

• Host Response to Respiratory Infections

  In this study, we describe a strategy to identify undiagnosed respiratory viral infections through screening nasopharyngeal (NP) swabs for the chemokine CXCL10, which is highly induced in the nasopharynx as part of the host antiviral response. Using this strategy, we conducted two screens: first, we screened NP swabs collected at Yale New Haven Hospital (YNHH) in January 2017 from patients with undiagnosed respiratory viral infections and identified patients infected with seasonal coronaviruses and the relatively uncommon influenza C virus. Second, we screened samples from the beginning of March 2020 in the weeks before YNHH tested for SARS-CoV-2 and identified four patients that had undiagnosed SARS-CoV-2 infections. Sequences uploaded as part of this study include samples with rhinovirus, human coronavirus NL63, and 8 samples as part of the January 2017 screen for undiagnosed respiratory viral infections.

  Study phs002442

• Nature and Contribution of Noncoding, Regulatory Mutations in Neurodevelopmental Disorders

  This dbGaP study contains variant call files generated from whole-genome sequencing data of families with autism. The variant callers include FreeBayes, GATK, Platypus, and Strelka2. A family-level VCF file, from each caller, is provided for each family in the study. The families included in this study are from the Simons Simplex Collection (SSC), the Study of Autism Genetics Exploration (SAGE), and The Autism Simplex Collection (TASC); sequencing was performed at the New York Genome Center, as part of the Centers for Common Disease Genomics (CCDG) Consortium. The analysis to generate the variant callsets was supported by a K99 Pathway to Independence grant to Dr. Tychele Turner (1K99MH117165-01). *Access to phenotype data at the individual level for Simons Simplex Collection (SSC) subjects can be requested from SFARI Base: https://www.sfari.org/resource/sfari-base/.

  Study phs001874

• 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

• Genetics of Hypertension Associated Treatment (GenHAT) Study, Genomic Background of Blood Pressure Response to Treatment in African Americans

  The GenHAT study is an ancillary pharmacogenomics study to the Antihypertensive and Lipid Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). ALLHAT was a randomized, double-blind, multi-center trial that enrolled 42,418 participants ≥55 years of age with hypertension and at least one additional risk factor for cardiovascular disease (CVD). Participants were randomized to treatment with one of four primary antihypertensive drugs: chlorthalidone (thiazide-like diuretic), amlodipine (CCB), lisinopril (ACE-i), or doxazosin (alpha-adrenergic blocker) in a ratio of 1.7:1:1:1, respectively. Participants were followed for treatment response and CVD outcomes. The original GenHAT study (N=39,114) evaluated the association of candidate hypertensive genetic variants with CVD outcomes for participants consenting to genetic research. The current GWAS study focuses on a subset of African American GenHAT participants (n=6908).  

  Study phs002716

• Whole Genome Sequencing of Harvard University Embryonic Stem Cell Lines 63 and 64

  In this study we used next generation deep sequencing technologies to analyze the genomes of Harvard University Stem Cell lines 63 and 64. We performed 101-bp paired-end whole genome sequencing of the two cell lines using Illumina HiSeq platforms. The sequence reads obtained were analyzed for copy number and used for replication timing analysis. Our data suggests that read depth profiles can be used to map replication timing in Embryonic Stem Cells (ESCs). Further we observe that replication profiles are highly correlated across ESCs but distinct from those of other cell types such as Lymphoblastoid Cell Lines (LCLs). These results demonstrated that read depth data from whole genome sequencing can be used to study variation in replication timing within the human population and across different cell types. Whole genome sequences from HUES63 and HUES64 used for this study are being submitted.

  Study phs000825