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• Clinical and Molecular Features of Acquired Resistance to Immunotherapy in Non-Small Cell Lung Cancer

  PD-(L)1 blockade has been shown to promote durable responses in non-small cell lung cancer (NSCLC) patients and has been rapidly incorporated into the treatment regimens for many with advanced disease. Despite this, mechanisms of acquired resistance (AR) to PD-(L)1 have not been well understood. To address the clinical and molecular landscape of AR to PD-(L)1 blockade in NSCLC patients, a large clinical cohort of AR to PD-(L)1 blockade in lung cancer was examined. In conjunction, a systematic genomic and transcriptomic analysis in a subset of patients (n = 29) with available tissue samples was conducted. To investigate the molecular mechanisms of AR to PD-1 blockade from pre- and/or post-treatment tumors, microarray-based whole transcriptome expression data for 29 tumor samples, and whole exome sequencing (WES) data from 34 tumor samples was generated from this subset. Microarray data was uploaded to the Gene Expression Omnibus (GEO) database. Most AR tumors showed retained or increased inflammatory characteristics with significant upregulation of IFNγ which was suggestive of persistent albeit insufficient anti-tumor immune response. This finding expounds upon the prior pre-clinical and translational data supporting the intricate role of IFNγ in sensitivity and resistance to immunotherapy. Whereas initial IFNγ exposure may be fundamental to T cell activation (a hallmark of immune response), persistent IFNγ related effects and upregulation may potentially signal immune dysfunction and IFNγ insensitivity in contrast. The inflammatory phenotypes identified have implications for future rational development of new immunotherapy strategies for patients with AR.

  Study phs002834

• A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy

  The accurate identification and prioritization of antigenic peptides is crucial for the development of personalized cancer immunotherapies. Publicly available pipelines to predict clinical neoantigens do not allow direct integration of mass spectrometry immunopeptidomics data, which can uncover antigenic peptides derived from various canonical and non-canonical sources. To address this, we present an end-to-end clinical proteogenomic pipeline, called NeoDisc, that combines state-of-the-art publicly available and in-house software for immunopeptidomics, genomics and transcriptomics with in-silico tools for the identification, prediction, and prioritization of tumor-specific and immunogenic antigens from multiple sources, including neoantigens, viral antigens and high-confidence tumor-specific antigens.

  Study EGAS50000000228

• A Multiethnic Genome-wide Scan of Prostate Cancer

  Multiple GWA studies of prostate cancer conducted in European White populations are ongoing. These studies will continue to have a dramatic impact on our understanding of the contribution of common genetic variation on inter-individual susceptibility to this common cancer. Important questions that will remain unanswered, however, are whether all common risk alleles for prostate cancer will be revealed in studies limited to populations of European ancestry. A comprehensive examination of common genetic variation in men of Japanese, Latino, and African ancestry will be required to understand population differences in disease risk and to reveal the full spectrum of causal alleles that exist in these populations. Further, genetic and environmental diversity is likely to contribute to ethnic heterogeneity of genetic effects. Elucidating gene x gene and gene x environment interactions is also likely to provide knowledge that may be critical for understanding the contribution of genetic susceptibility to racial/ethnic disparities in prostate cancer incidence and for translating the findings from GWA studies into interventions. In this study we plan to undertake a genome-wide association study (GWAS) of prostate cancer in the Multiethnic Cohort (MEC) Study. We propose the following hypotheses: (a) that inherited DNA variation influences risk of prostate cancer; (b) that many of the causal alleles will be outside known "candidate genes" requiring an agnostic, comprehensive search; and (c) that performing this search in a multi-ethnic cohort is more powerful than a study limited to a single population to reveal the full range of causal alleles relevant to the U.S. population. The version 1 release of this dataset will include genotype data for the Japanese and Latino populations in the study. The version 2 release will include data for the African ancestry population along with the Japanese and Latino subjects. The version 3 release will include fully-cleaned genotype data for all three populations. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to prostate cancer through large-scale genome-wide association studies of a well-characterized multi-ethnic cohort. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center and at the University of Southern California. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington. As an add-on to this GWAS we performed a targeted re-sequencing of all known prostate cancer risk loci in the samples from the MEC. Sequencing was performed in Dr. Reich's lab at Harvard Medical School.

  Study phs000306

• GWAS for Membranous Nephropathy

  Primary membranous nephropathy (MN) is a rare autoimmune cause of kidney failure. This dataset is from a genome-wide association study (GWAS) designed to identify novel genetic risk loci for MN. The provided cohort (named as European-1 Cohort) is composed of 611 cases of primary MN and 1,246 healthy controls of European ancestry. This cohort was used in the GWAS meta-analysis, as described in the manuscript entitled "Genetic architecture of membranous nephropathy and its potential diagnostic implications" (Nature Communications 2020, in press).The genome-wide summary statistics, including trans-ethnic meta-analysis across 8 GWAS cohorts of European and East Asian ancestry and ethnicity specific meta-analyses, are freely available for download on the Kiryluk lab website: http://www.columbiamedicine.org/divisions/kiryluk/resources.php.

  Study phs001984

• Epidemiologic Architecture for Genes Linked to Environment (EAGLE) MetaboChip Study

  The Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study is a study site of the larger Population Architecture using Genomics and Epidemiology (PAGE) I study.  EAGLE accessed two data resources during the course of study: the National Health and Nutrition Examination Surveys (NHANES) and BioVU, the Vanderbilt University Medical Center biorepository linked to de-identified electronic health records.The EAGLE MetaboChip Study, also known as EAGLE BioVU in the literature, is a data resource of Illumina MetaboChip genotypes for ~15,000 DNA samples from African American/Black, Hispanic, and Asian patients in BioVU (PMID: 26201699). Several EAGLE BioVU and PAGE I study phenotypes were extracted using structured and unstructured data available in de-identified electronic health records linked to the DNA samples. 

  Study phs002767

• Center for Common Disease Genomics (CCDG) - Cardiovascular: BioImage Cohort

  The genetic basis of cardiovascular disease in individuals of non-European ancestry remains largely unknown. Availability of ethnically diverse study populations is essential to fully investigate the underlying causes of disease. The BioImage Study enrolled adults aged 55-80 in a prospective observational study. Subjects had no prior history of cardiovascular disease, but were identified to be at intermediate to high risk for atherosclerotic cardiovascular events (PMID: 25790876). The recruiting target was a cohort with similar demographics to the US population in terms of race and ethnicity. Produced as part of the NHGRI Centers for Common Disease Genomics, this study contains whole genome sequence data and variant calls from 922 African American participants of the BioImage Study.

  Study phs002325

• Comprehensive survey for the construction of an integrated database of food, gut microbiome, and health information (the "Sukoyaka Health Survey"). A study on the relationship between food and health and genetic background.

  We conducted a cohort-based study to investigate the association between the genetic background and diet/lifestyle in 50 healthy Japanese. We analyzed some participants living in Miyazaki. The SNP array (Japonica Array v2) was used for genotyping. Shotgun metagenomic sequencing of fecal microbiome and metabolome of feces and blood were analyzed.

  Study JGAS000679

• Spatial transcriptome analysis for elucidating progression of early lung adenocarcinoma

  In this study, we performed spatial transcriptome analysis of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) to identify molecular events which occur during progression of ealry lung adenocarcinoma. For the analysis, we used cancer tissues which were precisely classified by Noguchi classification. Using the obtained data, we elucidated key molecular changes during tumor cell progression and their associated microenvironment statuses.

  Study JGAS000677

• HV31 - Read identifier list for local CCS, CLR, ONT and MGI reads

  This file contains read identifiers for local CCS, CLR, ONT and MGI reads for each of the eight selected genomic regions (HLA, KIR, IGH, IGK, IGL, TRA, TRD, andTRG). We extracted these reads by aligning whole-genome sequencing data to a draft whole-genome de novo assembly, and selecting reads that map to contigs representing each region. These reads were involved in the polishing and validation of the HV31 assembly. Please refer to the relevant manuscript (https://doi.org/10.1101/2021.02.03.429586) for additional details. Read identifiers are stored in JSON format. Along with the full FASTQ files, this file enables convenient re-analysis of the HV31 sequencing data in the eight selected regions.

  Dataset EGAD00001007761

• Developing Allelic Imbalance Analysis from Single-Nucleus RNA-Seq Data

  Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that, because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq) and introns are under lower purifying selection, and are thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. Overall, we provide an end-to-end experimental and computational approach for future studies.

  Study phs003749