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• Genome-Wide Pleiotropy Scan Across Multiple Cancers

  A whole-exome sequencing (WES) study was conducted in 3,233 cases diagnosed with multiple primary cancers and 3,229 matched cancer-free controls (90% non-Hispanic white, 3% African-American, 3% East Asian, and 4% Latino) selected from individuals in the Kaiser Permanente Research Bank (KPRB) who were members of the Kaiser Permanente Northern California (KPNC) health plan. Cancer-free controls were matched to cases on age at specimen collection (within 2 years), sex, genotyping array (which matched on self-reported race/ethnicity), closest distance using the first two principal components for genetic ancestry, and reagent kit. Cases and controls were drawn from two prospective KPRB cohorts: the Research Program on Genes, Environment and Health (RPGEH) and the ProHealth study. Participants were sequenced by the Regeneron Genetics Center using the Illumina NovaSeq 6000 platform, and sample preparation and quality control were performed using a high-throughput, fully-automated system [PMID: 33087929]. Reads were aligned to the GRCh38 reference genome, and variants were called using WeCall [PMID: 33087929]. Participants with sex discordance, 20x coverage at less than 80% of targeted sites, and/or contamination greater than 5% were excluded. After quality control, we retained n = 6,247 (3,111 cases, 3,136 controls) individuals for downstream analyses. Among participants selected for this WES study, n = 5,432 (2,299 cases; 3,133 controls) consented to deposition of data to the National Institutes of Health (NIH).Further quality control was applied to filter low quality variants. Genotype calls with low depth of coverage (DP) were updated to missing (DP < 7 for SNPs and DP < 10 for indels), after which sites with low allele balance (AB) - variants without at least one sample having AB ≥ 15% for SNPs or AB ≥ 20% for indels - were removed. Lastly, variants with missingness > 10% and Hardy-Weinberg equilibrium p-value < 10-15 were excluded. Further description of quality control and downstream single-variant and gene-based analyses is available in Cavazos et al, 2022 [medRxiv].

  Study phs002809

• NSIGHT North Carolina Newborn Exome Sequencing for Universal Screening (NC NEXUS)

  Since newborn screening (NBS) began in the 1960s, technological advances have resulted in its use in an increasing number of disorders. Recent developments in whole-genome sequencing and its simpler corollary, whole-exome sequencing (WES), now afford the opportunity to comprehensively define the variation within an individual's genome in a rapid and affordable manner. Many challenges arise with the clinical application of genome-scale sequencing and in deriving practical benefits to infants and children. Its utility in NBS has yet to be demonstrated and its application in the pediatric population requires special examination, not only for potential clinical benefits but also for the unique ethical challenges it presents. In this proposal, we outline a highly interdisciplinary approach to identify, confront, and overcome the major challenges that must be met in order to implement deep sequencing technology to enhance current newborn screening in a diverse pediatric population. Overarching Aim 1 will evaluate the utility of WES as a diagnostic tool to extend the utility of current NBS. Using diverse cohorts of infants and young children with known conditions identified through NBS, we will examine the sensitivity and specificity of WES. We will also utilize WES in cohorts of children with known conditions not currently screened as potential candidates for NBS in the future. Overarching Aim 2 will develop and assess a framework for analyzing WES in a clinically oriented framework based on principles of ethics and evidence-based medicine. We will develop strategies to guide clinicians, clinical laboratories, and patients/families in their decisions regarding the inevitable incidental findings that will be detected, in ways that respect the child and protect his/her future autonomy, while also respecting parental interests and rights. Overarching Aim 3 will explore ethical, legal, and social issues (ELSI) involved in informed decision making and develop best practices regarding the return of results after testing. We will develop novel decision support tools and evaluate their usefulness in parental decision making, and examine the burdens placed on clinicians as this new technology is deployed in the vulnerable and special population that are newborns and their families.

  Study phs002095

• Gabriella Miller Kids First (GMKF) Pediatric Research Program in Susceptibility to Ewing Sarcoma Based on Germline Risk and Familial History of Cancer

  Ewing sarcoma (EWS) is a deadly bone cancer that occurs in children and adolescents. Mounting evidence suggests that a genetic predisposition exists for this pediatric cancer, although the specific genetic contribution has yet to be identified. EWS has never been linked to a specific cancer predisposition syndrome, although several case reports have been published that describe siblings and cousins with EWS. Furthermore, neuroectodermal tumors appear to occur more commonly in families with EWS. The two consistent epidemiology findings in EWS include a very strong Caucasian predilection and increased rates of hernia in EWS patients and their family members. Finally, the role of genetic microsatellite repeats in EWS tumorigenesis has been recently described, and these GGAA microsatellites are polymorphic in repeat size and location across the genome. The study goals of this Kids First project include (1) To identify cancer predisposition genes in EWS trios increasing disease risk, (2) To identify genome-wide GGAA microsatellite repeats in EWS trios increasing disease risk, and (3) To identity de novo mutation and structural variant rates in EWS trios reflecting underlying DNA repair defects that increase disease risk. As part of the Kids First Common Fund initiative, this study proposal will further elucidate the genetic contribution to pediatric cancer development. Around 375 of these trios were selected for whole genome sequencing as part of the Gabriella Miller Kids First fund. The EWS trios have been collected as part of the Children's Oncology Group's AEPI10N5 Study ("Genetic Epidemiology of Ewing Sarcoma"), and each trio has associated phenotypic data including a detailed family history. We will interrogate the sequence data using our genomic analysis pipeline at the University of Utah and the Utah Science Technology and Research initiative's (USTAR) Center for Genetic Discovery. We will look for the genetic contribution to EWS and the sequence data with be shared in a repository designated by the Kids First Common Fund. The WGS of these ~375 EWS trios will help us to understand the genetic origins of a deadly childhood cancer and may lead to novel strategies for prevention and treatment.

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• Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes

  Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. Since 2007, common genetic variants in ~200 loci have been identified in genome-wide association studies (GWAS) in relation to breast cancer risk. However, it is often difficult to translate GWAS findings to disease prevention and treatment since causal genes in the large majority of GWAS-identified loci are unknown. Furthermore, a large fraction of breast cancer heritability remains unexplained. Recent studies suggest that nearly 80% of disease heritability can be explained by genetic variants regulating gene expression. Herein, we propose three well-powered transcriptome-wide association studies (TWAS) to systematically investigate the association of breast cancer risk with gene expression across the transcriptome of African, Asian and European descendants. In Aim 1, we will perform RNA sequencing and high-density genotyping assays using normal breast tissue samples, and build race-specific gene expression prediction models using data from 1000 women of African, Asian and European descent. These models will be applied to the GWAS data generated from approximately 320,000 breast cancer patients and controls to impute gene expression for association analyses of predicted gene expression with risk of breast cancer overall, and by estrogen receptor and HER2 status. In Aim 2, we will select the top 50 genes identified in Aim 1 for in vitro functional assays to assess their influence on major cell functions related to cancer biology. In Aim 3, we will evaluate whether TWAS-identified genes may express differently in normal breast tissues and breast cancer tissues collected from African, Asian, and European descendants to assess whether these genes may contribute to racial differences in breast cancer risk by molecular subtypes. With strong methodology and a large sample size, we believe that this proposed study should be able to identify and characterize a large number of novel genes related to breast cancer risk. Uncovering breast cancer susceptibility genes will greatly improve the understanding of the genetic and biological basis for breast cancer and accelerate the translation of genetic findings to disease prevention and patient care.

  Study phs003535

• NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource for Studying the Impact of Genetic Variation on Molecular Phenotypes

  The iPSC Collection for Omic Research (iPSCORE) Resource was created as part of the Next-Gen Consortium funded by NHLBI. The overarching purpose of the resource is to provide a large collection of human induced pluripotent stem cells (iPSCs) for use in studying the impact of genetic variation on molecular and physiological phenotypes. The resource has been used in a number of studies in the Dr. Kelly A. Frazer's Lab examining both the characteristics of human iPSCs and a variety of iPSC-derived cell types including cardiovascular progenitor cells (iPSC-CVPCs), pancreatic precursor cells (iPSC-PPCs), and retina pigment epithelium cells (iPSC-RPEs). We have shown that the iPSCs, CVPCs, and PPCs are suitable surrogate models to identify genetic factors active in early developmental processes because they exhibit fetal-like molecular properties. A total of 273 individuals have participated in the study, of which 222 have had iPSCs generated from fibroblasts. Of the 273 individuals, 181 are part of 55 families that include 24 monozygotic twin pairs and 5 dizygotic twin pairs, allowing for the incorporation of familial relationships into genetic analyses. Germline DNA has been sequenced from blood or fibroblast samples for all 273 individuals (available through dbGaP phs001325) and other genomic data (RNA-seq, DNA methylation, genotype arrays, ATAC-seq, H3K27ac ChIP-seq, HiC-seq) have been generated from the 222 iPSCs as well as derived cell types (available through dbGaP phs000924). QTL analyses were conducted for multiple omics data types and summary statistics are available through dbGaP phs0001325. Important note: Of the 273 individuals, 268 are consented for general research use and 5 are consented for cardiac research only. For detailed information about iPSCORE Collection including samples, methods used to generate the data, and how to access the datasets visit the Frazer lab website.The 222 well characterized iPSC lines that constitute the iPSCORE resource are available, please contact Dr. Kelly A. Frazer (kafrazer@health.ucsd.edu) if you are interested in obtaining the collection.

  Study phs000924

• NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource for Studying the Impact of Genetic Variation on Molecular and Physiological Phenotypes - Whole Genome Sequence

  The iPSC Collection for Omic Research (iPSCORE) Resource was created as part of the Next-Gen Consortium funded by NHLBI. The overarching purpose of the resource is to provide a large collection of human induced pluripotent stem cells (iPSCs) for use in studying the impact of genetic variation on molecular and physiological phenotypes. The resource has been used in a number of studies in the Dr. Kelly A. Frazer's Lab examining both the characteristics of human iPSCs and a variety of iPSC-derived cell types including cardiovascular progenitor cells (iPSC-CVPCs), pancreatic precursor cells (iPSC-PPCs), and retina pigment epithelium cells (iPSC-RPEs). We have shown that the iPSCs, CVPCs, and PPCs are suitable surrogate models to identify genetic factors active in early developmental processes because they exhibit fetal-like molecular properties.A total of 273 individuals have participated in the study, of which 222 have had iPSCs generated from fibroblasts. Of the 273 individuals, 181 are part of 55 families that include 24 monozygotic twin pairs and 5 dizygotic twin pairs, allowing for the incorporation of familial relationships into genetic analyses.Germline DNA has been sequenced from blood or fibroblast samples for all 273 individuals (available through dbGaP phs001325) and other genomic data (RNA-seq, DNA methylation, genotype arrays, ATAC-seq, H3K27ac ChIP-seq, HiC-seq) have been generated from the 222 iPSCs as well as derived cell types (available through dbGaP phs000924).QTL analyses were conducted for multiple omics data types and summary statistics are available through dbGaP phs0001325.Important note: Of the 273 individuals, 268 are consented for general research use and 5 are consented for cardiac research only.For detailed information about iPSCORE Collection including samples, methods used to generate the data, and how to access the datasets visit the Frazer lab website.The 222 well characterized iPSC lines that constitute the iPSCORE resource are available, please contact Dr. Kelly A. Frazer (kafrazer@health.ucsd.edu) if you are interested in obtaining the collection.

  Study phs001325

• Kids First: Whole Genome Sequencing in Recessive Structural Brain Defects

  Almost 5% of all live births in the US (1:20 births) display an inborn defect, including both structural and functional/metabolic abnormalities. These are among the most common causes of Infant mortality in the developed world and underlie nearly half of hospitalizations in the first 3 years of life. Of the 35 major defects observable at birth from the International Clearinghouse for Birth Defects Surveillance Program (www.icbdsr.org, external link), about half involve the nervous system. Many of these result in lifelong neurodevelopmental disorders. Structural Brain Defects (SBDs) result from errors in development of the central nervous system, including defects in the forebrain, midbrain and hindbrain. Many SBDs arise as the consequence of a single gene bi-allelic mutation, and for this reason, occur more commonly in populations or communities with elevated consanguinity.Our lab has identified dozens of novel SBD genes using WES/WGS in consanguineous SBD families. Importantly, the genes that we and others have identified in these unique families are then used to advance diagnosis in pediatric SBDs around the world. We have built an enormous cohort of SBD families, including newly recruited families not yet studied genetically, and previous families that were negative for cause following WES analysis. Here we propose to collaborate with the Gabriella Miller Kids First Pediatric Research Program (X01) to have sequencing performed in individuals from a total of 200 families with genetically undiagnosed SBDs. The Gleeson Lab team of researchers is dedicated to the field of SBDs, with an outstanding track record of high-impact science, and a collaborative approach to discovery. We have 150 newly recruited families that we propose to study by WES by sequencing blood-derived DNA from two affected patients, or the parents and one affected patient. We also have 50 families in which WES was negative, which we propose to study in a multi-omics approach combining WGS from blood-derived DNA. We anticipate that this study will lead to the identification of many new molecular causes of SBDs, as well as uncover new genotype-phenotype correlations and new disease mechanisms, paving the way for future breakthroughs in detection, treatment and prevention.

  Study phs002590

• Genomic analysis of patient-derived xenograft models reveals intratumor-heterogeneity in endometrial cancer and can predict tumor growth inhibition with talazoparib

  Background: Endometrial cancer (EC) is a major gynecological cancer with increasing incidence. It comprised of four molecular subtypes with differing etiology, prognoses, and response to chemotherapy. In the future, clinical trials testing new single agents or combination therapies will be targeted to the molecular subtype most likely to respond. Pre-clinical models that faithfully represent the molecular subtypes of EC are urgently needed, we sought to develop and characterize a panel of novel EC patient-derived xenograft (PDX) models. Methods: Here, we report whole exome or whole genome sequencing of 11 PDX models and the matched primary tumor. Analysis of multiple PDX lineages and passages was performed to study tumor heterogeneity across lineages and/or passages. Based on recent reports of frequent defects in the homologous recombination (HR) pathway in EC, we assessed mutational signatures and HR deficiency scores and correlated these with in vivo responses to the PARP inhibitor (PARPi) talazoparib in six PDXs representing the copy number high/p53-mutant and mismatch-repair deficient molecular subtypes of EC. Results: PDX models were successfully generated with similar histomorphology from all four molecular subtypes of EC and uterine carcinosarcomas. We also observed a wide range of inter-tumor and intra-tumor heterogeneity across different PDX lineages, however one arm of most PDX models recapitulated the molecular landscape of the primary tumor without major genomic drift. An in vivo response to talazoparib was detected in four copy number high models. Two models (carcinosarcomas) showed a response consistent with stable disease and two models (one copy number high serous EC and another carcinosarcoma) showed significant tumor growth inhibition, albeit one consistent with progressive disease, however all lacked the HR deficiency genomic signature. Conclusions: EC PDX models represent the four molecular subtypes of disease and can capture intra-tumoral heterogeneity of the original primary tumor. PDXs of the copy number high molecular subtype showed sensitivity to PARPi, however, deeper and more durable responses will likely require combination of PARPi with other agents.

  Study EGAS00001004666

• Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers

  Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination. Biological Materials were provided by the Ontario Tumour Bank, which is funded by the Ontario Institute for Cancer Research Reference for citation: Ling Liu, Jinghua Feng, Julian Polimeni, Manli Zhang, Hai Nguyen, Urmi Das, Xu Zhang, Harminder Singh, Xiao-Jian Yao, Etienne Leygue, Sam K.P. Kung, and Xie J. Characterization of cell free plasma methyl-DNA from xenografted tumours to guide the selection of diagnostic markers for early-stage cancers. Frontiers in Oncology, 2021 Feb. 5. DOI: 10.3389/fonc.2021.615821.

  Study EGAS00001006175

• Chromatin profiles classify castration-resistant prostate cancers suggesting therapeutic targets

  Untreated prostate cancers rely on androgen receptor (AR) signaling for growth and survival, forming the basis for the initial efficacy of androgen deprivation therapy (ADT). Yet, the disease can relapse and progress to a lethal stage termed castration-resistant prostate cancer (CRPC). Reactivation of AR signaling represents the most common driver of CRPC growth and next generation AR signaling inhibitors (ARSIs) are now used in combination with ADT as a first line therapy. However, ARSIs can result in selective pressure generating AR-independent tumors. The transition from AR-dependence frequently accompanies a change in phenotype resembling developmental trans-differentiation or ‘lineage plasticity’. Neuroendocrine prostate cancer, which lacks a defined pathologic classification, is the most studied type of lineage plasticity. However, most AR-null tumors do not exhibit neuroendocrine features and are classified as ‘double-negative prostate cancer’, the drivers of which are poorly defined. Lineage plasticity studies in CRPC are limited by the lack of genetically defined patient-derived models that recapitulate the disease spectrum. To address this, we developed a biobank of organoids generated from patient biopsies to study the landscape of metastatic CRPC and allow for functional validation assays. Proteins called transcription factors (TFs) are drivers of tumor lineage plasticity. To identify the key TFs that drive the growth of AR-independent tumors, we integrated epigenetic and transcriptomic data generated from CRPC models. By presenting a map of the chromatin accessibility and transcriptomic landscape of CRPC using a diverse biobank of organoids, PDXs and cell lines that recapitulate the heterogeneity of metastatic prostate cancer, we validate CRPC-AR and CRPC-NE subtypes and reveal two subtypes of AR-negative/low samples as well as their respective masterTFs. Additional analysis revealed a model in which YAP, TAZ, TEAD and AP-1 function together and drive oncogenic growth in CRPC-SCL samples. Overall, we show here how an approach to stratify CRPC patients into four subtypes using their transcriptomic signatures can potentially inform upon appropriate clinical decisions.

  Study EGAS00001006059