AbstractX chromosome inactivation (XCI) is a key epigenetic gene expression regulatory process, which may play a role in women’s cancer. In particular tissues, some genes are known to escape XCI, yet patterns of XCI in ovarian cancer (OC) and their clinical associations are largely unknown. To examine XCI in OC, we integrated germline genotype with tumor copy number, gene expression and DNA methylation information from 99 OC patients. Approximately 10% of genes showed different XCI status (either escaping or being subject to XCI) compared with the studies of other tissues. Many of these genes are known oncogenes or tumor suppressors (e.g. DDX3X, TRAPPC2 and TCEANC). We also observed strong association between cis promoter DNA methylation and allele-specific expression imbalance (P = 2.0 × 10−10). Cluster analyses of the integrated data identified two molecular subgroups of OC patients representing those with regulated (N = 47) and dysregulated (N = 52) XCI. This XCI cluster membership was associated with expression of X inactive specific transcript (P = 0.002), a known driver of XCI, as well as age, grade, stage, tumor histology and extent of rl disease following surgical debulking. Patients with dysregulated XCI (N = 52) had shorter time to recurrence (HR = 2.34, P = 0.001) and overall survival time (HR = 1.87, P = 0.02) than those with regulated XCI, although results were attenuated after covariate adjustment. Similar findings were observed when restricted to high-grade serous tumors. We found evidence of a unique OC XCI profile, suggesting that XCI may play an important role in OC biology. Additional studies to examine somatic changes with paired tumor-normal tissue are needed.
Abstract 420: Targeted deep sequencing of mitochondrial DNA in epithelial ovarian carcinomas
Abstract Introduction: Mitochondria are intracellular organelles that play an important role in energy metabolism, reactive oxygen species generation, and apoptosis. They possess their own haploid genome distinct from nuclear DNA, and mutations in mitochondrial DNA (mtDNA) have previously been linked to cancer risk, disease progression, and treatment response for multiple tumor types. However, the spectrum of mtDNA variation in epithelial ovarian carcinoma (EOC) and associations with clinical characteristics have not been fully explored. Methods: We extracted mtDNA from fresh frozen EOC tumors of women diagnosed with primary invasive epithelial ovarian, fallopian tube, or peritoneal carcinoma, and performed targeted sequencing using the Illumina MiSeq Reporter mtDNA workflow. Homoplasmic and heteroplasmic SNVs and indels were called using an in-house bioinformatics pipeline. We estimated mtDNA haplogroup using Haplogrep and compared to results from available germline mtDNA SNP genotyping. We derived regional weighted variant burden scores based on mtDNA functional domains, accounting for underlying haplogroup, heteroplasmic fraction, and predicted functional impact. To assess potential differences in variant burden by histotype, we compared burden scores using Kruskal-Wallis testing. Among high-grade serous tubo-ovarian cases, we explored associations with overall survival (OS) using Cox proportional hazards regression. After quality control filtering, 389 mitochondrial genomes were analyzed, including those from 320 tubo-ovarian high-grade serous tumors, 42 endometrioid tumors, and 18 clear cell tumors. Results: Accounting for predicted haplogroup, we identified a median count of two global private heteroplasmies per tumor (range: 0-9). Elevated mutation rates were identified in the regulatory control region as well as among the various mt-tRNAs (>3 per 10kb per sample) relative to the remainder of the mtDNA. The majority of recurrent variants across tumors were also identified in the mtDNA control region. We did not observe an association with overall mtDNA variant burden and patient age at diagnosis. Regional mtDNA burden scores revealed a significant association with histotype (P<0.001) for the oxidative phosphorylation complex IV genes, with higher burden in tubo-ovarian high-grade serous and clear-cell tumors relative to endometrioid tumors. For patients with tubo-ovarian high-grade serous tumors, increased variant burden in MT-CO1 (cytochrome C oxidase I) was associated with improved OS (HR = 0.32; 95% CI = [0.14,0.70], LRT P = 0.001) after adjustment for age, stage, and debulking status. Conclusions: We demonstrate a wide range of tumor mtDNA variant patterns in the largest known collection of EOC patients. This work provides the first extensive evaluation of mtDNA variation in these diseases and highlights the potential prognostic relevance of mitochondrial dysfunction. Citation Format: Nicholas B. Larson, Stacey J. Winham, Chen Wang, Jared M. Evans, Sebastian M. Armasu, Bryan M. McCauley, Sean J. Yoder, Lan Min Zhang, Catherine M. Phelan, Ellen L. Goode. Targeted deep sequencing of mitochondrial DNA in epithelial ovarian carcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 420.
Abstract 225: Tumor-infiltrating CD8-positive T-lymphocytes in tubo-ovarian high-grade serous cancer are associated with multiple germline variants in 22q12.1 in a genome-wide association analysis
Abstract Tubo-ovarian high-grade serous cancer (HGSC) is the most common histotype of epithelial ovarian cancer (70%-80%) and the leading cause of death from gynecological malignancy. Novel monoclonal antibody and adoptive cell transfer immunotherapies have found success in cancer in the past five years; however success in HGSC treatment has been elusive thus far. We have recently shown that CD8+ T-lymphocytes infiltrating the tumor proper (TILs) associate in a dose response manner with longer patient survival time regardless of age, stage or residual disease. As understanding host factors associated with this clinically relevant tumor phenotype will contribute to the development of targeted therapies, we sought to identify germline genetic factors associated with CD8+ TIL levels in HGSC. We performed a germline genome-wide association study (GWAS) of CD8+ TILs using 1204 HGSC patients of European ancestry from twelve studies with centralized genotyping, immunohistochemistry, and harmonization of clinical data. Germline genotypes were assayed using the Illumina Infinium OncoArray Beadchip and were imputed to over 11.4 million variants based on the 1000 Genomes Project reference panel. CD8 immunohistochemistry was performed on tissue microarrays using the Leica Bond Rx stainer and scored into four levels of CD8+ TILs per x400 magnification of a 0.55-mm diameter field for each tumor hotspot: none (no CD8+ TILs), low (1-2 CD8+ TILs), moderate (3-19 CD8+ TILs), high (20 or more CD8+ TILs). GWAS used multinomial regression modelling of these four CD8+ TIL levels adjusted for study site, age, and European ancestry principal components. On the average, CD8+ TIL levels were 18%, 19%, 44% and 18% for none, low, moderate and high levels, respectively. As expected, CD8+ TIL levels associated with overall survival time (p < 2.6x10-8), and CD8+ TIL levels and age at diagnosis were similarly distributed across study sites. We identified a region on chromosome 22 with multiple, correlated variants (MAF > 20%) associated with CD8+ TIL levels at p-value < 2.0x10-5. The most statistically significant variant was an indel (rs557925408) located in the an intron of the MYO18B gene (Myosin XVIIIB, p-value < 8.7x10-6). Each copy of this variant associated with a reduced extent of CD8+ TIL infiltration (OR low v none = 0.92; OR moderate v none = 0.61). An independent set of 1200 OncoArray genotyped HGSC cases are undergoing CD8+ TIL scoring in December 2017 and will be included in final genome-wide analysis. This will provide improved statistical power and enable consideration of additional genetic models (e.g., linear trend tests). Comprehensive integrative analysis of germline, tumor, and clinical features provides a model for clinical molecular epidemiology studies and will be key to increasing our understanding of this important HGSC immunophenotype. Citation Format: Yanina Natanzon, Martin Köbel, Stacey J. Winham, Sebastian M. Armasu, Bryan M. McCauley, Robert A. Vierkant, Julie M. Cunningham, David Bowtell, Ian G. Campbell, Jenny Chang-Claude, Anna deFazio, Peter A. Fasching, Mark T. Goodman, Beth Y. Karlan, Francesmary Modugno, Kirsten B. Moysich, Roberta B. Ness, Weiva Sieh, Paul D. Pharoah, Susan J. Ramus, Ellen L. Goode. Tumor-infiltrating CD8-positive T-lymphocytes in tubo-ovarian high-grade serous cancer are associated with multiple germline variants in 22q12.1 in a genome-wide association analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 225.
Association of p16 expression with prognosis varies across ovarian carcinoma histotypes: an Ovarian Tumor Tissue Analysis consortium study
AbstractWe aimed to validate the prognostic association of p16 expression in ovarian high‐grade serous carcinomas (HGSC) and to explore it in other ovarian carcinoma histotypes. p16 protein expression was assessed by clinical‐grade immunohistochemistry in 6525 ovarian carcinomas including 4334 HGSC using tissue microarrays from 24 studies participating in the Ovarian Tumor Tissue Analysis consortium. p16 expression patterns were interpreted as abnormal (either overexpression referred to as block expression or absence) or normal (heterogeneous). CDKN2A (which encodes p16) mRNA expression was also analyzed in a subset (n = 2280) mostly representing HGSC (n = 2010). Association of p16 expression with overall survival (OS) was determined within histotypes as was CDKN2A expression for HGSC only. p16 block expression was most frequent in HGSC (56%) but neither protein nor mRNA expression was associated with OS. However, relative to heterogeneous expression, block expression was associated with shorter OS in endometriosis‐associated carcinomas, clear cell [hazard ratio (HR): 2.02, 95% confidence (CI) 1.47–2.77, p < 0.001] and endometrioid (HR: 1.88, 95% CI 1.30–2.75, p = 0.004), while absence was associated with shorter OS in low‐grade serous carcinomas (HR: 2.95, 95% CI 1.61–5.38, p = 0.001). Absence was most frequent in mucinous carcinoma (50%), and was not associated with OS in this histotype. The prognostic value of p16 expression is histotype‐specific and pattern dependent. We provide definitive evidence against an association of p16 expression with survival in ovarian HGSC as previously suggested. Block expression of p16 in clear cell and endometrioid carcinoma should be further validated as a prognostic marker, and absence in low‐grade serous carcinoma justifies CDK4 inhibition.
Genomic Analysis Using Regularized Regression in High-Grade Serous Ovarian Cancer
High-grade serous ovarian cancer (HGSOC) is a complex disease in which initiation and progression have been associated with copy number alterations, epigenetic processes, and, to a lesser extent, germline variation. We hypothesized that, when summarized at the gene level, tumor methylation and germline genetic variation, alone or in combination, influence tumor gene expression in HGSOC. We used Elastic Net (ENET) penalized regression method to evaluate these associations and adjust for somatic copy number in 3 independent data sets comprising tumors from more than 470 patients. Penalized regression models of germline variation, with or without methylation, did not reveal a role in HGSOC gene expression. However, we observed significant association between regional methylation and expression of 5 genes ( WDPCP, KRT6C, BRCA2, EFCAB13, and ZNF283). CpGs retained in ENET model for BRCA2 and ZNF283 appeared enriched in several regulatory elements, suggesting that regularized regression may provide a novel utility for integrative genomic analysis.
Identification of Genetic Interaction with Risk Factors Using a Time-To-Event Model
Background: Certain diseases can occur with and without a trigger. We use Venous Thromboembolism (VTE) as our example to identify genetic interaction with pregnancy in women with VTE during pre- or postpartum. Pregnancy is one of the major risk factors for VTE as it accounts for 10% of maternal deaths. Methods: We performed a whole genome association analysis using the Cox Proportional Hazard (CoxPH) model adjusted for covariates to identify genetic variants associated with the time-to-event of VTE related to pre- or postpartum during the childbearing age of 18–45 years using a case-only design in a cohort of women with VTE. Women with a VTE event after 45 years of age were censored and contributed only follow-up time. Results: We identified two intragenic single nucleotide polymorphisms (SNPs) at genome-wide significance in the PURB gene located on chromosome 7, and two additional intragenic SNPs, one in the LINGO2 gene on chromosome 9 and one in RDXP2 on chromosome X. Conclusions: We showed that the time-to-event model is a useful approach for identifying potential hazard-modification of the genetic variants when the event of interest (VTE) occurs due to a risk factor (pre- or post-partum).
Abstract 3368: Omics data integration analysis in high grade serous ovarian cancer: results from three studies
Abstract High grade serous ovarian cancer (HGSOC) is a complex disease in which initiation and progression have been associated with gene mutation, DNA methylation changes, genetic variation, and epigenetic processes. Variation in several susceptibility regions and cancer-typical global methylation patterns have been observed in HGSOC; however, this knowledge has not been compelling in understanding HGSOC intiation or progression. As ingetration of genomic, epigenomic, and transcriptomic data has increased mechanistic understanding in other cancers, we hypothesized that tumor methylation alone or in combination with germline genetic variation influences tumor gene expression in HGSOC. We examined three nested models using an Elastnic Net (ENET) penalized regression method while adjusting for somatic copy number (CNV): a) germline genotype and tumor DNA methylation (full model), b) genotype only, and c) DNA methylation only. We included 339 cases from The Cancer Genome Atlas (TCGA), 54 cases from Mayo Clinic, and 78 cases from the Australian Ovarian Cancer Study (AOCS). Genotyping and copy number calls on germline DNA, expression, methylation and copy number on somatic samples were collected and analyzed on different platforms separately at each study site. We excluded genes with low overall expression and thus analyzed a total of 11,922 genes available in three datasets ( Ensembl IDs, 500kb window up- and downstream). In general, combining genomic data in HGSOC did not reveal a role for germline genetic variation in altering gene expression. However, in methylation only models 79 genes were associated with differential expression in the TCGA cases (permutation multiple testing adjusted p-val <0.05), in the Mayo cases (unadjusted p-val <0.05) and AOCS cases (unadjusted p-val <0.05). A known tummor suppressor (FBXW7) was associated with differential expression in the three datasets at p-val <0.01. This work demonstrates the feasibility, utility, and statistical power of ENET gene-level analyses incoporating maximal genomic information. Citation Format: Yanina Natanzon, Madalene Earp, Julie M. Cunningham, Kimberly R. Kalli, Stacey J. Winham, Sebastian M. Armasu, Melissa C. Larson, Chen Wang, David D. Bowtell, Dale W. Garsed, Ellen Goode. Omics data integration analysis in high grade serous ovarian cancer: results from three studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3368. doi:10.1158/1538-7445.AM2017-3368
Abstract 2420: Integrative analyses of gene expression, DNA methylation, genotype and copy number alterations characterize X-chromosome inactivation in ovarian cancer
Abstract Introduction: In females, X-chromosome inactivation (XCI) epigenetically silences transcription of one copy of the X chromosome. Which chromosome is silenced is randomly selected, and is tissue- and cell-specific. While some genes are known to escape XCI under normal conditions, aberrant XCI patterns are thought to occur in female-specific cancers, although the role of XCI in ovarian tumorigenesis and progression is largely unknown. The process of XCI is complex, and integration of gene expression, DNA methylation, and copy number data can inform the XCI status of individual genes and chromosome-wide XCI patterns for individual patients. Methods: We evaluated gene- and chromosome-level patterns of XCI by integrating RNA sequence, copy number alteration, genotype, and DNA methylation data to study XCI escape patterns in tumor samples from 99 ovarian cancer patients. We measured allele-specific expression (ASE) for 397 X-linked genes to identify the active alleles for each tumor. Combining ASE data with knowledge of copy number status, we used a Bayesian beta-binomial mixture model to estimate which genes escaped XCI for each patient, and validated our findings using DNA methylation data. To assess global XCI patterns, we performed cluster analyses on the ASE and methylation data, after adjusting for loss of heterozygosity. We examined the relationship between the clusters and clinical factors, including overall survival and time to recurrence. Results: DNA promoter methylation demonstrated inverse regional correlations with ASE. Cluster analyses using ASE and methylation data demonstrated evidence of two tumor clusters, representing normal XCI and global XCI dysregulation. The dysregulated XCI cluster (N=52) was associated with lower X-inactive specific transcript expression as expected (p<0.01). Patients with XCI dysregulated tumors were higher grade, stage, serous histology and were sub-optimally debulked (p<0.05). These patients also had shorter overall survival time (HR=1.87, p=0.02) and time to recurrence (HR=2.34, p<0.01), although associations were attenuated after covariate adjustment. In 45 tumor samples with sufficient data, we observed escape patterns largely consistent with previous reports of multiple tissue types. When comparing tumor to normal ovarian tissue, eight genes (CXorf23, CXorf36, BRWD3, ELF4, SLITRK4, GABRE, CLCN4, SH3BGRL) showed putative escape in the tumor and two genes (RBBP7, OFD1) showed discrepant tumor inactivation. Conclusions: We identified discrepant gene-level XCI tumor classifications compared to normal tissue and identified a group of patients with chromosome-wide XCI dysregulation associated with worse clinical prognosis. This provides evidence of the role of XCI in ovarian cancer and highlights the need to integrate multiple genomic data types to study XCI. Citation Format: Stacey J. Winham, Nicholas B. Larson, Sebastian M. Armasu, Zachary C. Fogarty, Melissa C. Larson, Kimberly R. Kalli, Kate Lawrenson, Simon Gayther, Brooke L. Fridley, Ellen L. Goode. Integrative analyses of gene expression, DNA methylation, genotype and copy number alterations characterize X-chromosome inactivation in ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2420. doi:10.1158/1538-7445.AM2017-2420
Pooled Clustering of High-Grade Serous Ovarian Cancer Gene Expression Leads to Novel Consensus Subtypes Associated with Survival and Surgical Outcomes