Lawrenson, Kate

Abstract Introduction: Identifying dysregulated gene expression in ovarian cancers has been limited by a deficit of available normal tissues. Here, we generated the largest set of high-grade serous ovarian cancer (HGSOC) tumors with normal precursor tissues for transcriptome analyses to identify lncRNA expression patterns, provide insight into their cellular contexts and functions, and assess their relevance to HGSOC pathogenesis and genetic susceptibility. Methods: We performed RNA sequencing on 220 primary HGSOCs and 116 benign epithelia (micro-dissected fallopian tube, ovarian surface, and inclusion cyst epithelia), and combined samples with 428 HGSOCs from TCGA, 60 HGSOCs from a prior study, and 180 bulk ovary tissues from GTEx. Reads were processed with a uniform bioinformatic and quality control pipeline, combined and batch corrected. Normalized TPM expression values were compared using the Wilcoxon rank sum test with >2-fold change and FDR <1% considered statistically significant. We computed weighted gene co-expression networks for each tissue type and tested for enrichment of differentially expressed genes (DEGs) and gene ontologies within co-expression modules. Results: Transcriptomes included 27,700 expressed genes (8,202 lncRNAs) across 706 HGSOCs, 180 bulk ovary, and 88 ovarian epithelia tissues. Most genes were expressed in all tissues, though 5% each showed HGSOC- or normal tissue-specific expression which comprised ≥50% lncRNA. Comparing HGSOCs to normal tissues identified 11,804 DEGs with 4,522 lncRNAs (DElncRNA) of which ~50% were tissue-specific. DEGs included MUC16 and multiple GWAS/TWAS implicated susceptibility genes including RAD51, BRIP1, BNC2, TIPARP-AS1, PRC1, KANSL1, ANKLE1, CHMP4C, ESRP2, and CCNE1. The most highly expressed DElncRNA in HGSOC were upregulated RMRP (P=1.4 × 10−39), SNHG1 (P=3.0 × 10−27), and HAGLR (P=2.0 × 10−24) at the HOXD risk locus. Lower proportions of lncRNA were seen in the HGSOC co-expression modules compared to those in normal tissues and less (3% vs. 15%) HGSOC modules were considered strongly lncRNA regulated (>50% lncRNA in module). Tissue-specific DElncRNA tended toward upregulation in HGSOC compared to ovarian epithelia with enriched modules associated with cell cycle regulation (P=1.5 × 10−38); and toward downregulation in HGSOC compared to bulk ovary with enriched modules associated with chemokine signaling/response (P=1.7 × 10−113). Conclusions: The lower proportion of lncRNA involved in HGSOC co-expression networks indicates a marked loss of regulation by lncRNA. Preliminary interrogation of HGSOC-dysregulated lncRNA expression revealed tissue-specific differences that highlight unique biological pathways in precursor epithelia and the ovarian microenvironment that contribute to HGSOC pathogenesis. Our results provide additional support for previously nominated risk genes. eQTL analysis has recently been completed and integration with GWAS are underway to elucidate lncRNA and lncRNA-regulated susceptibility genes and will be presented at the conference. Citation Format: Brett M. Reid, Ann Chen, Zhihua Chen, Florian A. Karreth, Peter Kanetsky, Jennifer B. Permuth, Ozlen Saglam, Jamie K. Teer, Xiaoqing Yu, Simon Gayther, Ellen Goode, Paul Pharoah, Thomas A. Sellers, Kate Lawrenson, Jonathan Tyrer. Patterns of lncRNA-regulated gene expression in high-grade serous ovarian carcinomas [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr A004.

Abstract Purpose: Identifying dysregulated gene expression in ovarian cancers has been limited by a deficit of available normal tissues. Here, we generated the largest set of high-grade serous ovarian cancer (HGSOC) tumors with normal precursor tissues for transcriptome analyses. Methods: We performed RNA sequencing on 220 primary HGSOCs and 116 benign epithelia (micro-dissected fallopian tube, ovarian surface, and inclusion cysts), and combined samples with 428 HGSOCs from TCGA, 60 HGSOCs from a prior study, and 180 bulk ovary tissues from GTEx. Raw reads were processed with a uniform bioinformatic and quality control pipeline; combined data were batch corrected. We tested for differences in median normalized CPM expression values using the Wilcoxon rank sum test with >2-fold change and a false discovery rate <1% considered statistically significant. We also conducted weighted gene co-expression network analysis in each tissue type. The hypergeometric test was used for enrichment of differentially expressed genes (DEGs) and gene ontologies within modules. Results: Transcriptomes comprised 27,700 expressed genes (8,202 lncRNAs) across 706 HGSOCs, 180 bulk ovary, and 88 ovarian epithelia tissues. Most (~90%) genes were expressed in all tissues; 5% each showed HGSOC- or normal tissue-specific expression and ≥50% were lncRNA. Comparing HGSOCs to ovarian epithelia and to bulk ovary identified 11,804 DEGs with 4,522 lncRNAs (DElncRNA) of which ~50% were tissue-specific. DEGs included MUC16 and multiple GWAS/TWAS implicated susceptibility genes including RAD51, BRIP1, BNC2, TIPARP-AS1, PRC1, KANSL1, ANKLE1, CHMP4C, ESRP2, and CCNE1. The most highly expressed DElncRNA in HGSOC were upregulated RMRP (P=1.4x10-39), SNHG1 (P=3.0x10-27), and HAGLR (P=2.0x10-24) at the HOXD risk locus. The highest expressed DElncRNA in precursor tissues was the HGSOC-downregulated MEG3 (P=1.7x10-67). DEGs were enriched in HGSOC co-expression modules associated with immune response, cell motility/localization, cell cycle regulation, angiogenesis, reproductive development, transcriptional regulation, and metabolic processes. Tissue-specific DElncRNA tended toward upregulation compared to ovarian epithelia with enriched modules associated with cell cycle regulation (hub=BUB1B; top DElncRNA TRPM2-AS, P=1.5x10-38); and toward downregulation compared to bulk ovary with enriched modules associated with chemokine signaling/response (hub= GADD45B, top DElncRNA RP11-87P3.1, P=1.7x10-113). Conclusion: HGSOC-dysregulated lncRNA expression revealed tissue-specific differences that highlight unique biological pathways in precursor epithelia and the ovarian microenvironment that contribute to HGSOC pathogenesis. Our results provide additional evidence to support previously nominated risk genes. Integration with eQTL and GWAS are underway to further elucidate novel HGSOC susceptibility genes. Citation Format: Brett M. Reid, Ann Chen, Zhihua Chen, Florian A. Karreth, Peter Kanetsky, Jennifer B. Permuth, Ozlen Saglam, Jamie Teer, Xiaoqing Yu, Simon Gayther, Ellen Goode, Paul Pharoah, Thomas A. Sellers, Kate Lawrenson. Patterns of dysregulated coding and noncoding gene expression in high-grade serous ovarian carcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6065.

AbstractBackgroundKnown risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.MethodsSingle nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer–related cell types.ResultsWe identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types.ConclusionsCNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

Abstract Purpose: To identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes. Experimental Design: We profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival. Results: We detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy. Conclusions: Our study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838

Abstract Background: Ovarian clear cell carcinoma (OCCC) is a rare ovarian cancer histotype that tends to be resistant to standard platinum-based chemotherapeutics. We sought to better understand the role of DNA methylation in clinical and biological subclassification of OCCC. Methods: We interrogated genome-wide methylation using DNA from fresh frozen tumors from 271 cases, applied nonsmooth nonnegative matrix factorization (nsNMF) clustering, and evaluated clinical associations and biological pathways. Results: Two approximately equally sized clusters that associated with several clinical features were identified. Compared with Cluster 2 (N = 137), Cluster 1 cases (N = 134) presented at a more advanced stage, were less likely to be of Asian ancestry, and tended to have poorer outcomes including macroscopic residual disease following primary debulking surgery (P < 0.10). Subset analyses of targeted tumor sequencing and IHC data revealed that Cluster 1 tumors showed TP53 mutation and abnormal p53 expression, and Cluster 2 tumors showed aneuploidy and ARID1A/PIK3CA mutation (P < 0.05). Cluster-defining CpGs included 1,388 CpGs residing within 200 bp of the transcription start sites of 977 genes; 38% of these genes (N = 369 genes) were differentially expressed across cluster in transcriptomic subset analysis (P < 10−4). Differentially expressed genes were enriched for six immune-related pathways, including IFNα and IFNγ responses (P < 10−6). Conclusions: DNA methylation clusters in OCCC correlate with disease features and gene expression patterns among immune pathways. Impact: This work serves as a foundation for integrative analyses that better understand the complex biology of OCCC in an effort to improve potential for development of targeted therapeutics.

Abstract Copy number alterations and loss of heterozygosity (LOH) are common in ovarian tumors, including those on the X chromosome. In females, one of the two copies of the X chromosome is transcriptionally silenced during embryonic development in the epigenetic process of X chromosome inactivation. Specifically, the long non-coding RNA XIST is expressed from the inactive X (Xi) and triggers chromosome-wide DNA methylation. In breast and ovarian cancer cell line studies, Xi deletion with concomitant duplication of the active X (Xa) has been observed. We sought to examine which copy of the X chromosome, Xi or Xa, was gained or lost in a set of primary ovarian tumors, using levels of XIST expression as a marker of X chromosome inactivation. To determine which copy of the X chromosome harbors the alterations, we compared local copy number and LOH in Xq13.2 to the levels of XIST expression in a set of N=134 primary tumors from Mayo Clinic ovarian cancer patients. Associations with XIST expression were examined using ANOVA, with copy number of two and absence of LOH as the reference level. Associations between expression of XIST and expression of other genes were examined with a mixed effects model, to account for the repeated observations across patients, after adjusting for local copy number and LOH. Associations with XIST expression and overall survival were performed with Cox regression. Additional analyses were performed in a subset of 24 patient tumors with X chromosome-wide alterations to simplify interpretation, including a visual examination of chromosome-wide DNA methylation patterns. Analyses were replicated in N=106 ovarian tumors from TCGA with X chromosome-wide alterations. Across N=134 ovarian tumors from Mayo Clinic, abnormal copy number (not equal to two) was associated with reduced XIST expression (p=0.0016). Levels of XIST expression were similar for tumors with one copy and tumors with three or more copies. Similarly, levels of XIST expression were also lower for tumors with LOH (p=5.2E-5). Reduced XIST expression was also associated with poorer survival, after adjusting for age (p=0.02). Results were consistent in the subset of tumors with whole chromosome alterations (pCN=0.0013, pLOH=0.0019). For these tumors, when LOH was present, XIST expression was low and the DNA methylation distribution is bi-modal, suggesting that the inactive X was lost and the active X was gained. Furthermore, after adjusting for copy number and LOH, XIST expression was weakly positively correlated with the median expression of other genes (R2=0.04, p=0.026). In N=106 TCGA tumors with whole X chromosome alterations, XIST expression was also reduced in tumors with abnormal copy number (p=0.006) and with LOH (p=1.5E-10). Taken together, because XIST is expressed from Xi and not Xa, associations of reduced XIST expression with abnormal copy number and presence of LOH suggest that Xi is frequently lost and Xa is gained in ovarian tumors, consistent with cell line studies. These results should be further validated in larger sample sets and examined for association with clinical outcome. Citation Format: Yilin Song, Bryan M. McCauley, Melissa C. Larson, Sebastian M. Armasu, Kate Lawrenson, Ellen L. Goode, Nicholas B. Larson, Stacey J. Winham. Evidence of decreased X chromosome inactivation in primary ovarian tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2452.

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 Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. Significance: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene. See related commentary by Choi and Brown, p. 439

Abstract Background: Endometrioid carcinoma (EC) and clear cell carcinoma (CC) histotypes of epithelial ovarian cancer are understudied compared with the more common high-grade serous carcinomas (HGSC). We therefore sought to characterize EC and CC transcriptomes in relation to HGSC. Methods: Following bioinformatics processing and gene abundance normalization, differential expression analysis of RNA sequence data collected on fresh-frozen tumors was completed with nonparametric statistical analysis methods (55 ECs, 19 CCs, 112 HGSCs). Association of gene expression with progression-free survival (PFS) was completed with Cox proportional hazards models. Eight additional multi-histotype expression array datasets (N = 852 patients) were used for replication. Results: In the discovery set, tumors generally clustered together by histotype. Thirty-two protein-coding genes were differentially expressed across histotype (P < 1 × 10−10) and showed similar associations in replication datasets, including MAP2K6, KIAA1324, CDH1, ENTPD5, LAMB1, and DRAM1. Nine genes associated with PFS (P < 0.0001) showed similar associations in replication datasets. In particular, we observed shorter PFS time for CC and EC patients with high gene expression for CCNB2, CORO2A, CSNK1G1, FRMD8, LIN54, LINC00664, PDK1, and PEX6, whereas, the converse was observed for HGSC patients. Conclusions: The results suggest important histotype differences that may aid in the development of treatment options, particularly those for patients with EC or CC. Impact: We present replicated findings on transcriptomic differences and how they relate to clinical outcome for two of the rarer ovarian cancer histotypes of EC and CC, along with comparison with the common histotype of HGSC. Cancer Epidemiol Biomarkers Prev; 27(9); 1101–9. ©2018 AACR.

ABSTRACTX‐chromosome inactivation (XCI) epigenetically silences transcription of an X chromosome in females; patterns of XCI are thought to be aberrant in women's cancers, but are understudied due to statistical challenges. We develop a two‐stage statistical framework to assess skewed XCI and evaluate gene‐level patterns of XCI for an individual sample by integration of RNA sequence, copy number alteration, and genotype data. Our method relies on allele‐specific expression (ASE) to directly measure XCI and does not rely on male samples or paired normal tissue for comparison. We model ASE using a two‐component mixture of beta distributions, allowing estimation for a given sample of the degree of skewness (based on a composite likelihood ratio test) and the posterior probability that a given gene escapes XCI (using a Bayesian beta‐binomial mixture model). To illustrate the utility of our approach, we applied these methods to data from tumors of ovarian cancer patients. Among 99 patients, 45 tumors were informative for analysis and showed evidence of XCI skewed toward a particular parental chromosome. For 397 X‐linked genes, we observed tumor XCI patterns largely consistent with previously identified consensus states based on multiple normal tissue types. However, 37 genes differed in XCI state between ovarian tumors and the consensus state; 17 genes aberrantly escaped XCI in ovarian tumors (including many oncogenes), whereas 20 genes were unexpectedly inactivated in ovarian tumors (including many tumor suppressor genes). These results provide evidence of the importance of XCI in ovarian cancer and demonstrate the utility of our two‐stage analysis.