Kanetsky, Peter A.

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.

Abstract Background The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci. Methods We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci. Results We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci. Conclusions Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.

Abstract Autophagy has been linked with melanoma, but no polymorphisms in autophagy related (ATG) genes have been investigated for association with melanoma prognostic indicators and survival. We examined 5 ATG gene single nucleotide polymorphisms (SNPs) in a large international multicenter population-based case-control study of melanoma. DNA from 911 melanoma patients was genotyped for five SNPs with a known or suspected impact on autophagic flux. While we did not identify an association with survival, a significant association was identified between the minor allele for an ATG16L polymorphism (rs2241880) and a decrease in Breslow thickness (p = 0.03), earlier tumor stage at diagnosis (OR 0.47, 95% CI 0.27-0.81, p = 0.02) and younger age at diagnosis (p = 0.02). In addition, two SNPs in ATG5 (rs2245214 and rs510432) were found to be significantly associated with increased tumor stage of melanoma (OR 1.84 95% CI 1.12-3.02, p = 0.05; OR 1.47 95% CI 1.11-1.94, p = 0.03). Finally, we identified inverse associations between the minor allele of rs2245214 and melanomas on the scalp or neck (OR 0.20, 95% CI 0.05-0.86, p = 0.03); rs1864182 (OR 0.42, 95% CI 0.21-0.88, p = 0.02) and brisk TILs, and rs510432 (OR 0.55 95% CI 0.34-0.87, p = 0.01) with non-brisk TILs, although they were not globally significant. In summary, our data suggests that ATG SNPs, while not associated with survival, may be associated with Breslow thickness, tumor stage, age at diagnosis, and aggressive histopathological factors. These associations could contribute to our current understanding of the significant role of autophagy in melanoma progression. Citation Format: Kirsten A. m. White, Li Luo, Todd A. Thompson, Salina Torres, Chien-An A. Hu, Nancy E. Thomas, Hoda Anton-Culver, Stephen B. Gruber, Lynn From, Klaus J. Busam, Irene Orlow, Peter A. Kanetsky, Lorraine D. Marrett, Richard P. Gallagher, Roberto Zanetti, Stefano Rosso, Terry Dwyer, Anne E. Cust, Allison Venn, Colin B. Begg, Marianne Berwick, Jenna Lillyquist. Variants in autophagy related genes and clinical characteristics in melanoma: a population-based study. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1016.

Abstract Genome wide association studies (GWAS) have mapped multiple independent cancer risk loci (n = 6) to a small region on chr5p15.33 for at least ten distinct cancers, including bladder, breast, glioma, lung, melanoma, non-melanoma skin, ovarian, pancreas, prostate, and testicular germ cell cancer. This region harbors two plausible target genes, TERT which encodes the catalytic subunit of telomerase reverse transcriptase which maintains chromosome ends by adding telomeres repeats, and CLPTM1L which encodes the cleft lip and palate transmembrane protein 1-like protein which promotes cancer cell growth, protect cells from apoptosis, and can induce abnormal cytokinesis. The most significant pancreatic cancer GWAS SNP on chr5p15.33 was rs401681 (P = 3.7×10−7, OR = 1.19), located in the 13th intron of the CLPTM1L gene and within the independent multi-cancer risk locus in this region most distant from TERT. Imputation and fine mapping in pancreatic cancer resolved this signal by three orders of magnitude (P = 1.4×10−10, OR = 1.30) to a set of seven highly correlated SNPs. Electrophoretic mobility shift assays (EMSA) and luciferase assays across these SNPs led us to a single SNP, rs36115365, that showed allele-specific effects in both assays and overlapped with prominent ENCODE marks indicating regulatory potential. Examining this SNP across cell lines derived from multiple types of cancer linked to this locus, specifically pancreatic, testicular, lung, and melanoma, established a consistent pattern of a specific protein binding and enhanced regulatory activity for the risk allele across eight cancer cell lines (two cell lines per cancer type). siRNA-based targeting of the putative gene regulatory-region harboring rs36115365 resulted in a strong inhibition of TERT expression (average 60%, range 45-85%) but no effect on CLPTM1L expression. This inhibition of TERT expression was stronger from the pancreatic cancer risk as compared to the protective allele. Quantitative mass spectrometry identified Zinc finger protein 148 (ZNF148) as the protein specifically binding the risk allele, further supported by direct and allele-specific binding of purified recombinant ZNF148 in EMSA assays. Lastly, siRNA-mediated knockdown of ZNF148 resulted in significant reduction of TERT but not CLPTM1L expression across multiple cancer cell lines. Our results indicate that the pancreatic cancer GWAS signal at the single independent chr5p15.33 multi-cancer risk locus most distant from TERT may be explained by a single SNP that influences TERT expression via ZNF148. Citation Format: Kevin M. Brown, Jun Fang, Jinping Jia, Zhaoming Wang, Matthew Makowski, Tongwu Zhang, Jason Hoskins, Jiyeon Choi, Younghun Han, Mingfeng Zhang, Mai Xu, Peter Kanetsky, Andresson Thorkell, Gloria M. Petersen, Katherine L. Nathanson, Christopher I. Amos, Maria T. Landi, Stephen J. Chanock, Michiel Vermeulen, Laufey T. Amundadottir. Functional characterization of a multicancer risk locus on chr5p15.33 reveals regulation of TERT by ZNF148. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4610. doi:10.1158/1538-7445.AM2015-4610