Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants

The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.

Prevention of Epithelial Ovarian Cancer

Given the challenges with achieving effective and durable treatment for epithelial ovarian cancer, primary prevention is highly desirable. Fortunately, decades of research have provided evidence for several strategies that can be deployed to optimize risk reduction. These include surgery, chemoprevention, and lifestyle factor modifications. These broad categories vary in terms of the magnitude of risk reduction possible, the possible short-term and long-term side effects, the degree of difficulty, and acceptability. Thus, the concept of a risk-based model to personalize preventive interventions is advocated to guide discussion between care providers and women at risk. For women with inherited major gene mutations that greatly increase risk of ovarian cancer, surgical approaches have favorable risk to benefit ratios. Chemoprevention and lifestyle factor modifications portend a lower degree of risk reduction but confer lower risk of undesirable side effects. Since complete prevention is not currently possible, better methods for early detection remain a high priority.

Evidence of Novel Susceptibility Variants for Prostate Cancer and a Multiancestry Polygenic Risk Score Associated with Aggressive Disease in Men of African Ancestry

BACKGROUND

Genetic factors play an important role in prostate cancer (PCa) susceptibility.

OBJECTIVE

To discover common genetic variants contributing to the risk of PCa in men of African ancestry.

DESIGN, SETTING, AND PARTICIPANTS

We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness.

RESULTS AND LIMITATIONS

Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10-4).

CONCLUSIONS

This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry.

PATIENT SUMMARY

In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease.

Abstract 6065: Patterns of dysregulated coding and noncoding gene expression in high-grade serous ovarian carcinomas

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.

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

A Rare Germline HOXB13 Variant Contributes to Risk of Prostate Cancer in Men of African Ancestry

A rare African ancestry-specific germline deletion variant in HOXB13 (X285K, rs77179853) was recently reported in Martinican men with early-onset prostate cancer. Given the role of HOXB13 germline variation in prostate cancer, we investigated the association between HOXB13 X285K and prostate cancer risk in a large sample of 22 361 African ancestry men, including 11 688 prostate cancer cases. The risk allele was present only in men of West African ancestry, with an allele frequency in men that ranged from 0.40% in Ghana and 0.31% in Nigeria to 0% in Uganda and South Africa, with a range of frequencies in men with admixed African ancestry from North America and Europe (0-0.26%). HOXB13 X285K was associated with 2.4-fold increased odds of prostate cancer (95% confidence interval [CI] = 1.5-3.9, p = 2 × 10^-4), with greater risk observed for more aggressive and advanced disease (Gleason ≥8: odds ratio [OR] = 4.7, 95% CI = 2.3-9.5, p = 2 × 10^-5; stage T3/T4: OR = 4.5, 95% CI = 2.0-10.0, p = 2 × 10^-4; metastatic disease: OR = 5.1, 95% CI = 1.9-13.7, p = 0.001). We estimated that the allele arose in West Africa 1500-4600 yr ago. Further analysis is needed to understand how the HOXB13 X285K variant impacts the HOXB13 protein and function in the prostate. Understanding who carries this mutation may inform prostate cancer screening in men of West African ancestry. PATIENT SUMMARY: A rare African ancestry-specific germline deletion in HOXB13, found only in men of West African ancestry, was reported to be associated with an increased risk of overall and advanced prostate cancer. Understanding who carries this mutation may help inform screening for prostate cancer in men of West African ancestry.

Functional analysis of the 1p34.3 risk locus implicates GNL2 in high-grade serous ovarian cancer

The high-grade serous ovarian cancer (HGSOC) risk locus at chromosome 1p34.3 resides within a frequently amplified genomic region signifying the presence of an oncogene. Here, we integrate in silico variant-to-function analysis with functional studies to characterize the oncogenic potential of candidate genes in the 1p34.3 locus. Fine mapping of genome-wide association statistics identified candidate causal SNPs local to H3K27ac-demarcated enhancer regions that exhibit allele-specific binding for CTCF in HGSOC and normal fallopian tube secretory epithelium cells (FTSECs). SNP risk associations colocalized with eQTL for six genes (DNALI1, GNL2, RSPO1, SNIP1, MEAF6, and LINC01137) that are more highly expressed in carriers of the risk allele, and three (DNALI1, GNL2, and RSPO1) were upregulated in HGSOC compared to normal ovarian surface epithelium cells and/or FTSECs. Increased expression of GNL2 and MEAF6 was associated with shorter survival in HGSOC with 1p34.3 amplifications. Despite its activation of β-catenin signaling, RSPO1 overexpression exerted no effects on proliferation or colony formation in our study of ovarian cancer and FTSECs. Instead, GNL2, MEAF6, and SNIP1 silencing impaired in vitro ovarian cancer cell growth. Additionally, GNL2 silencing diminished xenograft tumor formation, whereas overexpression stimulated proliferation and colony formation in FTSECs. GNL2 influences 60S ribosomal subunit maturation and global protein synthesis in ovarian cancer and FTSECs, providing a potential mechanism of how GNL2 upregulation might promote ovarian cancer development and mediate genetic susceptibility of HGSOC.

Morphologic and molecular correlates of EZH2 as a predictor of platinum resistance in high-grade ovarian serous carcinoma

BACKGROUND

Enhancer of zesta homologue 2 (EZH2) is an essential component of polycomb repressive complex 2 (PRC2) that contributes to tumor progression and chemo-resistance. The aim of this study was to comprehensively assess the prognostic value of EZH2 across the morphologic and molecular spectra of high-grade serous ovarian carcinoma (HGSOC) by utilizing both immunohistochemistry (IHC) and proteogenomic technologies.

METHODS

IHC of EZH2 was performed using a tissue microarray of 79 HGSOC scored (+/-) for lymphovascular invasion (LVI), tumor-infiltrating lymphocytic aggregates ≥1 mm (TIL) and architectural growth patterns. The association of EZH2 H-score with response to therapy and overall survival was evaluated by tumor features. We also evaluated EZH2 transcriptional (RNA sequencing) and protein (mass spectrometry) expression from bulk tumor samples from 336 HGSOC from The Cancer Genome Atlas (TCGA). EZH2 expression and co-expression networks were compared by clinical outcomes.

RESULTS

For HGSOC without TIL (58%), EZH2 expression was almost 2-fold higher in platinum resistant tumors (P = 0.01). Conversely, EZH2 was not associated with platinum resistance among TIL+ HGSOC (P = 0.41). EZH2 expression was associated with reduced survival for tumors with LVI (P = 0.04). Analysis of TCGA found higher EZH2 expression in immunoreactive and proliferative tumors (P = 6.7 × 10^- 5) although protein levels were similar across molecular subtypes (P = 0.52). Both mRNA and protein levels of EZH2 were lower in platinum resistant tumors although they were not associated with survival. Co-expression analysis revealed EZH2 networks totaling 1049 mRNA and 448 proteins that were exclusive to platinum sensitive or resistant tumors. The EZH2 network in resistant HGSOC included CARM1 which was positively correlated with EZH2 at both mRNA (r = 0.33, p = 0.003) and protein (r = 0.14, P = 0.01) levels. Further, EZH2 co-expression with CARM1 corresponded to a decreased prognostic significance of EZH2 expression in resistant tumors.

CONCLUSIONS

Our findings demonstrate that EZH2 expression varies based on its interactions with immunologic pathways and tumor microenvironment, impacting the prognostic interpretation. The association between high EZH2 expression and platinum resistance in TIL- HGSOC warrants further study of the implications for therapeutic strategies.

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.

Cross-Cancer Genome-Wide Association Study of Endometrial Cancer and Epithelial Ovarian Cancer Identifies Genetic Risk Regions Associated with Risk of Both Cancers

BACKGROUND

Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers.

METHODS

Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data.

RESULTS

Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10-5). We found seven loci associated with risk for both cancers (P Bonferroni < 2.4 × 10-9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10-7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation.

CONCLUSIONS

Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis.

IMPACT

Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.

The effect of sample size on polygenic hazard models for prostate cancer

We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.

Abstract A32: Process improvement in online consenting for the Moffitt Cancer Center Total Cancer Care biobanking protocol

Introduction: Broad-based institutional biobanking protocols are crucial for advancing personalized medicine in cancer research. However, in-person consenting is resource intensive and interrupts clinic flow. Ethical standards support online consenting for biobanking protocols, which has the potential to reach more participants for enrollment. Herein, we discuss challenges in implementing broad-based online patient consenting at the Moffitt Cancer Center (MCC) for our institutional biobanking protocol, Total Cancer Care (TCC), and subsequent steps to better integrate this process with clinical care on-boarding. We hypothesized that implementation of online patient consenting would broaden patient enrollment into TCC and the redesigned process would increase the number of online patient consents by at least 5-fold.

Methods: TCC started as the institutional biobanking protocol in 2006. TCC online consent was implemented in Feb. 2013 (Phase 1) and redesigned in Oct. 2018 (Phase 2). Phase 1 was developed with the guidance of ethicists and patient advisors, and consisted of (a) communication via email, (b) education online with text, video, and FAQs, (c) review and initialing of the Informed Consent form (ICF), and (d) typed name signature on ICF. The Phase 2 redesign created a more streamlined process that was integrated into the MCC New Patient To-Do list, a clinical on-boarding platform. The revised version used interactive material, a shorter animated video, and an electronically signed ICF. We compared the number of online patient consents in Phase 1 and 2 and have preliminary data on patient acceptance of Phase 2.

Results: Since 2006, 108,898 MCC patients enrolled into TCC. 342 patients enrolled online in Phase I between 2013–2018 (5/mo). In the initial 6 weeks of Phase 2, there was a 13-fold increase in online consenting (n=98, 65/mo) compared to Phase 1. According to web analytics, TCC pages in Phase 2 were viewed 991 times compared to 432 views over 6 weeks in Phase 1. In general, patient characteristics were similar between those who enrolled online and those who enrolled in person during the same timeframe, with a slightly higher percentage of online vs. in-person enrollees being female (57% vs. 53%, respectively). In a small survey of new patients who viewed the clinical on-boarding platform in Phase 2, 76% reviewed the TCC material without issue whereas 20% did not review the TCC material.

Conclusions: While online consenting has tremendous potential, we had very low uptake of patient education and consenting in our initial design (Phase 1). Challenges included a lack of visibility within the patient portal and a dependency on email as the primary mode of directing patients to online consenting. Alternatively, we have seen initial success with our second phase of online consenting that was directly integrated with patient on-boarding. Initial success highlights the potential of this modality to increase patient enrollment into biobanking studies. Further evaluation of this approach is ongoing.

Citation Format: Erin M. Siegel, Kyle P. Hawkins, Lynne Hildreth, Timothy Grose, David Stringfellow, Amanda Bloomer, Shelley Tworoger, Dana Rollison, Scott Gilbert, Thomas A. Sellers. Process improvement in online consenting for the Moffitt Cancer Center Total Cancer Care biobanking protocol [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr A32.

A Genetic Risk Score to Personalize Prostate Cancer Screening, Applied to Population Data

BACKGROUND

A polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening.

METHODS

United Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3-T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups.

RESULTS

The expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age.

CONCLUSIONS

PHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS.

IMPACT

Personalized genetic risk assessments could inform prostate cancer screening decisions.

A Germline Variant at 8q24 Contributes to Familial Clustering of Prostate Cancer in Men of African Ancestry

Although men of African ancestry have a high risk of prostate cancer (PCa), no genes or mutations have been identified that contribute to familial clustering of PCa in this population. We investigated whether the African ancestry-specific PCa risk variant at 8q24, rs72725854, is enriched in men with a PCa family history in 9052 cases, 143 cases from high-risk families, and 8595 controls of African ancestry. We found the risk allele to be significantly associated with earlier age at diagnosis, more aggressive disease, and enriched in men with a PCa family history (32% of high-risk familial cases carried the variant vs 23% of cases without a family history and 12% of controls). For cases with two or more first-degree relatives with PCa who had at least one family member diagnosed at age <60 yr, the odds ratios for TA heterozygotes and TT homozygotes were 3.92 (95% confidence interval [CI] = 2.13-7.22) and 33.41 (95% CI = 10.86-102.84), respectively. Among men with a PCa family history, the absolute risk by age 60 yr reached 21% (95% CI = 17-25%) for TA heterozygotes and 38% (95% CI = 13-65%) for TT homozygotes. We estimate that in men of African ancestry, rs72725854 accounts for 32% of the total familial risk explained by all known PCa risk variants. PATIENT SUMMARY: We found that rs72725854, an African ancestry-specific risk variant, is more common in men with a family history of prostate cancer and in those diagnosed with prostate cancer at younger ages. Men of African ancestry may benefit from the knowledge of their carrier status for this genetic risk variant to guide decisions about prostate cancer screening.

Abstract 3517: A germline variant at 8q24 contributes to familial clustering of prostate cancer in men of African ancestry

Germline variation at 8q24 is the strongest risk factor for prostate cancer (PCa) across all racial and ethnic populations. While most 8q24 associations have been observed across populations, rs72725854 [T risk allele frequency ~6%] is only found in men of African ancestry and is the strongest known genome-wide association signal for PCa in this population. We investigated whether the T allele of rs72725854 is associated with PCa family history and age at diagnosis, characteristics known to have a strong genetic component. Analyses were performed using a sample of 9,052 cases and 8,595 controls from the African Ancestry Prostate Cancer (AAPC) GWAS Consortium and the ELLIPSE/PRACTICAL OncoArray Consortium. Participants were unselected for PCa family history. Among cases, 23.7% carried at least one copy of the T allele versus 11.6% of controls. The OR was 2.29 (95% CI=2.10–2.49) for TA heterozygotes and 5.04 (95% CI=3.36–7.55) for TT homozygotes. The percentage of cases carrying the T allele was significantly greater for men with a PCa family history (27.4% vs. 22.7% without a family history, p=0.002) and for men diagnosed &lt;60 (28.2% vs. 21.6% if over ≥60, p=0.002). The mean age at diagnosis for men with the TT genotype was 61.1 years (sd=8.7), compared to 62.7 (sd=9.1) for TA heterozygotes and 64.3 (sd=8.9) for AA homozygotes (p=5.7E-14). Carrier frequency was highest among men with both a positive family history and an early diagnosis (30.8%). The T allele was also over-represented in cases with more advanced PCa, with carrier frequencies ranging from 26% for lethal PCa (metastatic disease, PSA&gt;100 ng/ml or death from PCa), 25.4% for high-risk disease (stage T3/T4, Gleason 8-10, or PSA=20-100 ng/ml), 24.6% for intermediate-risk disease (Gleason=7, stage T1/T2, and PSA=10-20 ng/ml), and 21.4% for low-risk disease (Gleason&lt;7, stage T1/T2, and PSA&lt;10 ng/ml) (p=0.026). We also examined whether the risk allele is over-represented in 144 men from PCa families, with multiple first- and/or second-degree relatives with PCa or men diagnosed with PCa ≤55 years old. Among affected probands, 32.7% carried the risk allele, with 3.5% being homozygous carriers. The OR for TA heterozygotes and TT homozygotes was 3.41 (95% CI=2.33–4.98) and 11.06 (95% CI=3.92–31.18), respectively. Among men without a family history, the absolute risk for PCa by age 60 for non-risk allele carriers was 4.3%, compared to 9.0% and 15.6% for TA heterozygotes and TT homozygotes, respectively. Absolute risks by age 60 were higher among men with a family history of prostate cancer, reaching 9.0% for non-risk allele carriers, compared to 20.8% and 37.7% for TA heterozygotes and TT homozygotes, respectively. Given the high PCa risk conveyed by rs72725854 and the greater frequency of the allele in men with more aggressive and lethal disease, carriers of the risk allele would benefit from earlier and more regular PSA screening.

Citation Format: Burcu F. Darst, Jeannette T. Bensen, Sue A. Ingles, Benjamin A. Rybicki, Barbara Nemesure, Esther M. John, Jay H. Fowke, Victoria L. Stevens, Sonja I. Berndt, Chad D. Huff, Jong Y. Park, Wei Zheng, Elaine A. Ostrander, Shiv Srivastava, John Carpten, Thomas A. Sellers, Maureen Sanderson, Dana C. Crawford, Olivier Cussenot, Jennifer Cullen, Rick A. Kittles, Jianfeng Xu, Zsofia Kote-Jarai, Luc Multigner, Marie-Elise Parent, Florence Menegaux, Geraldine Cancel-Tassin, Adam S. Kibel, Eric A. Klein, Phyllis J. Goodman, Jennifer J. Hu, Graham Casey, Anselm J. Hennis, Ian M. Thompson, Robin Leach, James L. Mohler, Elizabeth T. Fontham, Gary J. Smith, Jack A. Taylor, Rosalind A. Eeles, Laurent Brureau, Stephen J. Chanock, Stephen Watya, Janet L. Stanford, Diptasri Mandal, William B. Isaacs, Kathleen A. Cooney, William J. Blot, David V. Conti, Christopher A. Haiman. A germline variant at 8q24 contributes to familial clustering of prostate cancer in men of African ancestry [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 3517.

Abstract A30: Super-enhancer-associated long noncoding RNA UCA1 interacts directly with AMOT to inhibit Hippo signaling pathway in epithelial ovarian cancer

Long noncoding RNAs (lncRNAs) have emerged as critical regulators of tumorigenesis and yet their mechanistic role remains challenging to characterize. Here, we present LncRNA Interpreter, a strategy integrating functional proteomics with interacting proteins to characterize lncRNAs. Its robustness is exemplified by lncRNA Urothelial Cancer Associated 1 (UCA1), a driver of ovarian cancer development. Reverse phase protein array (RPPA) analysis indicates that UCA1 inhibits Hippo signaling pathway and in vivo RNA antisense purification (iRAP) of UCA1 interacting proteins identified angiomotin (AMOT), a known YAP regulator, as direct binding partner. Loss-of-function experiments show that AMOT mediates Hippo signaling pathway inhibition by UCA1. UCA1 enhances the AMOT-YAP interaction to prevent YAP phosphorylation and facilitate its nuclear translocation. Together, our LncRNA Interpreter pipeline identified UCA1 as an lncRNA regulator of the Hippo signaling pathway and highlighted the UCA1-AMOT-YAP signaling axis in ovarian cancer development. LncRNA Interpreter can readily be applied to other lncRNAs implicated in complex diseases.

Citation Format: Xianzhi Lin, Tassja J. Spindler, Marcos A de Souza Fonseca, Rosario I. Corona, Ji-Heui Seo, Felipe S Dezem, Lewyn Li, Janet M. Lee, Henry W. Long, Thomas A. Sellers, Beth Y. Karlan, Houtan Noushmehr, Matthew L. Freedman, Simon A. Gayther, Kate Lawrenson. Super-enhancer-associated long noncoding RNA UCA1 interacts directly with AMOT to inhibit Hippo signaling pathway in epithelial ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on the Hippo Pathway: Signaling, Cancer, and Beyond; 2019 May 8-11; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(8_Suppl):Abstract nr A30.

Assessment of polygenic architecture and risk prediction based on common variants across fourteen cancers

Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence.

Abstract B34: LINC00886, a risk locus-associated long noncoding RNA, promotes ovarian cancer progression

Background: Recent genome-wide association studies (GWAS) have identified a plethora of SNPs that cluster at loci associated with increased epithelial ovarian cancer (EOC) risk. The functional validation of genes in such risk loci focused primarily on the protein-coding space while long noncoding RNAs (lncRNAs) were disregarded. Given the emerging evidence that lncRNAs can act as oncogenes and tumor suppressors, we seek to evaluate the functional role of EOC risk locus-associated lncRNAs in EOC development.

Methods: We interrogated GWAS for EOC and the FANTOM-CAT database for lncRNAs to identify EOC risk-associated SNPs that lie within lncRNA regulatory regions. We first prioritized the lncRNAs that are associated with EOC risk loci using public databases including GTEx and TCGA. To assess the oncogenic potential of these lncRNAs, we performed in vitro functional assays such as proliferation, colony formation, anchorage-independent growth and migration by overexpressing and silencing candidate lncRNAs in fallopian tube secretory epithelial and ovarian cancer cells. To validate our findings in vivo, we intraperitoneally injected OVCAR-8 cells into immunocompromised mice and evaluated tumor growth. LncRNA subcellular localization was evaluated based on qPCR from cytoplasmic and nuclear RNA. Further, we investigated expression changes upon lncRNAs overexpression in OVCAR-8 and FT282 cells by RNA sequencing (RNA-seq) and predicted shared microRNAs (miRNA) binding sites using LncBase Predicted v.2 and TargetScanHuman 7.2.

Results: We identified 5 candidate risk locus-associated lncRNAs (CATG00000115318.1, HAGLR, LINC00886, CATG00000117550.1, and CTD-2521M24.8). Functional assays showed that LINC00886 promoted cancer cell proliferation and colony formation in vitro. Overexpression of LINC00886 in OVCAR-8 cells significantly promoted peritoneal dissemination in a xenograft model. LINC00886 was mainly localized to the cytoplasm, suggesting it could function by decoying miRNAs. Interestingly, we observed that LINC00886 overexpression increased the levels of several oncogenes, of which several (ROR2, TNFSF14, GPNMB, LTB, and ZBTB20) share miRNA binding sites with LINC00886.

Conclusion: LINC00886, a risk loci-associated lncRNA, promotes an aggressive phenotype in ovarian cancer, suggesting an oncogenic function. We are currently investigating the molecular mechanism of LINC00886 as a ceRNA in ovarian cancer progression.

Citation Format: Koji Nakamura, Brett M. Reid, Thomas A. Sellers, Florian A. Karreth. LINC00886, a risk locus-associated long noncoding RNA, promotes ovarian cancer progression [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr B34.

Identification of novel epithelial ovarian cancer loci in women of African ancestry

Women of African ancestry have lower incidence of epithelial ovarian cancer (EOC) yet worse survival compared to women of European ancestry. We conducted a genome-wide association study in African ancestry women with 755 EOC cases, including 537 high-grade serous ovarian carcinomas (HGSOC) and 1,235 controls. We identified four novel loci with suggestive evidence of association with EOC (p < 1 × 10-6 ), including rs4525119 (intronic to AKR1C3), rs7643459 (intronic to LOC101927394), rs4286604 (12 kb 3' of UGT2A2) and rs142091544 (5 kb 5' of WWC1). For HGSOC, we identified six loci with suggestive evidence of association including rs37792 (132 kb 5' of follistatin [FST]), rs57403204 (81 kb 3' of MAGEC1), rs79079890 (LOC105376360 intronic), rs66459581 (5 kb 5' of PRPSAP1), rs116046250 (GABRG3 intronic) and rs192876988 (32 kb 3' of GK2). Among the identified variants, two are near genes known to regulate hormones and diseases of the ovary (AKR1C3 and FST), and two are linked to cancer (AKR1C3 and MAGEC1). In follow-up studies of the 10 identified variants, the GK2 region SNP, rs192876988, showed an inverse association with EOC in European ancestry women (p = 0.002), increased risk of ER positive breast cancer in African ancestry women (p = 0.027) and decreased expression of GK2 in HGSOC tissue from African ancestry women (p = 0.004). A European ancestry-derived polygenic risk score showed positive associations with EOC and HGSOC in women of African ancestry suggesting shared genetic architecture. Our investigation presents evidence of variants for EOC shared among European and African ancestry women and identifies novel EOC risk loci in women of African ancestry.

Empirically-derived synthetic populations to mitigate small sample sizes

Limited sample sizes can lead to spurious modeling findings in biomedical research. The objective of this work is to present a new method to generate synthetic populations (SPs) from limited samples using matched case-control data (n = 180 pairs), considered as two separate limited samples. SPs were generated with multivariate kernel density estimations (KDEs) with unconstrained bandwidth matrices. We included four continuous variables and one categorical variable for each individual. Bandwidth matrices were determined with Differential Evolution (DE) optimization by covariance comparisons. Four synthetic samples (n = 180) were derived from their respective SPs. Similarity between observed samples with synthetic samples was compared assuming their empirical probability density functions (EPDFs) were similar. EPDFs were compared with the maximum mean discrepancy (MMD) test statistic based on the Kernel Two-Sample Test. To evaluate similarity within a modeling context, EPDFs derived from the Principal Component Analysis (PCA) scores and residuals were summarized with the distance to the model in X-space (DModX) as additional comparisons. Four SPs were generated from each sample. The probability of selecting a replicate when randomly constructing synthetic samples (n = 180) was infinitesimally small. MMD tests indicated that the observed sample EPDFs were similar to the respective synthetic EPDFs. For the samples, PCA scores and residuals did not deviate significantly when compared with their respective synthetic samples. The feasibility of this approach was demonstrated by producing synthetic data at the individual level, statistically similar to the observed samples. The methodology coupled KDE with DE optimization and deployed novel similarity metrics derived from PCA. This approach could be used to generate larger-sized synthetic samples. To develop this approach into a research tool for data exploration purposes, additional evaluation with increased dimensionality is required. Moreover, given a fully specified population, the degree to which individuals can be discarded while synthesizing the respective population accurately will be investigated. When these objectives are addressed, comparisons with other techniques such as bootstrapping will be required for a complete evaluation.

Calibrated Breast Density Measurements

RATIONALE AND OBJECTIVES

Mammographic density is an important risk factor for breast cancer, but translation to the clinic requires assurance that prior work based on mammography is applicable to current technologies. The purpose of this work is to evaluate whether a calibration methodology developed previously produces breast density metrics predictive of breast cancer risk when applied to a case-control study.

MATERIALS AND METHODS

A matched case control study (n = 319 pairs) was used to evaluate two calibrated measures of breast density. Two-dimensional mammograms were acquired from six Hologic mammography units: three conventional Selenia two-dimensional full-field digital mammography systems and three Dimensions digital breast tomosynthesis systems. We evaluated the capability of two calibrated breast density measures to quantify breast cancer risk: the mean (PGm) and standard deviation (PGsd) of the calibrated pixels. Matching variables included age, hormone replacement therapy usage/duration, screening history, and mammography unit. Calibrated measures were compared to the percentage of breast density (PD) determined with the operator-assisted Cumulus method. Conditional logistic regression was used to generate odds ratios (ORs) from continuous and quartile (Q) models with 95% confidence intervals. The area under the receiver operating characteristic curve (Az) was also used as a comparison metric. Both univariate models and models adjusted for body mass index and ethnicity were evaluated.

RESULTS

In adjusted models, both PGsd and PD were statistically significantly associated with breast cancer with similar Az of 0.61-0.62. The corresponding ORs and confidence intervals were also similar. For PGsd, the OR was 1.34 (1.09, 1.66) for the continuous measure and 1.83 (1.11, 3.02), 2.19 (1.28, 3.73), and 2.20 (1.26, 3.85) for Q2-Q4. For PD, the OR was 1.43 (1.16, 1.76) for the continuous measure and 0.84 (0.52, 1.38), 1.96 (1.19, 3.23), and 2.27 (1.29, 4.00) for Q2-Q4. The results for PGm were slightly attenuated and not statistically significant. The OR was 1.22 (0.99, 1.51) with Az = 0.60 for the continuous measure and 1.24 (0.78, 1.97), 0.98 (0.60, 1.61), and 1.26, (0.77, 2.07) for Q2-Q4 with Az = 0.60.

CONCLUSION

The calibrated PGsd measure provided significant associations with breast cancer comparable to those given by PD. The calibrated PGm performed slightly worse. These findings indicate that the calibration approach developed previously replicates under more general conditions.

Abstract 1562: Germline polymorphisms in cancer stem cell genes associate with survival among women with high-grade serous ovarian cancer

Background: Cancer stem cells (CSCs) are a rare population of tumor initiating cells associated with chemoresistance, recurrence and poor survival. Our group previously correlated germline variants in ovarian CSC-related genes with chemoresponse in 362 high-grade serous ovarian cancer (HGSOC) patients. Here, we evaluate CSC variants in a large, independent population to determine their association with overall (OS) and progression-free (PFS) survival.

Methods: Over 2,500 women of European ancestry diagnosed with HGSOC who underwent cytoreductive surgery have been followed for clinical outcome and genotyped on the OncoArray. We identified 4,209 common (MAF&gt;0.01) short polymorphisms (SNPs) that were genotyped or well-imputed (r2&gt;0.70) within 26 CSC-related genes. Associations with OS and PFS were estimated with additive genetic cox proportional hazards models adjusted for ancestral principal components, age at diagnosis, and study. Residual disease after surgery (≤1cm vs. &gt;1cm), and stage at diagnosis (advanced vs. local) were assessed for confounding (covariate), modification (interaction), and mediational (logistic regression) effects. For each SNP, the best fit model was adopted and p-values were adjusted for multiple testing using a false discovery rate (FDR) &lt; 15% threshold. Primary analyses evaluated 1,254 patients who received standard chemotherapy; secondary analysis included 2,659 patients, regardless of chemotherapy regimen.

Results: Two genes that were previously associated with response to chemotherapy (ESRRB, ALDH1A1) and two new genes (NOTCH2, CXCR4) were associated with OS and PFS. Eight variants within ESRRB were significantly associated with improved OS and comprised four independent (rsq&lt;0.2) intronic variants. The top hit rs7160216 (HR=0.61, P=8.4x10-7, FDR=0.004) was modified by residual disease with the association attenuated in optimally debulked patients (HR=0.88, P interaction=0.05). One independent variant in ALDH1A1 was associated with an almost 2-fold lower OS (rs17563633 HR=1.80, P=7.2x10-5, FDR=0.03) and a ~6-fold lower OS in suboptimally debulked patients (HR=5.8, P interaction=9.2x10-4). Analysis of all patients, irrespective of chemotherapy, identified a significant association for rs17848385 in CXCR4 with reduced OS (HR=1.36, P=1.3x10-5, FDR=0.05). Aforementioned variants also displayed similar, significant associations with PFS though without modification. No significant SNP effects on survival were mediated through residual disease or stage; however, uncorrelated SNP blocks in ESRRB and ALDH1A1 associated with these factors proposing possible genomic interaction.

Conclusion: Polymorphisms in CSC genes are associated with survival of HGSOC and more research is needed to clarify the prognostic value of these genes, particularly as carriers may benefit from emerging therapies targeting CSC pathways.

Citation Format: Brett M. Reid, Jennifer B. Permuth, Zhihua Chen, Ann Chen, Thomas A. Sellers, on behalf of the Ovarian Cancer Association Consortium (OCAC). Germline polymorphisms in cancer stem cell genes associate with survival among women with high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1562.

Spatial Correlation and Breast Cancer Risk

We present a novel method for evaluating local spatial correlation structure in two-dimensional (2D) mammograms and evaluate its capability for risk prediction as one possible application. Two matched case-control studies were analyzed. Study 1 included women (N = 588 pairs) with mammograms acquired with either Hologic Selenia full field digital mammography (FFDM) units or Hologic Dimensions digital breast tomosynthesis units. Study 2 included women (N =180 pairs) with mammograms acquired with a General Electric Senographe 2000D FFDM unit. Matching variables included age, HRT usage/duration, screening history, and mammography unit. Local autocorrelation functions were determined with Fourier analysis and compared with a template defined as a 2D double-sided exponential function with one spatial extent parameter: n = 4, 12, 24, 50, 74, 100, and 124, where (n+1)×(n+1) is the area of the local spatial extent measured in pixels. The difference between the local correlation and template was gauged within an adjustable parameter kernel and summarized, producing two measures: the mean (m_n+1)_, and standard deviation (s_n+1). Both adjustable parameters were varied in Study 1. Select measures that produced significant associations with breast cancer were translated to Study 2. Breast cancer associations were evaluated with conditional logistic regression, adjusted for body mass index and ethnicity. Odds ratios (ORs) were estimated as per standard deviation increment with 95% confidence intervals (CIs). Two measures were selected for breast cancer association analysis in Study 1: m₇₅ and s₂₅. Both measures revealed significant associations with breast cancer: OR = 1.45 (1.23, 1.66) for m₇₅ and OR = 1.30 (1.14, 1.49) for s_25. When translating to Study 2, these measures also revealed significant associations: OR = 1.49 (1.12, 1.96) for m₇₅ and OR = 1.34 (1.06, 1.69) for s₂₅. Novel correlation metrics presented in this work produced significant associations with breast cancer risk. This approach is general and may have applications beyond mammography.

Abstract 4183: Recruiting African-American prostate cancer patients for biobank research

Significant racial disparities exist in prostate cancer (PCa) incidence and mortality rates. Exploration of the basis for disparities would be enhanced by access to data and biological specimens on men of African Ancestry (AA). Unfortunately, AA men remain underrepresented in cancer biorepositories. To address this gap, we have embarked on an effort to create a state-wide biospecimen bank focused on AA men with PCa in Florida. The objective is to collect and manage patients’ data, outcome information, and biospecimens (i.e., tumor tissue samples and saliva) from diverse AA men for research. The objective is to collect and manage patients’ data, outcome information, and biospecimens who have been diagnosed with PCa in Florida. Self-identified AA PCa patients, diagnosed between 2013 and 2017, who were living in Florida at the time of diagnosis were identified through the Florida State cancer registry. Potential participants were mailed packets describing the study, with follow-up by telephone to answer questions and obtain informed consent. Interested patients were screened for eligibility and asked to complete a questionnaire, provide a saliva sample, and provide permission to obtain their tumor tissue sample. Patients were offered up to $30 for participating in the study. The Florida Cancer Registry reported a total of 7,960 AA PCa cases during the ascertainment period. Information packets were sent to 4,898 AA. A total of 116 were found to be ineligible mainly due to deceased or non-English speaking patients. To date, 796 have consented to participate, 1,175 declined ether by mail (n=185) or phone (=985), 740 could not be located, and 2,033 have not responded to the initial information packet/phone after total of 5 attempts. This yields a participation rate of 16.3% (796/4,898). The adjusted participation rate, or the percentage of participants who consented to participate out of those who had communication with the research team, is 41% (796/1,959). Primary reasons for declining include patients stating that they are not interested (72%), too sick (8%), or too busy (5%). A significant inverse association was found between current age and participation rate (p&lt;0.0001) but not insurance status. Older AA PCa patients were found to be less likely to participate in the study. A significant association was also found between Gleason score and participation rate. AA men who had a more aggressive form of PCa (higher Gleason score) were more likely to participate in the study (p&lt;0.01). Our results demonstrate that recruiting Blacks/African-American PCa patients in the biobank study using a cancer registry is feasible, yet difficult. Despite prevailing recruitment challenges, we implemented a diverse of recruitment methods to increase reach. These recruitment methods helped identify additional avenues for targeting this population to increase participation and, ultimately, address cancer disparities among this population.

Citation Format: Jennifer Damonte, Siddhartha Roy, Carmen Benson, Kala Jamison, Hyun Park, Allan Pollack, Shahla Masood, Changdong Yeo, Young-chul Kim, Jasreman Dhillon, Kosj Yamoah, Julio Pow-Sang, Thomas A. Sellers, Clement K. Gwede, Jong Y. Park. Recruiting African-American prostate cancer patients for biobank research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4183.

Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women

OBJECTIVE

Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women.

METHODS

Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations.

RESULTS

At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10-9) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10-9). SNP rs6902488 at 6p25.2 (r2 = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10-8). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10-7) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10-7). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10-7).

CONCLUSION

While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.

Evaluation of vitamin D biosynthesis and pathway target genes reveals UGT2A1/2 and EGFR polymorphisms associated with epithelial ovarian cancer in African American Women

An association between genetic variants in the vitamin D receptor (VDR) gene and epithelial ovarian cancer (EOC) was previously reported in women of African ancestry (AA). We sought to examine associations between genetic variants in VDR and additional genes from vitamin D biosynthesis and pathway targets (EGFR, UGT1A, UGT2A1/2, UGT2B, CYP3A4/5, CYP2R1, CYP27B1, CYP24A1, CYP11A1, and GC). Genotyping was performed using the custom-designed 533,631 SNP Illumina OncoArray with imputation to the 1,000 Genomes Phase 3 v5 reference set in 755 EOC cases, including 537 high-grade serous (HGSOC), and 1,235 controls. All subjects are of African ancestry (AA). Logistic regression was performed to estimate odds ratios (OR) and 95% confidence intervals (CI). We further evaluated statistical significance of selected SNPs using the Bayesian False Discovery Probability (BFDP). A significant association with EOC was identified in the UGT2A1/2 region for the SNP rs10017134 (per allele OR = 1.4, 95% CI = 1.2-1.7, P = 1.2 × 10-6 , BFDP = 0.02); and an association with HGSOC was identified in the EGFR region for the SNP rs114972508 (per allele OR = 2.3, 95% CI = 1.6-3.4, P = 1.6 × 10-5 , BFDP = 0.29) and in the UGT2A1/2 region again for rs1017134 (per allele OR = 1.4, 95% CI = 1.2-1.7, P = 2.3 × 10-5 , BFDP = 0.23). Genetic variants in the EGFR and UGT2A1/2 may increase susceptibility of EOC in AA women. Future studies to validate these findings are warranted. Alterations in EGFR and UGT2A1/2 could perturb enzyme efficacy, proliferation in ovaries, impact and mark susceptibility to EOC.

Genome-wide Analysis of Common Copy Number Variation and Epithelial Ovarian Cancer Risk

BACKGROUND

Germline DNA copy number variation (CNV) is a ubiquitous source of genetic variation and remains largely unexplored in association with epithelial ovarian cancer (EOC) risk.

METHODS

CNV was quantified in the DNA of approximately 3,500 cases and controls genotyped with the Illumina 610k and HumanOmni2.5M arrays. We performed a genome-wide association study of common (>1%) CNV regions (CNVRs) with EOC and high-grade serous (HGSOC) risk and, using The Cancer Genome Atlas (TCGA), performed in silico analyses of tumor-gene expression.

RESULTS

Three CNVRs were associated (P < 0.01) with EOC risk: two large (∼100 kb) regions within the 610k set and one small (<5 kb) region with the higher resolution 2.5M data. Large CNVRs included a duplication at LILRA6 (OR = 2.57; P = 0.001) and a deletion at CYP2A7 (OR = 1.90; P = 0.007) that were strongly associated with HGSOC risk (OR = 3.02; P = 8.98 × 10^-5). Somatic CYP2A7 alterations correlated with EGLN2 expression in tumors (P = 2.94 × 10^-47). An intronic ERBB4/HER4 deletion was associated with reduced EOC risk (OR = 0.33; P = 9.5 × 10^-2), and somatic deletions correlated with ERBB4 downregulation (P = 7.05 × 10^-5). Five CNVRs were associated with HGSOC, including two reduced-risk deletions: one at 1p36.33 (OR = 0.28; P = 0.001) that correlated with lower CDKIIA expression in TCGA tumors (P = 2.7 × 10^-7), and another at 8p21.2 (OR = 0.52; P = 0.002) that was present somatically where it correlated with lower GNRH1 expression (P = 5.9 × 10^-5).

CONCLUSIONS

Though CNV appears to not contribute largely to EOC susceptibility, a number of low-to-common frequency variants may influence the risk of EOC and tumor-gene expression.

IMPACT

Further research on CNV and EOC susceptibility is warranted, particularly with CNVs estimated from high-density arrays.

Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk

DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P < 7.94 × 10-7. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. SIGNIFICANCE: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.

Functional Analysis and Fine Mapping of the 9p22.2 Ovarian Cancer Susceptibility Locus

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.

Author Correction: Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci

In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.

Novel Common Genetic Susceptibility Loci for Colorectal Cancer

BACKGROUND

Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk.

METHODS

We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided.

RESULTS

The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0.

CONCLUSIONS

This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.

Technical challenges in generalizing calibration techniques for breast density measurements

PURPOSE

We are developing a calibration methodology for full-field digital mammography (FFDM). Calibration compensates for image acquisition technique influences on the pixel representation, ideally producing improved inter-image breast density estimates. This approach relies on establishing references with rigid breast tissue-equivalent phantoms (BTEs) and requires an accurate estimate of the compressed breast thickness because the system readout is nominal. There is also an attenuation mismatch between adipose breast tissue and the adipose BTE that was noted in our previous work. It is referred to as the "attenuation anomaly" and addressed in this report. The objectives are to evaluate methods to correct for the compressed breast thickness and compensate for the attenuation anomaly.

METHODS

Thickness correction surfaces were established with a deformable phantom (DP) using both image and physical measurements for three direct x-ray conversion FFDM units. The Cumulative Sum serial quality control procedure was established to ensure the thickness correction measurements were stable over time by imaging and calibrating DPs biweekly in lieu of physical measurements. The attenuation anomaly was addressed by evaluating adipose image regions coupled with an optimization technique to adjust the adipose calibration data. We compared calibration consistency across matched left and right cranial caudal (CC) mammographic views (n = 199) with and without corrections using Bland-Altman plots. These plots were complemented by comparing the right and left breast calibrated average (μ_a ) and population distribution mean (m_a ) with 95% confidence intervals and difference distribution variances with the F-test for uncorrected and corrected data.

RESULTS

Thickness correction surfaces were well approximated as tilted planes and were dependent upon compression force. A correction was developed for the attenuation anomaly. All paddles (large and small paddles for all units) exhibited similar tilt as a function of force. Without correction, m_a  = 0.92 (-1.77, 3.62) was not significantly different from zero with many negative μ_a samples. The thickness correction produced a significant shift in the μ_a distribution in the positive direction with m_a  = 13.99 (11.17, 16.80) and reduced the difference distribution variance significantly (P < 0.0001). Applying both corrections in tandem gave m_a  = 22.83 (20.32, 25.34), representing another significant positive shift in comparison with the thickness correction in isolation. Thickness corrections were stable over approximately a 2-year timeframe for all units.

CONCLUSION

These correction techniques are valid approaches for addressing technical problems with calibration that relies on reference phantoms. The efficacy of the calibration methodology will require validation with clinical endpoints in future studies.

Generalized breast density metrics

Mammograms represent data that can inform future risk of breast cancer. Data from two case-control study populations were analyzed. Population 1 included women (N  =  180 age matched case-control pairs) with mammograms acquired with one indirect x-ray conversion mammography unit. Population 2 included women (N  =  319 age matched case-control pairs) with mammograms acquired from 6 direct x-ray conversion units. The Fourier domain was decomposed into n concentric rings (radial spatial frequency bands). The power in each ring was summarized giving a set of measures. We investigated images in raw, for presentation (processed) and calibrated representations and made comparison with the percentage of breast density (BD) determined with the operator assisted Cumulus method. Breast cancer associations were evaluated with conditional logistic regression, adjusted for body mass index and ethnicity. Odds ratios (ORs), per standard deviation increase derived from the respective breast density distributions and 95% confidence intervals (CIs) were estimated. A measure from a lower radial frequency ring, corresponding 0.083-0.166 cycles mm^-1 and BD had significant associations with risk in both populations. In Population 1, the Fourier measure produced significant associations in each representation: OR  =  1.76 (1.33, 2.32) for raw; OR  =  1.43 (1.09, 1.87) for processed; and OR  =  1.68 (1.26, 2.25) for calibrated. BD also provided significant associations in Population 1: OR  =  1.72 (1.27, 2.33). In Population 2, the Fourier measure produced significant associations for each representation as well: OR  =  1.47 (1.19, 1.80) for raw; OR  =  1.38 (1.15, 1.67) for processed; and OR  =  1.42 (1.15, 1.75) for calibrated. BD provided significant associations in Population 2: OR  =  1.43 (1.17, 1.76). Other coincident spectral regions were also predictive of case-control status. In sum, generalized breast density measures were significantly associated with breast cancer in both FFDM technologies.

AA9int: SNP interaction pattern search using non-hierarchical additive model set

Motivation

The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions.

Results

We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies.

Availability and implementation

The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/.

Supplementary information

Supplementary data are available at Bioinformatics online.

When Is Enough, Enough? When Are More Observational Epidemiologic Studies Needed to Resolve a Research Question: Illustrations Using Biomarker-Cancer Associations

BACKGROUND

Research reproducibility is vital for translation of epidemiologic findings. However, repeated studies of the same question may be undertaken without enhancing existing knowledge. To identify settings in which additional research is or is not warranted, we adapted research synthesis metrics to determine number of additional observational studies needed to change the inference from an existing meta-analysis.

METHODS

The fail-safe number (FSN) estimates number of additional studies of average weight and null effect needed to drive a statistically significant meta-analysis to null (P ≥ 0.05). We used conditional power to determine number of additional studies of average weight and equivalent heterogeneity to achieve 80% power in an updated meta-analysis to detect the observed summary estimate as statistically significant. We applied these metrics to a curated set of 98 meta-analyses on biomarkers and cancer risk.

RESULTS

Both metrics were influenced by number of studies, heterogeneity, and summary estimate size in the existing meta-analysis. For the meta-analysis on Helicobacter pylori and gastric cancer with 15 studies [OR = 2.29; 95% confidence interval (CI), 1.71-3.05], FSN was 805 studies, supporting futility of further study. For the meta-analysis on dehydroepiandrosterone sulfate and prostate cancer with 7 studies (OR = 1.29; 95% CI, 0.99-1.69), 5 more studies would be needed for 80% power, suggesting further study could change inferences.

CONCLUSIONS

Along with traditional assessments, these metrics could be used by stakeholders to decide whether additional studies addressing the same question are needed.

IMPACT

Systematic application of these metrics could lead to more judicious use of resources and acceleration from discovery to population-health impact.

MAFG is a potential therapeutic target to restore chemosensitivity in cisplatin-resistant cancer cells by increasing reactive oxygen species

Adjuvant chemotherapy for solid tumors based on platinum-derived compounds such as cisplatin is the treatment of choice in most cases. Cisplatin triggers signaling pathways that lead to cell death, but it also induces changes in tumor cells that modify the therapeutic response, thereby leading to cisplatin resistance. We have recently reported that microRNA-7 is silenced by DNA methylation and is involved in the resistance to platinum in cancer cells through the action of the musculoaponeurotic fibrosarcoma oncogene family, protein G (MAFG). In the present study, we first confirm the miR-7 epigenetic regulation of MAFG in 44 normal- and/or tumor-paired samples in non-small-cell lung cancer (NSCLC). We also provide translational evidence of the role of MAFG and the clinical outcome in NSCLC by the interrogation of two extensive in silico databases of 2019 patients. Moreover, we propose that MAFG-mediated resistance could be conferred due to lower reactive oxygen species production after cisplatin exposure. We developed specifically selected aptamers against MAFG, with high sensitivity to detect the protein at a nuclear level probed by aptacytochemistry and histochemistry analyses. The inhibition of MAFG activity through the action of the specific aptamer apMAFG6F increased the levels of reactive oxygen species production and the sensitivity to cisplatin. We report first the specific nuclear identification of MAFG as a novel detection method for diagnosis in NSCLC, and then we report that MAFG modulates the redox response and confers cell protection against free radicals generated after platinum administration, thus also being a promising therapeutic target.

A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk

Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 × 10-6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10-7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 × 10-3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419-30. ©2018 AACR.

rs495139 in the TYMS-ENOSF1 Region and Risk of Ovarian Carcinoma of Mucinous Histology

Thymidylate synthase (TYMS) is a crucial enzyme for DNA synthesis. TYMS expression is regulated by its antisense mRNA, ENOSF1. Disrupted regulation may promote uncontrolled DNA synthesis and tumor growth. We sought to replicate our previously reported association between rs495139 in the TYMS-ENOSF1 3' gene region and increased risk of mucinous ovarian carcinoma (MOC) in an independent sample. Genotypes from 24,351 controls to 15,000 women with invasive OC, including 665 MOC, were available. We estimated per-allele odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression, and meta-analysis when combining these data with our previous report. The association between rs495139 and MOC was not significant in the independent sample (OR = 1.09; 95% CI = 0.97⁻1.22; p = 0.15; N = 665 cases). Meta-analysis suggested a weak association (OR = 1.13; 95% CI = 1.03⁻1.24; p = 0.01; N = 1019 cases). No significant association with risk of other OC histologic types was observed (p = 0.05 for tumor heterogeneity). In expression quantitative trait locus (eQTL) analysis, the rs495139 allele was positively associated with ENOSF1 mRNA expression in normal tissues of the gastrointestinal system, particularly esophageal mucosa (r = 0.51, p = 1.7 × 10-28), and nonsignificantly in five MOC tumors. The association results, along with inconclusive tumor eQTL findings, suggest that a true effect of rs495139 might be small.

Variants in genes encoding small GTPases and association with epithelial ovarian cancer susceptibility

Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality in American women. Normal ovarian physiology is intricately connected to small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran) which govern processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. We hypothesized that common germline variation in genes encoding small GTPases is associated with EOC risk. We investigated 322 variants in 88 small GTPase genes in germline DNA of 18,736 EOC patients and 26,138 controls of European ancestry using a custom genotype array and logistic regression fitting log-additive models. Functional annotation was used to identify biofeatures and expression quantitative trait loci that intersect with risk variants. One variant, ARHGEF10L (Rho guanine nucleotide exchange factor 10 like) rs2256787, was associated with increased endometrioid EOC risk (OR = 1.33, p = 4.46 x 10-6). Other variants of interest included another in ARHGEF10L, rs10788679, which was associated with invasive serous EOC risk (OR = 1.07, p = 0.00026) and two variants in AKAP6 (A-kinase anchoring protein 6) which were associated with risk of invasive EOC (rs1955513, OR = 0.90, p = 0.00033; rs927062, OR = 0.94, p = 0.00059). Functional annotation revealed that the two ARHGEF10L variants were located in super-enhancer regions and that AKAP6 rs927062 was associated with expression of GTPase gene ARHGAP5 (Rho GTPase activating protein 5). Inherited variants in ARHGEF10L and AKAP6, with potential transcriptional regulatory function and association with EOC risk, warrant investigation in independent EOC study populations.

Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

An epigenomic approach to identifying differential overlapping and cis-acting lncRNAs in cisplatin-resistant cancer cells

Long noncoding RNAs (lncRNAs) are critical regulators of cell biology whose alteration can lead to the development of diseases such as cancer. The potential role of lncRNAs and their epigenetic regulation in response to platinum treatment are largely unknown. We analyzed four paired cisplatin-sensitive/resistant non-small cell lung cancer and ovarian cancer cell lines. The epigenetic landscape of overlapping and cis-acting lncRNAs was determined by combining human microarray data on 30,586 lncRNAs and 20,109 protein coding mRNAs with whole-genome bisulfite sequencing. Selected candidate lncRNAs were further characterized by PCR, gene-ontology analysis, and targeted bisulfite sequencing. Differential expression in response to therapy was observed more frequently in cis-acting than in overlapping lncRNAs (78% vs. 22%, fold change ≥1.5), while significantly altered methylation profiles were more commonly associated with overlapping lncRNAs (29% vs. 8%; P value <0.001). Moreover, overlapping lncRNAs contain more CpG islands (CGIs) (25% vs. 17%) and the majority of CGI-containing overlapping lncRNAs share these CGIs with their associated coding genes (84%). The differences in expression between sensitive and resistant cell lines were replicated in 87% of the selected candidates (P<0.05), while our bioinformatics approach identifying differential methylation was confirmed in all of the selected lncRNAs (100%). Five lncRNAs under epigenetic regulation appear to be involved in cisplatin resistance (AC091814.2, AC141928.1, RP11-65J3.1-002, BX641110, and AF198444). These novel findings provide new insights into epigenetic mechanisms and acquired resistance to cisplatin that highlight specific lncRNAs, some with unknown function, that may signal strategies in epigenetic therapies.

Common Genetic Variation and Susceptibility to Ovarian Cancer: Current Insights and Future Directions

In this review, we summarize current progress in the genetic epidemiology of epithelial ovarian cancer (EOC), focusing exclusively on elucidating the role of common germline genetic variation in conferring susceptibility to EOC. We provide an overview of the more than 30 EOC risk loci identified to date by genome-wide association studies (GWAS) and describe the contribution of large-scale, cross-cancer type, custom genotyping projects, such as the OncoArray and the Collaborative Oncological Gene-Environment Study, to locus discovery and replication. We discuss the histotype-specific nature of these EOC risk loci, pleiotropy, or overlapping genetic effects between EOC and other hormone-related cancer types, and the application of findings to polygenic risk prediction for EOC. The second part of the article offers a concise review of primarily laboratory-based studies that have led to the identification of several putative EOC susceptibility genes using common variants at the known EOC risk loci as starting points. More global biological insights emerging from network- and pathway-based analyses of GWAS for EOC susceptibility are also highlighted. Finally, we delve into potential future directions, including the need to identify EOC risk loci in non-European populations and the next generation of GWAS functional studies that are likely to involve genome editing to establish the cell type-specific carcinogenic effects of EOC risk variants Cancer Epidemiol Biomarkers Prev; 27(4); 395-404. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

Correlation between germline mutations in MMR genes and microsatellite instability in ovarian cancer specimens

A high proportion of ovarian cancers from women who carry germline mutations in mismatch repair (MMR) genes demonstrate microsatellite instability (MSI). The utility of pre-screening ovarian cancer specimens for MSI to identify potential patients for germline screening for MMR mutations is uncertain. 656 women with malignant ovarian cancer underwent both MSI testing and germline mutation testing for large rearrangements in three MMR genes, MLH1, MSH2 and MSH6. Germline DNA sequencing data for the same genes was available. Among the 656 women, only four (0.6%) carried a clearly pathogenic MMR mutation. All four cancers from patients with mutations had loss of two or more microsatellite markers (MSI-high). Eighty-four of 652 (13.0%) women without a mutation had MSI-high ovarian cancers. Using MSI-high as a prescreening criterion, the sensitivity of MSI testing to identify germline MMR gene mutations was 100% and the positive predictive value was 4.5%. Germline mutations in MLH1, MSH2 and MSH6 are rare among unselected cases of ovarian cancer. Patients with germline mutations often will have MSI-positive cancers and pre-screening of ovarian cancer specimens may be an efficient way of identifying patients with Lynch syndrome.

Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts

OBJECTIVES

To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.

DESIGN

Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.

SETTING

Multiple institutions that were members of international PRACTICAL consortium.

PARTICIPANTS

All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.

MAIN OUTCOME MEASURES

Prediction with hazard score of age of onset of aggressive cancer in validation set.

RESULTS

In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10-16). When men in the validation set with high scores (>98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.

CONCLUSIONS

Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.

Quantifying the Genetic Correlation between Multiple Cancer Types

Background: Many cancers share specific genetic risk factors, including both rare high-penetrance mutations and common SNPs identified through genome-wide association studies (GWAS). However, little is known about the overall shared heritability across cancers. Quantifying the extent to which two distinct cancers share genetic origin will give insights to shared biological mechanisms underlying cancer and inform design for future genetic association studies.Methods: In this study, we estimated the pair-wise genetic correlation between six cancer types (breast, colorectal, lung, ovarian, pancreatic, and prostate) using cancer-specific GWAS summary statistics data based on 66,958 case and 70,665 control subjects of European ancestry. We also estimated genetic correlations between cancers and 14 noncancer diseases and traits.Results: After adjusting for 15 pair-wise genetic correlation tests between cancers, we found significant (P < 0.003) genetic correlations between pancreatic and colorectal cancer (rg = 0.55, P = 0.003), lung and colorectal cancer (rg = 0.31, P = 0.001). We also found suggestive genetic correlations between lung and breast cancer (rg = 0.27, P = 0.009), and colorectal and breast cancer (rg = 0.22, P = 0.01). In contrast, we found no evidence that prostate cancer shared an appreciable proportion of heritability with other cancers. After adjusting for 84 tests studying genetic correlations between cancer types and other traits (Bonferroni-corrected P value: 0.0006), only the genetic correlation between lung cancer and smoking remained significant (rg = 0.41, P = 1.03 × 10-6). We also observed nominally significant genetic correlations between body mass index and all cancers except ovarian cancer.Conclusions: Our results highlight novel genetic correlations and lend support to previous observational studies that have observed links between cancers and risk factors.Impact: This study demonstrates modest genetic correlations between cancers; in particular, breast, colorectal, and lung cancer share some degree of genetic basis. Cancer Epidemiol Biomarkers Prev; 26(9); 1427-35. ©2017 AACR.