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 ß-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.

Racial and ethnic differences in epithelial ovarian cancer risk: an analysis from the Ovarian Cancer Association Consortium.

BACKGROUND: Limited estimates exist on risk factors for epithelial ovarian cancer (EOC) in Asian, Hispanic, and Native Hawaiian/Pacific Islander (NHPI) women. METHODS: Participants included 1734 Asian (785 cases, 949 controls), 266 NHPI (99 cases, 167 controls), 1149 Hispanic (505 cases, 644 controls), and 24,189 White (9,981 cases, 14,208 controls) women from 11 studies in the Ovarian Cancer Association Consortium. Logistic regression models estimated odds ratios (ORs) and 95% confidence intervals (CIs) for risk associations by race and ethnicity. RESULTS: Heterogeneity in EOC risk associations by race and ethnicity (p ≤ 0.02) was observed for oral contraceptive (OC) use, parity, tubal ligation and smoking. We observed inverse associations with EOC risk for OC use and parity across all groups; associations were strongest in NHPI and Asian women. The inverse association for tubal ligation with risk was most pronounced for NHPI participants (OR=0.25, 95% CI 0.13-0.48), versus Asian and White participants, respectively (OR=0.68, 95% CI 0.51-0.90; OR=0.78, 95% CI 0.73-0.85). CONCLUSIONS: Differences in EOC risk factor associations were observed across racial and ethnic groups, which could in part be due to varying prevalence of EOC histotypes. Inclusion of greater diversity in future studies is essential to inform prevention strategies.

Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors.

BACKGROUND: Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources. METHODS: We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations. RESULTS: In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis. CONCLUSIONS: Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.

Gene-based mediation analysis in epigenetic studies.

Mediation analysis has been a useful tool for investigating the effect of mediators that lie in the path from the independent variable to the outcome. With the increasing dimensionality of mediators such as in (epi)genomics studies, high-dimensional mediation model is needed. In this work, we focus on epigenetic studies with the goal to identify important DNA methylations that act as mediators between an exposure disease outcome. Specifically, we focus on gene-based high-dimensional mediation analysis implemented with kernel principal component analysis to capture potential nonlinear mediation effect. We first review the current high-dimensional mediation models and then propose two gene-based analytical approaches: gene-based high-dimensional mediation analysis based on linearity assumption between mediators and outcome (gHMA-L) and gene-based high-dimensional mediation analysis based on nonlinearity assumption (gHMA-NL). Since the underlying true mediation relationship is unknown in practice, we further propose an omnibus test of gene-based high-dimensional mediation analysis (gHMA-O) by combing gHMA-L and gHMA-NL. Extensive simulation studies show that gHMA-L performs better under the model linear assumption and gHMA-NL does better under the model nonlinear assumption, while gHMA-O is a more powerful and robust method by combining the two. We apply the proposed methods to two datasets to investigate genes whose methylation levels act as important mediators in the relationship: (1) between alcohol consumption and epithelial ovarian cancer risk using data from the Mayo Clinic Ovarian Cancer Case-Control Study and (2) between childhood maltreatment and comorbid post-traumatic stress disorder and depression in adulthood using data from the Gray Trauma Project.

Lifestyle and personal factors associated with having macroscopic residual disease after ovarian cancer primary cytoreductive surgery.

OBJECTIVE: The presence of macroscopic residual disease after primary cytoreductive surgery (PCS) is an important factor influencing survival for patients with high-grade serous ovarian cancer (HGSC). More research is needed to identify factors associated with having macroscopic residual disease. We analyzed 12 lifestyle and personal exposures known to be related to ovarian cancer risk or inflammation to identify those associated with having residual disease after surgery. METHODS: This analysis used data on 2054 patients with advanced stage HGSC from the Ovarian Cancer Association Consortium. The exposures were body mass index, breastfeeding, oral contraceptive use, depot-medroxyprogesterone acetate use, endometriosis, first-degree family history of ovarian cancer, incomplete pregnancy, menopausal hormone therapy use, menopausal status, parity, smoking, and tubal ligation. Logistic regression models were fit to assess the association between these exposures and having residual disease following PCS. RESULTS: Menopausal estrogen-only therapy (ET) use was associated with 33% lower odds of having macroscopic residual disease compared to never use (OR = 0.67, 95%CI 0.46-0.97, p = 0.033). Compared to nulliparous women, parous women who did not breastfeed had 36% lower odds of having residual disease (OR = 0.64, 95%CI 0.43-0.94, p = 0.022), while there was no association among parous women who breastfed (OR = 0.90, 95%CI 0.65-1.25, p = 0.53). CONCLUSIONS: The association between ET and having no macroscopic residual disease is plausible given a strong underlying biologic hypothesis between this exposure and diagnosis with HGSC. If this or the parity finding is replicated, these factors could be included in risk stratification models to determine whether HGSC patients should receive PCS or neoadjuvant chemotherapy.

The proteome of clear cell ovarian carcinoma.

Clear cell ovarian carcinoma (CCOC) is the second most common subtype of epithelial ovarian carcinoma. Late-stage CCOC is not responsive to gold-standard chemotherapy and results in suboptimal outcomes for patients. In-depth molecular insight is urgently needed to stratify the disease and drive therapeutic development. We conducted global proteomics for 192 cases of CCOC and compared these with other epithelial ovarian carcinoma subtypes. Our results showed distinct proteomic differences in CCOC compared with other epithelial ovarian cancer subtypes including alterations in lipid and purine metabolism pathways. Furthermore, we report potential clinically significant proteomic subgroups within CCOC, suggesting the biologic plausibility of stratified treatment for this cancer. Taken together, our results provide a comprehensive understanding of the CCOC proteomic landscape to facilitate future understanding and research of this disease. © 2022 The Pathological Society of Great Britain and Ireland.

Clinical parameters affecting survival outcomes in patients with low-grade serous ovarian carcinoma: an international multicentre analysis.

BACKGROUND: Women with low-grade ovarian serous carcinoma (LGSC) benefit from surgical treatment; however, the role of chemotherapy is controversial. We examined an international database through the Ovarian Cancer Association Consortium to identify factors that affect survival in LGSC. METHODS: We performed a retrospective cohort analysis of patients with LGSC who had had primary surgery and had overall survival data available. We performed univariate and multivariate analyses of progression-free survival and overall survival, and generated Kaplan-Meier survival curves. RESULTS: Of the 707 patients with LGSC, 680 (96.2%) had available overall survival data. The patients' median age overall was 54 years. Of the 659 patients with International Federation of Obstetrics and Gynecology stage data, 156 (23.7%) had stage I disease, 64 (9.7%) had stage II, 395 (59.9%) had stage III, and 44 (6.7%) had stage IV. Of the 377 patients with surgical data, 200 (53.0%) had no visible residual disease. Of the 361 patients with chemotherapy data, 330 (91.4%) received first-line platinum-based chemotherapy. The median follow-up duration was 5.0 years. The median progression-free survival and overall survival were 43.2 months and 110.4 months, respectively. Multivariate analysis indicated a statistically significant impact of stage and residual disease on progression-free survival and overall survival. Platinum-based chemotherapy was not associated with a survival advantage. CONCLUSION: This multicentre analysis indicates that complete surgical cytoreduction to no visible residual disease has the most impact on improved survival in LGSC. This finding could immediately inform and change practice.

Germline BRCA variants, lifestyle and ovarian cancer survival.

OBJECTIVE: Women with ovarian cancer who have a pathogenic germline variant in BRCA1 or BRCA2 (BRCA) have been shown to have better 5-year survival after diagnosis than women who are BRCA-wildtype (non-carriers). Modifiable lifestyle factors, including smoking, physical activity and body mass index (BMI) have previously been associated with ovarian cancer survival; however, it is unknown whether these associations differ by germline BRCA status. METHODS: We investigated measures of lifestyle prior to diagnosis in two cohorts of Australian women with invasive epithelial ovarian cancer, using Cox proportional hazards regression to calculate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: In the combined studies (n = 1923), there was little association between physical activity, BMI or alcohol intake and survival, and no difference by BRCA status. However, the association between current smoking status before diagnosis and poorer survival was stronger for BRCA variant carriers (HR 1.98; 95% CI 1.20-3.27) than non-carriers (HR 1.18; 95% CI 0.96-1.46; p-interaction 0.02). We saw a similar differential association with smoking when we pooled results from two additional cohorts from the USA and UK (n = 2120). Combining the results from all four studies gave a pooled-HR of 1.94 (95% CI 1.28-2.94) for current smoking among BRCA variant carriers compared to 1.08 (0.90-1.29) for non-carriers. CONCLUSIONS: Our results suggest that the adverse effect of smoking on survival may be stronger for women with a BRCA variant than those without. Thus, while smoking cessation may improve outcomes for all women with ovarian cancer, it might provide a greater benefit for BRCA variant carriers.

Into the future: A pilot study combining imaging with molecular profiling to predict resectability in ovarian cancer.

OBJECTIVE: We sought to determine the predictive value of combining tumor molecular subtype and computerized tomography (CT) imaging for surgical outcomes after primary cytoreductive surgery in advanced stage high-grade serous ovarian cancer (HGSOC) patients. METHODS: We identified 129 HGSOC patients who underwent pre-operative CT imaging and post-operative tumor mRNA profiling. A continuous CT-score indicative of overall disease burden was defined based on six imaging measurements of anatomic involvement. Molecular subtypes were derived from mRNA profiling of chemo-naïve tumors and classified as mesenchymal (MES) subtype (36%) or non-MES subtype (64%). Fischer exact tests and multivariate logistic regression examined residual disease and surgical complexity. RESULTS: Women with higher CT-scores were more likely to have MES subtype tumors (p = 0.014). MES subtypes and a high CT-score were independently predictive of macroscopic disease and high surgical complexity. In multivariate models adjusting for age, stage and American Society of Anesthesiologists (ASA) score, patients with a MES subtype and high CT-score had significantly elevated risk of macroscopic disease (OR = 26.7, 95% CI = [6.42, 187]) and were more likely to undergo high complexity surgery (OR = 9.53, 95% CI = [2.76, 40.6], compared to patients with non-MES tumor and low CT-score. CONCLUSION: Preoperative CT imaging combined with tumor molecular subtyping can identify a subset of women unlikely to have resectable disease and likely to require high complexity surgery. Along with other clinical factors, these may refine predictive scores for resection and assist treatment planning. Investigating methods for pre-surgical molecular subtyping is an important next step.

Mendelian randomization analyses suggest a role for cholesterol in the development of endometrial cancer.

Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two-sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low-density lipoprotein [LDL] and high-density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels (P < 5 × 10-8 ) were identified as instrumental variables, and assessed using genome-wide association study data from the Endometrial Cancer Association Consortium (12 906 cases and 108 979 controls) and the Global Lipids Genetic Consortium (n = 188 578). Mendelian randomization analyses found genetically raised LDL cholesterol levels to be associated with lower risks of endometrial cancer of all histologies combined, and of endometrioid and non-endometrioid subtypes. Conversely, higher genetically predicted HDL cholesterol levels were associated with increased risk of non-endometrioid endometrial cancer. After accounting for the potential confounding role of obesity (as measured by genetic variants associated with body mass index), the association between genetically predicted increased LDL cholesterol levels and lower endometrial cancer risk remained significant, especially for non-endometrioid endometrial cancer. There was no evidence to support a role for triglycerides in endometrial cancer development. Our study supports a role for LDL and HDL cholesterol in the development of non-endometrioid endometrial cancer. Further studies are required to understand the mechanisms underlying these findings.

Molecular signatures of X chromosome inactivation and associations with clinical outcomes in epithelial ovarian cancer.

X chromosome inactivation (XCI) is a key epigenetic gene expression regulatory process, which may play a role in women's cancer. In particular tissues, some genes are known to escape XCI, yet patterns of XCI in ovarian cancer (OC) and their clinical associations are largely unknown. To examine XCI in OC, we integrated germline genotype with tumor copy number, gene expression and DNA methylation information from 99 OC patients. Approximately 10% of genes showed different XCI status (either escaping or being subject to XCI) compared with the studies of other tissues. Many of these genes are known oncogenes or tumor suppressors (e.g. DDX3X, TRAPPC2 and TCEANC). We also observed strong association between cis promoter DNA methylation and allele-specific expression imbalance (P = 2.0 × 10-10). Cluster analyses of the integrated data identified two molecular subgroups of OC patients representing those with regulated (N = 47) and dysregulated (N = 52) XCI. This XCI cluster membership was associated with expression of X inactive specific transcript (P = 0.002), a known driver of XCI, as well as age, grade, stage, tumor histology and extent of residual disease following surgical debulking. Patients with dysregulated XCI (N = 52) had shorter time to recurrence (HR = 2.34, P = 0.001) and overall survival time (HR = 1.87, P = 0.02) than those with regulated XCI, although results were attenuated after covariate adjustment. Similar findings were observed when restricted to high-grade serous tumors. We found evidence of a unique OC XCI profile, suggesting that XCI may play an important role in OC biology. Additional studies to examine somatic changes with paired tumor-normal tissue are needed.

Refined cut-off for TP53 immunohistochemistry improves prediction of TP53 mutation status in ovarian mucinous tumors: implications for outcome analyses.

TP53 mutations are implicated in the progression of mucinous borderline tumors (MBOT) to mucinous ovarian carcinomas (MOC). Optimized immunohistochemistry (IHC) for TP53 has been established as a proxy for the TP53 mutation status in other ovarian tumor types. We aimed to confirm the ability of TP53 IHC to predict TP53 mutation status in ovarian mucinous tumors and to evaluate the association of TP53 mutation status with survival among patients with MBOT and MOC. Tumor tissue from an initial cohort of 113 women with MBOT/MOC was stained with optimized IHC for TP53 using tissue microarrays (75.2%) or full sections (24.8%) and interpreted using established criteria as normal or abnormal (overexpression, complete absence, or cytoplasmic). Cases were considered concordant if abnormal IHC staining predicted deleterious TP53 mutations. Discordant tissue microarray cases were re-evaluated on full sections and interpretational criteria were refined. The initial cohort was expanded to a total of 165 MBOT and 424 MOC for the examination of the association of survival with TP53 mutation status, assessed either by TP53 IHC and/or sequencing. Initially, 82/113 (72.6%) cases were concordant using the established criteria. Refined criteria for overexpression to account for intratumoral heterogeneity and terminal differentiation improved concordance to 93.8% (106/113). In the expanded cohort, 19.4% (32/165) of MBOT showed evidence for TP53 mutation and this was associated with a higher risk of recurrence, disease-specific death, and all-cause mortality (overall survival: HR = 4.6, 95% CI 1.5-14.3, p = 0.0087). Within MOC, 61.1% (259/424) harbored a TP53 mutation, but this was not associated with survival (overall survival, p = 0.77). TP53 IHC is an accurate proxy for TP53 mutation status with refined interpretation criteria accounting for intratumoral heterogeneity and terminal differentiation in ovarian mucinous tumors. TP53 mutation status is an important biomarker to identify MBOT with a higher risk of mortality.

Generating real-world evidence from unstructured clinical notes to examine clinical utility of genetic tests: use case in BRCAness.

BACKGROUND: Next-generation sequencing provides comprehensive information about individuals' genetic makeup and is commonplace in oncology clinical practice. However, the utility of genetic information in the clinical decision-making process has not been examined extensively from a real-world, data-driven perspective. Through mining real-world data (RWD) from clinical notes, we could extract patients' genetic information and further associate treatment decisions with genetic information. METHODS: We proposed a real-world evidence (RWE) study framework that incorporates context-based natural language processing (NLP) methods and data quality examination before final association analysis. The framework was demonstrated in a Foundation-tested women cancer cohort (N = 196). Upon retrieval of patients' genetic information using NLP system, we assessed the completeness of genetic data captured in unstructured clinical notes according to a genetic data-model. We examined the distribution of different topics regarding BRCA1/2 throughout patients' treatment process, and then analyzed the association between BRCA1/2 mutation status and the discussion/prescription of targeted therapy. RESULTS: We identified seven topics in the clinical context of genetic mentions including: Information, Evaluation, Insurance, Order, Negative, Positive, and Variants of unknown significance. Our rule-based system achieved a precision of 0.87, recall of 0.93 and F-measure of 0.91. Our machine learning system achieved a precision of 0.901, recall of 0.899 and F-measure of 0.9 for four-topic classification and a precision of 0.833, recall of 0.823 and F-measure of 0.82 for seven-topic classification. We found in result-containing sentences, the capture of BRCA1/2 mutation information was 75%, but detailed variant information (e.g. variant types) is largely missing. Using cleaned RWD, significant associations were found between BRCA1/2 positive mutation and targeted therapies. CONCLUSIONS: In conclusion, we demonstrated a framework to generate RWE using RWD from different clinical sources. Rule-based NLP system achieved the best performance for resolving contextual variability when extracting RWD from unstructured clinical notes. Data quality issues such as incompleteness and discrepancies exist thus manual data cleaning is needed before further analysis can be performed. Finally, we were able to use cleaned RWD to evaluate the real-world utility of genetic information to initiate a prescription of targeted therapy.

Menopausal hormone therapy prior to the diagnosis of ovarian cancer is associated with improved survival.

PURPOSE: Prior studies of menopausal hormone therapy (MHT) and ovarian cancer survival have been limited by lack of hormone regimen detail and insufficient sample sizes. To address these limitations, a comprehensive analysis of 6419 post-menopausal women with pathologically confirmed ovarian carcinoma was conducted to examine the association between MHT use prior to diagnosis and survival. METHODS: Data from 15 studies in the Ovarian Cancer Association Consortium were included. MHT use was examined by type (estrogen-only (ET) or estrogen+progestin (EPT)), duration, and recency of use relative to diagnosis. Cox proportional hazards models were used to estimate the association between hormone therapy use and survival. Logistic regression and mediation analysis was used to explore the relationship between MHT use and residual disease following debulking surgery. RESULTS: Use of ET or EPT for at least five years prior to diagnosis was associated with better ovarian cancer survival (hazard ratio, 0.80; 95% CI, 0.74 to 0.87). Among women with advanced stage, high-grade serous carcinoma, those who used MHT were less likely to have any macroscopic residual disease at the time of primary debulking surgery (p for trend <0.01 for duration of MHT use). Residual disease mediated some (17%) of the relationship between MHT and survival. CONCLUSIONS: Pre-diagnosis MHT use for 5+ years was a favorable prognostic factor for women with ovarian cancer. This large study is consistent with prior smaller studies, and further work is needed to understand the underlying mechanism.

Epigenetics in ovarian cancer.

Ovarian cancer is a disease with a poor prognosis and little progress has been made to improve treatment. It is now recognized that there are several histotypes of ovarian cancer, each with distinct epidemiologic and genomic characteristics. Cancer therapy is moving beyond classical chemotherapy to include epigenetic approaches. Epigenetics is the dynamic regulation of gene expression by DNA methylation and histone post translational modification in response to environmental cues. Improvement in technology to study DNA methylation has enabled a more agnostic approach and, with larger samples sets, has begun to unravel how epigenetics contributes to the etiology, response to chemotherapy and prognosis in of ovarian cancer. Investigations into histone modifications in ovarian cancer are more nascent. Much more is needed to be done to fully realize the potential that epigenetics holds for ovarian cancer clinical care.

A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants.

As a follow-up to genome-wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well-known ovarian cancer risk factors and their interactions with 28 genome-wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case-control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10-4 ). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46-0.60) compared to 0.71 (95%CI = 0.66-0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1-5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene-environment analysis in ovarian cancer.

A Common Variant at the 14q32 Endometrial Cancer Risk Locus Activates AKT1 through YY1 Binding.

A recent meta-analysis of multiple genome-wide association and follow-up endometrial cancer case-control datasets identified a novel genetic risk locus for this disease at chromosome 14q32.33. To prioritize the functional SNP(s) and target gene(s) at this locus, we employed an in silico fine-mapping approach using genotyped and imputed SNP data for 6,608 endometrial cancer cases and 37,925 controls of European ancestry. Association and functional analyses provide evidence that the best candidate causal SNP is rs2494737. Multiple experimental analyses show that SNP rs2494737 maps to a silencer element located within AKT1, a member of the PI3K/AKT/MTOR intracellular signaling pathway activated in endometrial tumors. The rs2494737 risk A allele creates a YY1 transcription factor-binding site and abrogates the silencer activity in luciferase assays, an effect mimicked by transfection of YY1 siRNA. Our findings suggest YY1 is a positive regulator of AKT1, mediating the stimulatory effects of rs2494737 increasing endometrial cancer risk. Identification of an endometrial cancer risk allele within a member of the PI3K/AKT signaling pathway, more commonly activated in tumors by somatic alterations, raises the possibility that well tolerated inhibitors targeting this pathway could be candidates for evaluation as chemopreventive agents in individuals at high risk of developing endometrial cancer.

Joint exposure to smoking, excessive weight, and physical inactivity and survival of ovarian cancer patients, evidence from the Ovarian Cancer Association Consortium.

PURPOSE: Previous epidemiologic studies have shown that smoking, obesity, and physical inactivity are associated with poor survival following a diagnosis of ovarian cancer. Yet, the combined relationship of these unfavorable lifestyle factors on ovarian cancer survival has not been sufficiently investigated. METHODS: Using data pooled from 13 studies, we examined the associations between combined exposures to smoking, overweight/obesity weight, and physical inactivity and overall survival (OS) as well as progression-free survival (PFS) among women diagnosed with invasive epithelial ovarian carcinoma (n = 7,022). Using age- and stage-adjusted Cox proportional hazards regression models, we estimated hazard ratios (HRs) and 95% confidence intervals (CIs) associated with joint exposure to these factors. RESULTS: Combined exposure to current smoking, overweight/obesity, and physical inactivity prior to diagnosis was associated with a significantly increased risk of mortality compared to women who never smoked, had normal body mass index (BMI), and were physically active (HR = 1.37; 95% CI 1.10-1.70). The association for a joint exposure to these factors exceeded that of each exposure individually. In fact, exposure to both current smoking and overweight/obesity, and current smoking and physical inactivity was also associated with increased risk of death (HR = 1.28; 95% CI 1.08-1.52, and HR = 1.26; 95% CI 1.04-1.54, respectively). The associations were of a similar magnitude when former smoking was assessed in combination with the other exposures and when excessive weight was limited to obesity only. No significant associations were observed between joint exposure to any of these factors and PFS. CONCLUSIONS: Joint exposure to smoking, excessive weight, and physical inactivity may negatively impact survival of ovarian cancer patients. These results suggest the importance of examining the combined effect of lifestyle factors on ovarian cancer patients' survival.

A combination of the immunohistochemical markers CK7 and SATB2 is highly sensitive and specific for distinguishing primary ovarian mucinous tumors from colorectal and appendiceal metastases.

Primary ovarian mucinous tumors can be difficult to distinguish from metastatic gastrointestinal neoplasms by histology alone. The expected immunoprofile of a suspected metastatic lower gastrointestinal tumor is CK7-/CK20+/CDX2+/PAX8-. This study assesses the addition of a novel marker SATB2, to improve the diagnostic algorithm. A test cohort included 155 ovarian mucinous tumors (105 carcinomas and 50 borderline tumors) and 230 primary lower gastrointestinal neoplasms (123 colorectal adenocarcinomas and 107 appendiceal neoplasms). All cases were assessed for SATB2, PAX8 CK7, CK20, and CDX2 expression on tissue microarrays. Expression was scored in a 3-tier system as absent, focal (1-50% of tumor cells) and diffuse ( >50% of tumor cells) and then categorized into either absent/present or nondiffuse/diffuse. SATB2 and PAX8 expression was further evaluated in ovarian tumors from an international cohort of 2876 patients (expansion cohort, including 159 mucinous carcinomas and 46 borderline mucinous tumors). The highest accuracy of an individual marker in distinguishing lower gastrointestinal from ovarian mucinous tumors was CK7 (91.7%, nondiffuse/diffuse cut-off) followed by SATB2 (88.8%, present/absent cut-off). The most effective combination was CK7 and SATB2 with accuracy of 95.3% using the 3-tier interpretation, absent/focal/diffuse. This combination outperformed the standard clinical set of CK7, CK20 and CDX2 (87.5%). Re-evaluation of outlier cases confirmed ovarian origin for all but one case. The accuracy of SATB2 was confirmed in the expansion cohort (91.5%). SATB2 expression was also detected in 15% of ovarian endometrioid carcinoma but less than 5% of other ovarian histotypes. A simple two marker combination of CK7 and SATB2 can distinguish lower gastrointestinal from ovarian primary mucinous tumors with greater than 95% accuracy. PAX8 and CDX2 have value as second-line markers. The utility of CK20 in this setting is low and this warrants replacement of this marker with SATB2 in clinical practice.

Genes associated with bowel metastases in ovarian cancer.

OBJECTIVE: This study is designed to identify genes and pathways that could promote metastasis to the bowel in high-grade serous ovarian cancer (OC) and evaluate their associations with clinical outcomes. METHODS: We performed RNA sequencing of OC primary tumors (PTs) and their corresponding bowel metastases (n = 21 discovery set; n = 18 replication set). Differentially expressed genes (DEGs) were those expressed at least 2-fold higher in bowel metastases (BMets) than PTs in at least 30% of patients (P < .05) with no increased expression in paired benign bowel tissue and were validated with quantitative reverse transcription PCR. Using an independent OC cohort (n = 333), associations between DEGs in PTs and surgical and clinical outcomes were performed. Immunohistochemistry and mouse xenograft studies were performed to confirm the role of LRRC15 in promoting metastasis. RESULTS: Among 27 DEGs in the discovery set, 21 were confirmed in the replication set: SFRP2, Col11A1, LRRC15, ADAM12, ADAMTS12, MFAP5, LUM, PLPP4, FAP, POSTN, GRP, MMP11, MMP13, C1QTNF3, EPYC, DIO2, KCNA1, NETO1, NTM, MYH13, and PVALB. Higher expression of more than half of the genes in the PT was associated with an increased requirement for bowel resection at primary surgery and an inability to achieve complete cytoreduction. Increased expression of LRRC15 in BMets was confirmed by immunohistochemistry and knockdown of LRRC15 significantly inhibited tumor progression in mice. CONCLUSIONS: We identified 21 genes that are overexpressed in bowel metastases among patients with OC. Our findings will help select potential molecular targets for the prevention and treatment of malignant bowel obstruction in OC.