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.

Cis- and trans-eQTL TWASs of breast and ovarian cancer identify more than 100 susceptibility genes in the BCAC and OCAC consortia.

Transcriptome-wide association studies (TWASs) have investigated the role of genetically regulated transcriptional activity in the etiologies of breast and ovarian cancer. However, methods performed to date have focused on the regulatory effects of risk-associated SNPs thought to act in cis on a nearby target gene. With growing evidence for distal (trans) regulatory effects of variants on gene expression, we performed TWASs of breast and ovarian cancer using a Bayesian genome-wide TWAS method (BGW-TWAS) that considers effects of both cis- and trans-expression quantitative trait loci (eQTLs). We applied BGW-TWAS to whole-genome and RNA sequencing data in breast and ovarian tissues from the Genotype-Tissue Expression project to train expression imputation models. We applied these models to large-scale GWAS summary statistic data from the Breast Cancer and Ovarian Cancer Association Consortia to identify genes associated with risk of overall breast cancer, non-mucinous epithelial ovarian cancer, and 10 cancer subtypes. We identified 101 genes significantly associated with risk with breast cancer phenotypes and 8 with ovarian phenotypes. These loci include established risk genes and several novel candidate risk loci, such as ACAP3, whose associations are predominantly driven by trans-eQTLs. We replicated several associations using summary statistics from an independent GWAS of these cancer phenotypes. We further used genotype and expression data in normal and tumor breast tissue from the Cancer Genome Atlas to examine the performance of our trained expression imputation models. This work represents an in-depth look into the role of trans eQTLs in the complex molecular mechanisms underlying these diseases.

Molecular subtypes of high-grade serous ovarian cancer across racial groups and gene expression platforms.

BACKGROUND: High-grade serous carcinoma (HGSC) gene expression subtypes are associated with differential survival. We characterized HGSC gene expression in Black individuals and considered whether gene expression differences by self-identified race may contribute to poorer HGSC survival among Black versus White individuals. METHODS: We included newly generated RNA-Seq data from Black and White individuals, and array-based genotyping data from four existing studies of White and Japanese individuals. We used K-means clustering, a method with no predefined number of clusters or dataset-specific features, to assign subtypes. Cluster- and dataset-specific gene expression patterns were summarized by moderated t-scores. We compared cluster-specific gene expression patterns across datasets by calculating the correlation between the summarized vectors of moderated t-scores. Following mapping to The Cancer Genome Atlas (TCGA)-derived HGSC subtypes, we used Cox proportional hazards models to estimate subtype-specific survival by dataset. RESULTS: Cluster-specific gene expression was similar across gene expression platforms and racial groups. Comparing the Black population to the White and Japanese populations, the immunoreactive subtype was more common (39% versus 23%-28%) and the differentiated subtype less common (7% versus 22%-31%). Patterns of subtype-specific survival were similar between the Black and White populations with RNA-Seq data; compared to mesenchymal cases, the risk of death was similar for proliferative and differentiated cases and suggestively lower for immunoreactive cases (Black population HR=0.79 [0.55, 1.13], White population HR=0.86 [0.62, 1.19]). CONCLUSIONS: While the prevalence of HGSC subtypes varied by race, subtype-specific survival was similar. IMPACT: HGSC subtypes can be consistently assigned across platforms and self-identified racial groups.

Genome-wide association analyses of ovarian cancer patients undergoing primary debulking surgery identify candidate genes for residual disease.

Survival from ovarian cancer depends on the resection status after primary surgery. We performed genome-wide association analyses for resection status of 7705 ovarian cancer patients, including 4954 with high-grade serous carcinoma (HGSOC), to identify variants associated with residual disease. The most significant association with resection status was observed for rs72845444, upstream of MGMT, in HGSOC (p = 3.9 × 10-8). In gene-based analyses, PPP2R5C was the most strongly associated gene in HGSOC after stage adjustment. In an independent set of 378 ovarian tumours from the AGO-OVAR 11 study, variants near MGMT and PPP2R5C correlated with methylation and transcript levels, and PPP2R5C mRNA levels predicted progression-free survival in patients with residual disease. MGMT encodes a DNA repair enzyme, and PPP2R5C encodes the B56γ subunit of the PP2A tumour suppressor. Our results link heritable variation at these two loci with resection status in HGSOC.

Molecular subtypes of high-grade serous ovarian cancer across racial groups and gene expression platforms.

Introduction: High-grade serous carcinoma (HGSC) gene expression subtypes are associated with differential survival. We characterized HGSC gene expression in Black individuals and considered whether gene expression differences by race may contribute to poorer HGSC survival among Black versus non-Hispanic White individuals. Methods: We included newly generated RNA-Seq data from Black and White individuals, and array-based genotyping data from four existing studies of White and Japanese individuals. We assigned subtypes using K-means clustering. Cluster- and dataset-specific gene expression patterns were summarized by moderated t-scores. We compared cluster-specific gene expression patterns across datasets by calculating the correlation between the summarized vectors of moderated t-scores. Following mapping to The Cancer Genome Atlas (TCGA)-derived HGSC subtypes, we used Cox proportional hazards models to estimate subtype-specific survival by dataset. Results: Cluster-specific gene expression was similar across gene expression platforms. Comparing the Black study population to the White and Japanese study populations, the immunoreactive subtype was more common (39% versus 23%-28%) and the differentiated subtype less common (7% versus 22%-31%). Patterns of subtype-specific survival were similar between the Black and White populations with RNA-Seq data; compared to mesenchymal cases, the risk of death was similar for proliferative and differentiated cases and suggestively lower for immunoreactive cases (Black population HR=0.79 [0.55, 1.13], White population HR=0.86 [0.62, 1.19]). Conclusions: A single, platform-agnostic pipeline can be used to assign HGSC gene expression subtypes. While the observed prevalence of HGSC subtypes varied by race, subtype-specific survival was similar.

Cis- and trans-eQTL TWAS of breast and ovarian cancer identify more than 100 risk associated genes in the BCAC and OCAC consortia.

Transcriptome-wide association studies (TWAS) have investigated the role of genetically regulated transcriptional activity in the etiologies of breast and ovarian cancer. However, methods performed to date have only considered regulatory effects of risk associated SNPs thought to act in cis on a nearby target gene. With growing evidence for distal (trans) regulatory effects of variants on gene expression, we performed TWAS of breast and ovarian cancer using a Bayesian genome-wide TWAS method (BGW-TWAS) that considers effects of both cis- and trans-expression quantitative trait loci (eQTLs). We applied BGW-TWAS to whole genome and RNA sequencing data in breast and ovarian tissues from the Genotype-Tissue Expression project to train expression imputation models. We applied these models to large-scale GWAS summary statistic data from the Breast Cancer and Ovarian Cancer Association Consortia to identify genes associated with risk of overall breast cancer, non-mucinous epithelial ovarian cancer, and 10 cancer subtypes. We identified 101 genes significantly associated with risk with breast cancer phenotypes and 8 with ovarian phenotypes. These loci include established risk genes and several novel candidate risk loci, such as ACAP3, whose associations are predominantly driven by trans-eQTLs. We replicated several associations using summary statistics from an independent GWAS of these cancer phenotypes. We further used genotype and expression data in normal and tumor breast tissue from the Cancer Genome Atlas to examine the performance of our trained expression imputation models. This work represents a first look into the role of trans-eQTLs in the complex molecular mechanisms underlying these diseases.

The tumor multi-omic landscape of endometrial cancers developed on a germline genetic background of adiposity.

High body mass index (BMI) is a causal risk factor for endometrial cancer but the tumor molecular mechanisms affected by adiposity and their therapeutic relevance remain poorly understood. Here we characterize the tumor multi-omic landscape of endometrial cancers that have developed on a background of lifelong germline genetic exposure to elevated BMI. We built a polygenic score (PGS) for BMI in women using data on independent, genome-wide significant variants associated with adult BMI in 434,794 women. We performed germline (blood) genotype quality control and imputation on data from 354 endometrial cancer cases from The Cancer Genome Atlas (TCGA). We assigned each case in this TCGA cohort their genetically predicted life-course BMI based on the BMI PGS. Multivariable generalized linear models adjusted for age, stage, microsatellite status and genetic principal components were used to test for associations between the BMI germline PGS and endometrial cancer tumor genome-wide genomic, transcriptomic, proteomic, epigenomic and immune traits in TCGA. High BMI germline PGS was associated with (i) upregulated tumor gene expression in the IL6-JAK-STAT3 pathway (FDR=4.2×10-7); (ii) increased estimated intra-tumor activated mast cell infiltration (FDR=0.008); (iii) increased single base substitution (SBS) mutational signatures 1 (FDR=0.03) and 5 (FDR=0.09) and decreased SBS13 (FDR=0.09), implicating age-related and APOBEC mutagenesis, respectively; and (iv) decreased tumor EGFR protein expression (FDR=0.07). Alterations in IL6-JAK-STAT3 signaling gene and EGFR protein expression were, in turn, significantly associated with both overall survival and progression-free interval. Thus, we integrated germline and somatic data using a novel study design to identify associations between genetically predicted lifelong exposure to higher BMI and potentially actionable endometrial cancer tumor molecular features. These associations inform our understanding of how high BMI may influence the development and progression of this cancer, impacting endometrial tumor biology and clinical outcomes.

Menopausal hormone therapy use and risk of ovarian cancer by race: the ovarian cancer in women of African ancestry consortium.

BACKGROUND: Most studies examining post-menopausal menopausal hormone therapy (MHT) use and ovarian cancer risk have focused on White women and few have included Black women. METHODS: We evaluated MHT use and ovarian cancer risk in Black (n = 800 cases, 1783 controls) and White women (n = 2710 cases, 8556 controls), using data from the Ovarian Cancer in Women of African Ancestry consortium. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association of MHT use with ovarian cancer risk, examining histotype, MHT type and duration of use. RESULTS: Long-term MHT use, ≥10 years, was associated with an increased ovarian cancer risk for White women (OR = 1.38, 95%CI: 1.22-1.57) and the association was consistent for Black women (OR = 1.20, 95%CI: 0.81-1.78, pinteraction = 0.4). For White women, the associations between long-term unopposed estrogen or estrogen plus progesterone use and ovarian cancer risk were similar; the increased risk associated with long-term MHT use was confined to high-grade serous and endometroid tumors. Based on smaller numbers for Black women, the increased ovarian cancer risk associated with long-term MHT use was apparent for unopposed estrogen use and was predominately confined to other epithelial histotypes. CONCLUSION: The association between long-term MHT use and ovarian cancer risk was consistent for Black and White women.

The Association between Mediated Deprivation and Ovarian Cancer Survival among African American Women.

BACKGROUND: Deprivation indices are often used to adjust for socio-economic disparities in health studies. Their role has been partially evaluated for certain population-level cancer outcomes, but examination of their role in ovarian cancer is limited. In this study, we evaluated a range of well-recognized deprivation indices in relation to cancer survival in a cohort of self-identified Black women diagnosed with ovarian cancer. This study aimed to determine if clinical or diagnostic characteristics lie on a mediating pathway between socioeconomic status (SES) and deprivation and ovarian cancer survival in a minority population that experiences worse survival from ovarian cancer. METHODS: We used mediation analysis to look at the direct and indirect causal effects of deprivation indices with main mediators of the SEER stage at diagnosis and residual disease. The analysis employed Bayesian structural equation models with variable selection. We applied a joint Bayesian structural model for the mediator, including a Weibull mixed model for the vital outcome with deprivation as exposure. We selected modifiers via a Monte Carlo model selection procedure. RESULTS: The results suggest that high SES-related indices, such as Yost, Kolak urbanicity (URB), mobility (MOB) and SES dimensions, and concentrated disadvantage index (CDI), all have a significant impact on improved survival. In contrast, area deprivation index (ADI)/Singh, and area level poverty (POV) did not have a major impact. In some cases, the indirect effects have very wide credible intervals, so the total effect is not well estimated despite the estimation of the direct effect. CONCLUSIONS: First, it is clear that commonly used indices such as Yost, or CDI both significantly impact the survival experience of Black women diagnosed with epithelial ovarian cancer. In addition, the Kolak dimension indices (URB, MOB, mixed immigrant: MICA and SES) also demonstrate a significant association, depending on the mediator. Mediation effects differ according to the mediator chosen.

Association of inflammation-related exposures and ovarian cancer survival in a multi-site cohort study of Black women.

BACKGROUND: An association was observed between an inflammation-related risk score (IRRS) and worse overall survival (OS) among a cohort of mostly White women with invasive epithelial ovarian cancer (EOC). Herein, we evaluated the association between the IRRS and OS among Black women with EOC, a population with higher frequencies of pro-inflammatory exposures and worse survival. METHODS: The analysis included 592 Black women diagnosed with EOC from the African American Cancer Epidemiology Study (AACES). Cox proportional hazards models were used to compute hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of the IRRS and OS, adjusting for relevant covariates. Additional inflammation-related exposures, including the energy-adjusted Dietary Inflammatory Index (E-DIITM), were evaluated. RESULTS: A dose-response trend was observed showing higher IRRS was associated with worse OS (per quartile HR: 1.11, 95% CI: 1.01-1.22). Adding the E-DII to the model attenuated the association of IRRS with OS, and increasing E-DII, indicating a more pro-inflammatory diet, was associated with shorter OS (per quartile HR: 1.12, 95% CI: 1.02-1.24). Scoring high on both indices was associated with shorter OS (HR: 1.54, 95% CI: 1.16-2.06). CONCLUSION: Higher levels of inflammation-related exposures were associated with decreased EOC OS among Black women.

Deprivation and segregation in ovarian cancer survival among African American women: a mediation analysis.

PURPOSE: Deprivation and segregation indices are often examined as possible explanations for observed health disparities in population-based studies. In this study, we assessed the role of recognized deprivation and segregation indices specifically as they affect survival in a cohort of self-identified Black women diagnosed with ovarian cancer who enrolled in the African American Cancer Epidemiology Study. METHODS: Mediation analysis was used to examine the direct and indirect effects between deprivation or segregation and overall survival via a Bayesian structural equation model with Gibbs variable selection. RESULTS: The results suggest that high socioeconomic status-related indices have an association with increased survival, ranging from 25% to 56%. In contrast, index of concentration at the extremes-race does not have a significant impact on overall survival. In many cases, the indirect effects have very wide credible intervals; consequently, the total effect is not well estimated despite the estimation of the direct effect. CONCLUSIONS: Our results show that Black women living in higher socioeconomic status neighborhoods are associated with increased survival with ovarian cancer using area-level economic indices such as Yost or index of concentration at the extremes-income. In addition, the Kolak urbanization index has a similar impact and highlights the importance of area-level deprivation and segregation as potentially modifiable social factors in ovarian cancer survival.

Predicted Proteome Association Studies of Breast, Prostate, Ovarian, and Endometrial Cancers Implicate Plasma Protein Regulation in Cancer Susceptibility.

BACKGROUND: Predicting protein levels from genotypes for proteome-wide association studies (PWAS) may provide insight into the mechanisms underlying cancer susceptibility. METHODS: We performed PWAS of breast, endometrial, ovarian, and prostate cancers and their subtypes in several large European-ancestry discovery consortia (effective sample size: 237,483 cases/317,006 controls) and tested the results for replication in an independent European-ancestry GWAS (31,969 cases/410,350 controls). We performed PWAS using the cancer GWAS summary statistics and two sets of plasma protein prediction models, followed by colocalization analysis. RESULTS: Using Atherosclerosis Risk in Communities (ARIC) models, we identified 93 protein-cancer associations [false discovery rate (FDR) < 0.05]. We then performed a meta-analysis of the discovery and replication PWAS, resulting in 61 significant protein-cancer associations (FDR < 0.05). Ten of 15 protein-cancer pairs that could be tested using Trans-Omics for Precision Medicine (TOPMed) protein prediction models replicated with the same directions of effect in both cancer GWAS (P < 0.05). To further support our results, we applied Bayesian colocalization analysis and found colocalized SNPs for SERPINA3 protein levels and prostate cancer (posterior probability, PP = 0.65) and SNUPN protein levels and breast cancer (PP = 0.62). CONCLUSIONS: We used PWAS to identify potential biomarkers of hormone-related cancer risk. SNPs in SERPINA3 and SNUPN did not reach genome-wide significance for cancer in the original GWAS, highlighting the power of PWAS for novel locus discovery, with the added advantage of providing directions of protein effect. IMPACT: PWAS and colocalization are promising methods to identify potential molecular mechanisms underlying complex traits.

Racial Differences in the Association of Endometriosis and Uterine Leiomyomas With the Risk of Ovarian Cancer.

OBJECTIVE: To evaluate associations between endometriosis and uterine leiomyomas with ovarian cancer risk by race and the effect of hysterectomy on these associations. METHODS: We used data from four case-control studies and two case-control studies nested within prospective cohorts in the OCWAA (Ovarian Cancer in Women of African Ancestry) consortium. The study population included 3,124 Black participants and 5,458 White participants, of whom 1,008 Black participants and 2,237 White participants had ovarian cancer. Logistic regression was used to calculate odds ratios (ORs) and 95% CIs for the associations of endometriosis and leiomyomas with ovarian cancer risk, by race, stratified by histotype and hysterectomy. RESULTS: The prevalences of endometriosis and leiomyomas were 6.4% and 43.2% among Black participants and 7.0% and 21.5% among White participants, respectively. Endometriosis was associated with an increased risk of endometrioid and clear-cell ovarian cancer in both racial groups (eg, OR for endometrioid tumors for Black and White participants 7.06 [95% CI 3.86-12.91] and 2.17 [95% CI 1.36-3.45], respectively, Phetereogeneity =.003). The association between endometriosis and ovarian cancer risk in White participants was stronger in those without hysterectomy, but no difference was observed in Black participants (all Pinteraction ≥.05). Leiomyomas were associated with an elevated risk of ovarian cancer only in those without hysterectomy in both Black (OR 1.34, 95% CI 1.11-1.62) and White (OR 1.22, 95% CI 1.05-1.41) participants (all Pinteraction ≥.05). CONCLUSIONS: Black and White participants with endometriosis had a higher risk of ovarian cancer, and hysterectomy modified this association among White participants. Leiomyomas were associated with an increased risk of ovarian cancer in both racial groups, with hysterectomy modifying the risk in both groups. Understanding how racial differences in access to care and treatment options (eg, hysterectomy) may help guide future risk reduction strategies.

The genomic landscape of familial glioma.

Glioma is a rare brain tumor with a poor prognosis. Familial glioma is a subset of glioma with a strong genetic predisposition that accounts for approximately 5% of glioma cases. We performed whole-genome sequencing on an exploratory cohort of 203 individuals from 189 families with a history of familial glioma and an additional validation cohort of 122 individuals from 115 families. We found significant enrichment of rare deleterious variants of seven genes in both cohorts, and the most significantly enriched gene was HERC2 (P = 0.0006). Furthermore, we identified rare noncoding variants in both cohorts that were predicted to affect transcription factor binding sites or cause cryptic splicing. Last, we selected a subset of discovered genes for validation by CRISPR knockdown screening and found that DMBT1, HP1BP3, and ZCH7B3 have profound impacts on proliferation. This study performs comprehensive surveillance of the genomic landscape of familial glioma.

Role of neighborhood context in ovarian cancer survival disparities: current research and future directions.

Ovarian cancer is the fifth leading cause of cancer-associated mortality among US women with survival disparities seen across race, ethnicity, and socioeconomic status, even after accounting for histology, stage, treatment, and other clinical factors. Neighborhood context can play an important role in ovarian cancer survival, and, to the extent to which minority racial and ethnic groups and populations of lower socioeconomic status are more likely to be segregated into neighborhoods with lower quality social, built, and physical environment, these contextual factors may be a critical component of ovarian cancer survival disparities. Understanding factors associated with ovarian cancer outcome disparities will allow clinicians to identify patients at risk for worse outcomes and point to measures, such as social support programs or transportation aid, that can help to ameliorate such disparities. However, research on the impact of neighborhood contextual factors in ovarian cancer survival and in disparities in ovarian cancer survival is limited. This commentary focuses on the following neighborhood contextual domains: structural and institutional context, social context, physical context represented by environmental exposures, built environment, rurality, and healthcare access. The research conducted to date is presented and clinical implications and recommendations for future interventions and studies to address disparities in ovarian cancer outcomes are proposed.

Association of Frequent Aspirin Use With Ovarian Cancer Risk According to Genetic Susceptibility.

Importance: Frequent aspirin use is associated with reduced ovarian cancer risk, but it is unknown whether genetic factors modify this association. Understanding effect modifiers is important given that any use of aspirin for ovarian cancer chemoprevention will likely need to focus on specific higher-risk subgroups. Objective: To evaluate whether the association between frequent aspirin use and ovarian cancer is modified by a polygenic score (PGS) for nonmucinous ovarian cancer. Design, Setting, and Participants: We pooled individual-level data from 8 population-based case-control studies from the Ovarian Cancer Association Consortium conducted in the US, UK, and Australia between 1995 and 2009. We included case patients and control participants with both genetic data and data on frequent aspirin use. Case patients with mucinous ovarian cancer were excluded. Data were analyzed between November 1, 2021, and July 31, 2022. Exposures: Frequent aspirin use, defined as daily or almost daily use for 6 months or longer. Main Outcomes and Measures: The main outcome was nonmucinous epithelial ovarian cancer. We used logistic regression to estimate odds ratios (ORs) and 95% CIs and likelihood ratio tests to investigate effect modification by the PGS. Results: There were 4476 case patients with nonmucinous ovarian cancer and 6659 control participants included in this analysis. At study enrollment, the median (IQR) age was 58 (50-66) years for case patients and 57 (49-65) years for control participants. Case patients and control participants self-reported that they were Black (122 [3%] vs 218 [3%]), White (3995 [89%] vs 5851 [88%]), or of other race and ethnicity (348 [8%] vs 580 [9%]; race and ethnicity were unknown for 11 [0%] vs 10 [0%]). There were 575 case patients (13%) and 1030 control participants (15%) who reported frequent aspirin use. The 13% reduction in ovarian cancer risk associated with frequent aspirin use (OR, 0.87 [95% CI, 0.76-0.99]) was not modified by the PGS. Consistent ORs were observed among individuals with a PGS less than (0.85 [0.70-1.02]) and greater than (0.86 [0.74-1.01]) the median. Results were similar by histotype. Conclusions and Relevance: The findings of this study suggest that genetic susceptibility to ovarian cancer based on currently identified common genetic variants does not appear to modify the protective association between frequent aspirin use and ovarian cancer risk. Future work should continue to explore the role of aspirin use for ovarian cancer prevention among individuals who are at higher risk for ovarian cancer.

Lifetime ovulatory years and risk of epithelial ovarian cancer: a multinational pooled analysis.

BACKGROUND: The role of ovulation in epithelial ovarian cancer (EOC) is supported by the consistent protective effects of parity and oral contraceptive use. Whether these factors protect through anovulation alone remains unclear. We explored the association between lifetime ovulatory years (LOY) and EOC. METHODS: LOY was calculated using 12 algorithms. Odds ratios (ORs) and 95% confidence intervals (CIs) estimated the association between LOY or LOY components and EOC among 26 204 control participants and 21 267 case patients from 25 studies. To assess whether LOY components act through ovulation suppression alone, we compared beta coefficients obtained from regression models with expected estimates assuming 1 year of ovulation suppression has the same effect regardless of source. RESULTS: LOY was associated with increased EOC risk (OR per year increase = 1.014, 95% CI = 1.009 to 1.020 to OR per year increase = 1.044, 95% CI = 1.041 to 1.048). Individual LOY components, except age at menarche, also associated with EOC. The estimated model coefficient for oral contraceptive use and pregnancies were 4.45 times and 12- to 15-fold greater than expected, respectively. LOY was associated with high-grade serous, low-grade serous, endometrioid, and clear cell histotypes (ORs per year increase = 1.054, 1.040, 1.065, and 1.098, respectively) but not mucinous tumors. Estimated coefficients of LOY components were close to expected estimates for high-grade serous but larger than expected for low-grade serous, endometrioid, and clear cell histotypes. CONCLUSIONS: LOY is positively associated with nonmucinous EOC. Differences between estimated and expected model coefficients for LOY components suggest factors beyond ovulation underlie the associations between LOY components and EOC in general and for non-HGSOC.

Survival of epithelial ovarian cancer in Black women: a society to cell approach in the African American cancer epidemiology study (AACES).

PURPOSE: The causes for the survival disparity among Black women with epithelial ovarian cancer (EOC) are likely multi-factorial. Here we describe the African American Cancer Epidemiology Study (AACES), the largest cohort of Black women with EOC. METHODS: AACES phase 2 (enrolled 2020 onward) is a multi-site, population-based study focused on overall survival (OS) of EOC. Rapid case ascertainment is used in ongoing patient recruitment in eight U.S. states, both northern and southern. Data collection is composed of a survey, biospecimens, and medical record abstraction. Results characterizing the survival experience of the phase 1 study population (enrolled 2010-2015) are presented. RESULTS: Thus far, ~ 650 patients with EOC have been enrolled in the AACES. The five-year OS of AACES participants approximates those of Black women in the Surveillance Epidemiology and End Results (SEER) registry who survive at least 10-month past diagnosis and is worse compared to white women in SEER, 49 vs. 60%, respectively. A high proportion of women in AACES have low levels of household income (45% < $25,000 annually), education (51% ≤ high school education), and insurance coverage (32% uninsured or Medicaid). Those followed annually differ from those without follow-up with higher levels of localized disease (28 vs 24%) and higher levels of optimal debulking status (73 vs 67%). CONCLUSION: AACES is well positioned to evaluate the contribution of social determinants of health to the poor survival of Black women with EOC and advance understanding of the multi-factorial causes of the ovarian cancer survival disparity in Black women.

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.