Accuracy of patient race and ethnicity data in a central cancer registry

PURPOSE

Race and Hispanic ethnicity data can be challenging for central cancer registries to collect. We evaluated the accuracy of the race and Hispanic ethnicity variables collected by the Utah Cancer Registry compared to self-report.

METHODS

Participants were 3,162 cancer survivors who completed questionnaires administered in 2015-2022 by the Utah Cancer Registry. Each survey included separate questions collecting race and Hispanic ethnicity, respectively. Registry-collected race and Hispanic ethnicity were compared to self-reported values for the same individuals. We calculated sensitivity and specificity for each race category and Hispanic ethnicity separately.

RESULTS

Survey participants included 323 (10.2%) survivors identifying as Hispanic, a lower proportion Hispanic than the 12.1% in the registry Hispanic variable (sensitivity 88.2%, specificity 96.5%). For race, 43 participants (1.4%) self-identified as American Indian or Alaska Native (AIAN), 32 (1.0%) as Asian, 23 (0.7%) as Black or African American, 16 (0.5%) Pacific Islander (PI), and 2994 (94.7%) as White. The registry race variable classified a smaller proportion of survivors as members of each of these race groups except White. Sensitivity for classification of race as AIAN was 9.3%, Asian 40.6%, Black 60.9%, PI 25.0%, and specificity for each of these groups was > 99%. Sensitivity and specificity for White were 98.8% and 47.4%.

CONCLUSION

Cancer registry race and Hispanic ethnicity data often did not match the individual's self-identification. Of particular concern is the high proportion of AIAN individuals whose race is misclassified. Continued attention should be directed to the accurate capture of race and ethnicity data by hospitals.

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.

Concurrent RB1 loss and BRCA-deficiency predicts enhanced immunological response and long-term survival in tubo-ovarian high-grade serous carcinoma

Background

Somatic loss of the tumour suppressor RB1 is a common event in tubo-ovarian high-grade serous carcinoma (HGSC), which frequently co-occurs with alterations in homologous recombination DNA repair genes including BRCA1 and BRCA2 (BRCA). We examined whether tumour expression of RB1 was associated with survival across ovarian cancer histotypes (HGSC, endometrioid (ENOC), clear cell (CCOC), mucinous (MOC), low-grade serous carcinoma (LGSC)), and how co-occurrence of germline BRCA pathogenic variants and RB1 loss influences long-term survival in a large series of HGSC.

Patients and methods

RB1 protein expression patterns were classified by immunohistochemistry in epithelial ovarian carcinomas of 7436 patients from 20 studies participating in the Ovarian Tumor Tissue Analysis consortium and assessed for associations with overall survival (OS), accounting for patient age at diagnosis and FIGO stage. We examined RB1 expression and germline BRCA status in a subset of 1134 HGSC, and related genotype to survival, tumour infiltrating CD8+ lymphocyte counts and transcriptomic subtypes. Using CRISPR-Cas9, we deleted RB1 in HGSC cell lines with and without BRCA1 mutations to model co-loss with treatment response. We also performed genomic analyses on 126 primary HGSC to explore the molecular characteristics of concurrent homologous recombination deficiency and RB1 loss.

Results

RB1 protein loss was most frequent in HGSC (16.4%) and was highly correlated with RB1 mRNA expression. RB1 loss was associated with longer OS in HGSC (hazard ratio [HR] 0.74, 95% confidence interval [CI] 0.66-0.83, P = 6.8 ×10-7), but with poorer prognosis in ENOC (HR 2.17, 95% CI 1.17-4.03, P = 0.0140). Germline BRCA mutations and RB1 loss co-occurred in HGSC (P < 0.0001). Patients with both RB1 loss and germline BRCA mutations had a superior OS (HR 0.38, 95% CI 0.25-0.58, P = 5.2 ×10-6) compared to patients with either alteration alone, and their median OS was three times longer than non-carriers whose tumours retained RB1 expression (9.3 years vs. 3.1 years). Enhanced sensitivity to cisplatin (P < 0.01) and paclitaxel (P < 0.05) was seen in BRCA1 mutated cell lines with RB1 knockout. Among 126 patients with whole-genome and transcriptome sequence data, combined RB1 loss and genomic evidence of homologous recombination deficiency was correlated with transcriptional markers of enhanced interferon response, cell cycle deregulation, and reduced epithelial-mesenchymal transition in primary HGSC. CD8+ lymphocytes were most prevalent in BRCA-deficient HGSC with co-loss of RB1.

Conclusions

Co-occurrence of RB1 loss and BRCA mutation was associated with exceptionally long survival in patients with HGSC, potentially due to better treatment response and immune stimulation.

Advancing Social and Environmental Research in Cancer Registries Using Geomasking for Address-Level Data

Understanding the social and environmental causes of cancer in the United States, particularly in marginalized communities, is a major research priority. Population-based cancer registries are essential for advancing this research, given their nearly complete capture of incident cases within their catchment areas. Most registries limit the release of address-level geocodes linked to cancer outcomes to comply with state health departmental regulations. These policies ensure patient privacy, uphold data confidentiality, and enhance trust in research. However, these restrictions also limit the conduct of high-quality epidemiologic studies on social and environmental factors that may contribute to cancer burden. Geomasking refers to computational algorithms that distort locational data to attain a balance between effectively "masking" the original address location while faithfully maintaining the spatial structure in the data. We propose that the systematic deployment of scalable geomasking algorithms could accelerate research on social and environmental contributions across the cancer continuum by reducing measurement error bias while also protecting privacy. We encourage multidisciplinary teams of registry officials, geospatial analysts, cancer researchers, and others engaged in this form of research to evaluate and apply geomasking procedures based on feasibility of implementation, accuracy, and privacy protection to accelerate population-based research on social and environmental causes of cancer.

Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors

BACKGROUND

Single-cell gene expression profiling provides unique opportunities to understand tumor heterogeneity and the tumor microenvironment. Because of cost and feasibility, profiling bulk tumors remains the primary population-scale analytical strategy. Many algorithms can deconvolve these tumors using single-cell profiles to infer their composition. While experimental choices do not change the true underlying composition of the tumor, they can affect the measurements produced by the assay.

RESULTS

We generated a dataset of high-grade serous ovarian tumors with paired expression profiles from using multiple strategies to examine the extent to which experimental factors impact the results of downstream tumor deconvolution methods. We find that pooling samples for single-cell sequencing and subsequent demultiplexing has a minimal effect. We identify dissociation-induced differences that affect cell composition, leading to changes that may compromise the assumptions underlying some deconvolution algorithms. We also observe differences across mRNA enrichment methods that introduce additional discrepancies between the two data types. We also find that experimental factors change cell composition estimates and that the impact differs by method.

CONCLUSIONS

Previous benchmarks of deconvolution methods have largely ignored experimental factors. We find that methods vary in their robustness to experimental factors. We provide recommendations for methods developers seeking to produce the next generation of deconvolution approaches and for scientists designing experiments using deconvolution to study tumor heterogeneity.

Pathways to lung cancer diagnosis among individuals who did not receive lung cancer screening: a qualitative study

BACKGROUND

Although early detection of lung cancer through screening is associated with better prognosis, most lung cancers are diagnosed among unscreened individuals. We therefore sought to characterize pathways to lung cancer diagnosis among unscreened individuals.

METHODS

Participants were individuals with lung cancer who did not undergo asymptomatic lung cancer screening (n = 13) and healthcare providers who may be involved in the pathway to lung cancer diagnosis (n = 13). We conducted semi-structured interviews to identify themes in lung cancer patients' narratives of their cancer diagnoses and providers' personal and/or professional experiences of various pathways to lung cancer diagnoses, to identify delays in diagnosis. We audio-recorded, transcribed, and coded interviews in two stages. First, we conducted deductive coding using three time-period intervals from the Models of Pathways to Treatment framework: appraisal, help-seeking, and diagnostic (i.e., excluding pre-treatment). Second, we conducted inductive coding to identify themes within each time-period interval, and classified these themes as either barriers or facilitators to diagnosis. Coding and thematic summarization were completed independently by two separate analysts who discussed for consensus.

RESULTS

Eight of the patient participants had formerly smoked, and five had never smoked. We identified eight barrier/facilitator themes within the three time-period intervals. Within the appraisal interval, the barrier theme was (1) minimization or misattribution of symptoms, and the facilitator theme was (2) acknowledgment of symptoms. Within the help-seeking interval, the barrier theme was (3) hesitancy to seek care, and the facilitator theme was (4) routine care. Within the diagnosis interval, barrier themes were (5) health system challenges, and (6) social determinants of health; and facilitator themes were (7) severe symptoms and known risk factors, and (8) self-advocacy. Many themes were interrelated, including minimization or misattribution of symptoms and hesitancy to seek care, which may collectively contribute to care and imaging delays.

CONCLUSIONS

Interventions to reduce hesitancy to seek care may facilitate timely lung cancer diagnoses. More prompt referral to imaging-especially computed tomography (CT)-among symptomatic patients, along with patient self-advocacy for imaging, may reduce delays in diagnosis.

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.

Use of the Decipher genomic classifier among men with prostate cancer in the United States

BACKGROUND

Management of localized or recurrent prostate cancer since the 1990s has been based on risk stratification using clinicopathological variables, including Gleason score, T stage (based on digital rectal exam), and prostate-specific antigen (PSA). In this study a novel prognostic test, the Decipher Prostate Genomic Classifier (GC), was used to stratify risk of prostate cancer progression in a US national database of men with prostate cancer.

METHODS

Records of prostate cancer cases from participating SEER (Surveillance, Epidemiology, and End Results) program registries, diagnosed during the period from 2010 through 2018, were linked to records of testing with the GC prognostic test. Multivariable analysis was used to quantify the association between GC scores or risk groups and use of definitive local therapy after diagnosis in the GC biopsy-tested cohort and postoperative radiotherapy in the GC-tested cohort as well as adverse pathological findings after prostatectomy.

RESULTS

A total of 572 545 patients were included in the analysis, of whom 8927 patients underwent GC testing. GC biopsy-tested patients were more likely to undergo active active surveillance or watchful waiting than untested patients (odds ratio [OR] =2.21, 95% confidence interval [CI] = 2.04 to 2.38, P < .001). The highest use of active surveillance or watchful waiting was for patients with a low-risk GC classification (41%) compared with those with an intermediate- (27%) or high-risk (11%) GC classification (P < .001). Among National Comprehensive Cancer Network patients with low and favorable-intermediate risk, higher GC risk class was associated with greater use of local therapy (OR = 4.79, 95% CI = 3.51 to 6.55, P < .001). Within this subset of patients who were subsequently treated with prostatectomy, high GC risk was associated with harboring adverse pathological findings (OR = 2.94, 95% CI = 1.38 to 6.27, P = .005). Use of radiation after prostatectomy was statistically significantly associated with higher GC risk groups (OR = 2.69, 95% CI = 1.89 to 3.84).

CONCLUSIONS

There is a strong association between use of the biopsy GC test and likelihood of conservative management. Higher genomic classifier scores are associated with higher rates of adverse pathology at time of surgery and greater use of postoperative radiotherapy.In this study the Decipher Prostate Genomic Classifier (GC) was used to analyze a US national database of men with prostate cancer. Use of the GC was associated with conservative management (ie, active surveillance). Among men who had high-risk GC scores and then had surgery, there was a 3-fold higher chance of having worrisome findings in surgical specimens.

Folate Intake and Ovarian Cancer Risk among Women with Endometriosis: A Case-Control Study from the Ovarian Cancer Association Consortium

BACKGROUND

Although folate intake has not been associated with an increased risk of ovarian cancer overall, studies of other cancer types have suggested that high folate intake may promote carcinogenesis in precancerous lesions. Women with endometriosis (a potential precancerous lesion) have an increased risk of developing ovarian cancer; however, whether high folate intake increases risk in this group is unknown.

METHODS

We conducted a pooled analysis of six case-control studies from the Ovarian Cancer Association Consortium to investigate the association between folate intake and risk of ovarian cancer among women with and without self-reported endometriosis. We included 570 cases/558 controls with and 5,171/7,559 without endometriosis. We used logistic regression to estimate odds ratios (OR) and 95% confidence intervals for the association between folate intake (dietary, supplemental, and total) and ovarian cancer risk. Finally, we used Mendelian randomization (MR) to evaluate our results using genetic markers as a proxy for folate status.

RESULTS

Higher dietary folate intake was associated with an increased risk of ovarian cancer for women with endometriosis [OR, 1.37 (1.01-1.86)] but not for women without endometriosis. There was no association between supplemental folate intake and ovarian cancer risk for women with or without endometriosis. A similar pattern was seen using MR.

CONCLUSIONS

High dietary folate intake may be associated with an increased risk of ovarian cancer among women with endometriosis.

IMPACT

Women with endometriosis with high folate diets may be at increased risk of ovarian cancer. Further research is needed on the potential cancer-promoting effects of folate in this group.

Metabolic obesity phenotypes and obesity-related cancer risk in the National Health and Nutrition Examination Survey

INTRODUCTION

Body mass index (BMI) fails to identify up to one-third of normal weight individuals with metabolic dysfunction who may be at increased risk of obesity-related cancer (ORC). Metabolic obesity phenotypes, an alternate metric to assess metabolic dysfunction with or without obesity, were evaluated for association with ORC risk.

METHODS

National Health and Nutrition Examination Survey participants from 1999 to 2018 (N = 19,500) were categorized into phenotypes according to the metabolic syndrome (MetS) criteria and BMI: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight/obese (MHO) and metabolically unhealthy overweight/obese (MUO). Adjusted multivariable logistic regression models were used to evaluate associations with ORC.

RESULTS

With metabolic dysfunction defined as ≥1 MetS criteria, ORC cases (n = 528) had higher proportions of MUNW (28.2% vs. 17.4%) and MUO (62.6% vs. 60.9%) phenotypes than cancer-free individuals (n = 18,972). Compared with MHNW participants, MUNW participants had a 2.2-times higher ORC risk [OR (95%CI) = 2.21 (1.27-3.85)]. MHO and MUO participants demonstrated a 43% and 56% increased ORC risk, respectively, compared to MHNW, but these did not reach statistical significance [OR (95% CI) = 1.43 (0.46-4.42), 1.56 (0.91-2.67), respectively]. Hyperglycaemia, hypertension and central obesity were all independently associated with higher ORC risk compared to MHNW.

CONCLUSIONS

MUNW participants have a higher risk of ORC than other abnormal phenotypes, compared with MHNW participants. Incorporating metabolic health measures in addition to assessing BMI may improve ORC risk stratification. Further research on the relationship between metabolic dysfunction and ORC is warranted.

31-Gene Expression Profile Testing in Cutaneous Melanoma and Survival Outcomes in a Population-Based Analysis: A SEER Collaboration

PURPOSE

The DecisionDx-Melanoma 31-gene expression profile (31-GEP) test is validated to classify cutaneous malignant melanoma (CM) patient risk of recurrence, metastasis, or death as low (class 1A), intermediate (class 1B/2A), or high (class 2B). This study aimed to examine the effect of 31-GEP testing on survival outcomes and confirm the prognostic ability of the 31-GEP at the population level.

METHODS

Patients with stage I-III CM with a clinical 31-GEP result between 2016 and 2018 were linked to data from 17 SEER registries (n = 4,687) following registries' operation procedures for linkages. Melanoma-specific survival (MSS) and overall survival (OS) differences by 31-GEP risk category were examined using Kaplan-Meier analysis and the log-rank test. Crude and adjusted hazard ratios (HRs) were calculated using Cox regression model to evaluate variables associated with survival. 31-GEP tested patients were propensity score-matched to a cohort of non-31-GEP tested patients from the SEER database. Robustness of the effect of 31-GEP testing was assessed using resampling.

RESULTS

Patients with a 31-GEP class 1A result had higher 3-year MSS and OS than patients with a class 1B/2A or class 2B result (MSS: 99.7% v 97.1% v 89.6%, P < .001; OS: 96.6% v 90.2% v 79.4%, P < .001). A class 2B result was an independent predictor of MSS (HR, 7.00; 95% CI, 2.70 to 18.00) and OS (HR, 2.39; 95% CI, 1.54 to 3.70). 31-GEP testing was associated with a 29% lower MSS mortality (HR, 0.71; 95% CI, 0.53 to 0.94) and 17% lower overall mortality (HR, 0.83; 95% CI, 0.70 to 0.99) relative to untested patients.

CONCLUSION

In a population-based, clinically tested melanoma cohort, the 31-GEP stratified patients by their risk of dying from melanoma.

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.

p53 and ovarian carcinoma survival: an Ovarian Tumor Tissue Analysis consortium study

Our objective was to test whether p53 expression status is associated with survival for women diagnosed with the most common ovarian carcinoma histotypes (high-grade serous carcinoma [HGSC], endometrioid carcinoma [EC], and clear cell carcinoma [CCC]) using a large multi-institutional cohort from the Ovarian Tumor Tissue Analysis (OTTA) consortium. p53 expression was assessed on 6,678 cases represented on tissue microarrays from 25 participating OTTA study sites using a previously validated immunohistochemical (IHC) assay as a surrogate for the presence and functional effect of TP53 mutations. Three abnormal expression patterns (overexpression, complete absence, and cytoplasmic) and the normal (wild type) pattern were recorded. Survival analyses were performed by histotype. The frequency of abnormal p53 expression was 93.4% (4,630/4,957) in HGSC compared to 11.9% (116/973) in EC and 11.5% (86/748) in CCC. In HGSC, there were no differences in overall survival across the abnormal p53 expression patterns. However, in EC and CCC, abnormal p53 expression was associated with an increased risk of death for women diagnosed with EC in multivariate analysis compared to normal p53 as the reference (hazard ratio [HR] = 2.18, 95% confidence interval [CI] 1.36-3.47, p = 0.0011) and with CCC (HR = 1.57, 95% CI 1.11-2.22, p = 0.012). Abnormal p53 was also associated with shorter overall survival in The International Federation of Gynecology and Obstetrics stage I/II EC and CCC. Our study provides further evidence that functional groups of TP53 mutations assessed by abnormal surrogate p53 IHC patterns are not associated with survival in HGSC. In contrast, we validate that abnormal p53 IHC is a strong independent prognostic marker for EC and demonstrate for the first time an independent prognostic association of abnormal p53 IHC with overall survival in patients with CCC.

Abstract 3005: Pre-diagnostic methylation-based leukocyte profiles and non-small cell lung cancer risk in heavy smokers

Pre-diagnosis circulating leukocyte profiles, including higher white blood cell (WBC) counts and neutrophil-to-lymphocyte ratios (NLR), have been reported to be associated with non-small cell lung cancer (NSCLC) risk. Higher neutrophil levels were recently reported to drive NSCLC-WBC count associations, implicating the innate immune response in NSCLC risk and etiology. Though not directly measurable in bio-banked blood, leukocyte subtype proportions can be estimated using established deconvolution algorithms applied to genome-wide DNA methylation data. We previously reported that NSCLC risk was elevated in heavy smokers with greater pre-diagnosis methylation-derived NLR (mdNLR). Here, we examine the influence of each pre-diagnosis mdNLR leukocyte subtype (neutrophils, and lymphocytes: B, Natural Killer, CD8+T, and CD4+T cells), separately on NSCLC risk. In our nested case-control study from the Beta Carotene and Retinol Efficacy Trial of heavy smokers (≥20 pack years), 243 NSCLC cases were 1:1 matched to controls on age (±5 years), sex, race and ethnicity, enrollment (±2 years), smoking status (ever/never), asbestos exposure, and follow-up time. Methylation was assayed on the Illumina EPIC array in whole blood collected on average 4.4 years (range 0.1-10.1) before diagnosis in NSCLC cases. We assessed conditional logistic regression models for each mdNLR-related leukocyte subtype, dichotomized at the median in controls, and further adjusted for continuous age and smoking pack years at blood draw. We evaluated NSCLC risk overall, and in subgroup strata: histotype, sex, smoking status, asbestos exposure, stage at diagnosis, age at blood draw, age at diagnosis, and time between blood draw and diagnosis. A greater than median level of neutrophils was suggestively associated with NSCLC risk (OR=1.40, 95% CI: 0.93-2.12); this association was restricted to squamous cell carcinoma (SCC n=103 pairs; 2.00, 1.03-3.86), with no association for adenocarcinoma (n=132 pairs; 0.99, 0.57-1.73). SCC-neutrophil associations were strongest among former smokers (n=26 pairs; 6.81, 1.48-31.3), cases with ≤ 4.4 years between blood draw and diagnosis (n=48 pairs; 3.00, 1.10-8.14), cases aged &gt; 64.8 years at blood draw (n=56 pairs; 2.66, 1.05-6.73), and cases diagnosed at stage III or IV (n=61 pairs; 2.21, 0.92-5.30). Greater than median lymphocyte levels were suggestively associated with reduced NSCLC (0.71, 0.47-1.08) and SCC risk (0.62, 0.32-1.21), but less so for adenocarcinoma (0.85, 0.48-1.50). Though statistically imprecise, SCC-lymphocyte associations were strongest for CD4+T cells (0.56, 0.28-1.12). Our results indicate that greater pre-diagnosis neutrophil levels may be a biomarker for SCC, but not adenocarcinoma, in heavy smokers. Given the descriptive nature of this analysis, small sample size, and multiple testing, additional research is needed to replicate these findings.

Citation Format: Laurie Grieshober, Stefan Graw, Matt J. Barnett, Gary E. Goodman, Chu Chen, Devin C. Koestler, Carmen J. Marsit, Jennifer A. Doherty. Pre-diagnostic methylation-based leukocyte profiles and non-small cell lung cancer risk in heavy smokers [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 3005.

Abstract 3506: High-grade serous ovarian cancer somatic mutational signatures in Black and White individuals

Causes of racial disparities in ovarian cancer survival are likely multifactorial, including socio-environmental, structural, and biological factors. Mutational signatures reflect endogenous and exogenous exposures, which may differ by race and ethnicity. This study aims to characterize mutational signatures and their associated etiologies among Black high-grade serous ovarian cancer (HGSC) cases, and to compare the occurrence and distribution of signatures with White TCGA cases. Mutational profiling with whole exome sequencing in matched blood and tumor formalin-fixed paraffin-embedded specimens was performed in 271 HGSC cases identifying as Black or African American and participating in the African American Cancer Epidemiology Study (AACES) or the North Carolina Ovarian Cancer Study (NCOCS). After filtering, we identified 28,601 high-confidence coding mutations in 256 samples that passed quality control assessments. The median number of mutations per sample was 67, similar to that in TCGA at 66. Mutation frequencies of the major genes identified in TCGA were nearly identical in Black AACES/NCOCS cases; mutations in TP53 were present in 96% and 89%, respectively, and mutation frequencies in BRCA1/2, CSMD3, NF1, CDK12, FAT3, GABRA6, and RB1 differed by only 0-2%. We performed mutational signature analysis using SigProfiler and refitting to the Catalogue of Somatic Mutations in Cancer (COSMIC) previously published single base-pair substitution (SBS) signatures reflecting mutational processes resulting from known endogenous and exogenous exposures. SBS signatures are defined by 96 mutation features including the single nucleotide variant class (e.g., C&gt;A, C&gt;G, C&gt;T, T&gt;A, T&gt;C, and T&gt;G) and the identity of the 5’/3’ flanking bases. We observed much higher frequencies of the mismatch repair deficiency, homologous recombination deficiency, ultraviolet light, and treatment exposure signatures in Black AACES/NCOCS cases (26%, 22%, 9%, and 8%, respectively) than in White TCGA cases (3%, 10%, 3%, and 2%, respectively). The frequencies of the remaining signatures with known etiologies (clock-like, reactive oxygen species, base excision repair, mutagen exposure, DNA polymerase epsilon, and tobacco signatures) differed by less than 5% between Black and White cases. Many mismatch repair deficiency signatures identified in Black AACES/NCOCS cases are dominated by C&gt;T or T&gt;C mutations and may represent an artifact from formalin fixation. While we observed that the somatic mutation frequencies in major genes associated with HGSC were similar in Black and White cases, the frequencies of some known mutational signatures were considerably higher in Black HGSC. In particular, despite similar frequencies of BRCA1/2 mutations, the homologous recombination deficiency signature was considerably more common in Black than White HGSC.

Citation Format: Katherine A. Lawson-Michod, David Nix, Lindsay Collin, Natalie Davidson, Ariel Hippen, Chad Huff, Aaron Atkinson, Lucas A. Salas, Lauren Peres, Casey Greene, Joellen Schildkraut, Jeffrey Marks, Jennifer A. Doherty. High-grade serous ovarian cancer somatic mutational signatures in Black and White individuals [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 3506.

Methylation Signature Implicated in Immuno-Suppressive Activities in Tubo-Ovarian High-Grade Serous Carcinoma

BACKGROUND

Better understanding of prognostic factors in tubo-ovarian high-grade serous carcinoma (HGSC) is critical, as diagnosis confers an aggressive disease course. Variation in tumor DNA methylation shows promise predicting outcome, yet prior studies were largely platform-specific and unable to evaluate multiple molecular features.

METHODS

We analyzed genome-wide DNA methylation in 1,040 frozen HGSC, including 325 previously reported upon, seeking a multi-platform quantitative methylation signature that we evaluated in relation to clinical features, tumor characteristics, time to recurrence/death, extent of CD8+ tumor-infiltrating lymphocytes (TIL), gene expression molecular subtypes, and gene expression of the ATP-binding cassette transporter TAP1.

RESULTS

Methylation signature was associated with shorter time to recurrence, independent of clinical factors (N = 715 new set, hazard ratio (HR), 1.65; 95% confidence interval (CI), 1.10-2.46; P = 0.015; N = 325 published set HR, 2.87; 95% CI, 2.17-3.81; P = 2.2 × 10-13) and remained prognostic after adjustment for gene expression molecular subtype and TAP1 expression (N = 599; HR, 2.22; 95% CI, 1.66-2.95; P = 4.1 × 10-8). Methylation signature was inversely related to CD8+ TIL levels (P = 2.4 × 10-7) and TAP1 expression (P = 0.0011) and was associated with gene expression molecular subtype (P = 5.9 × 10-4) in covariate-adjusted analysis.

CONCLUSIONS

Multi-center analysis identified a novel quantitative tumor methylation signature of HGSC applicable to numerous commercially available platforms indicative of shorter time to recurrence/death, adjusting for other factors. Along with immune cell composition analysis, these results suggest a role for DNA methylation in the immunosuppressive microenvironment.

IMPACT

This work aids in identification of targetable epigenome processes and stratification of patients for whom tailored treatment may be most beneficial.

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.

Familial risk of epithelial ovarian cancer after accounting for gynaecological surgery: a population-based study

BACKGROUND

Uptake of risk-reducing surgery has increased among women at high risk of epithelial ovarian cancer. We sought to characterise familial risk of epithelial ovarian cancer histotypes in a population-based study after accounting for gynaecological surgeries, including bilateral oophorectomy.

METHODS

We compared risk of epithelial ovarian cancer in relatives of 3536 epithelial ovarian cancer cases diagnosed in 1966-2016 and relatives of 35 326 matched controls. We used Cox competing risk models, incorporating bilateral oophorectomy as a competing risk, to estimate the relative risk of ovarian cancer in first-degree (FDR), second-degree (SDR) and third-degree (TDR) relatives from 1966 to 2016. We also estimated relative risks in time periods before (1966-1994, 1995-2004) and after (2005-2016) formal recommendations were made for prophylactic oophorectomy among women with pathogenic variants in BRCA1/2.

RESULTS

The relative risks of epithelial ovarian cancer in FDRs, SDRs and TDRs of cases versus controls were 1.68 (95% CI 1.39 to 2.04), 1.51 (95% CI 1.30 to 1.75) and 1.34 (95% CI 1.20 to 1.48), respectively. Relative risks were greatest for high-grade serous, mucinous and 'other epithelial' histotypes. Relative risks were attenuated for case FDRs, but not for SDRs or TDRs, from 2005 onwards, consistent with the timing of recommendations for prophylactic surgery.

CONCLUSION

Familial risk of epithelial ovarian cancer extends to TDRs, especially for high-grade serous and mucinous histotypes. Distant relatives share genes but minimal environment, highlighting the importance of germline inherited genetics in ovarian cancer aetiology. Increased ovarian cancer risk in distant relatives has implications for counselling and recommendations for prophylactic surgeries that, from our data, appear only to reach FDRs.

Increased FOXJ1 protein expression is associated with improved overall survival in high-grade serous ovarian carcinoma: an Ovarian Tumor Tissue Analysis Consortium Study

BACKGROUND

Recently, we showed a >60% difference in 5-year survival for patients with tubo-ovarian high-grade serous carcinoma (HGSC) when stratified by a 101-gene mRNA expression prognostic signature. Given the varied patient outcomes, this study aimed to translate prognostic mRNA markers into protein expression assays by immunohistochemistry and validate their survival association in HGSC.

METHODS

Two prognostic genes, FOXJ1 and GMNN, were selected based on high-quality antibodies, correlation with protein expression and variation in immunohistochemical scores in a preliminary cohort (n = 134 and n = 80, respectively). Six thousand four hundred and thirty-four (FOXJ1) and 5470 (GMNN) formalin-fixed, paraffin-embedded ovarian neoplasms (4634 and 4185 HGSC, respectively) represented on tissue microarrays from the Ovarian Tumor Tissue Analysis consortium underwent immunohistochemical staining and scoring, then univariate and multivariate survival analysis.

RESULTS

Consistent with mRNA, FOXJ1 protein expression exhibited a linear, increasing association with improved overall survival in HGSC patients. Women with >50% expression had the most favourable outcomes (HR = 0.78, 95% CI 0.67-0.91, p < 0.0001). GMNN protein expression was not significantly associated with overall HSGC patient survival. However, HGSCs with >35% GMNN expression showed a trend for better outcomes, though this was not significant.

CONCLUSION

We provide foundational evidence for the prognostic value of FOXJ1 in HGSC, validating the prior mRNA-based prognostic association by immunohistochemistry.

Profiling the immune landscape in mucinous ovarian carcinoma

OBJECTIVE

Mucinous ovarian carcinoma (MOC) is a rare histotype of ovarian cancer, with low response rates to standard chemotherapy, and very poor survival for patients diagnosed at advanced stage. There is a limited understanding of the MOC immune landscape, and consequently whether immune checkpoint inhibitors could be considered for a subset of patients.

METHODS

We performed multicolor immunohistochemistry (IHC) and immunofluorescence (IF) on tissue microarrays in a cohort of 126 MOC patients. Cell densities were calculated in the epithelial and stromal components for tumor-associated macrophages (CD68+/PD-L1+, CD68+/PD-L1-), T cells (CD3+/CD8-, CD3+/CD8+), putative T-regulatory cells (Tregs, FOXP3+), B cells (CD20+/CD79A+), plasma cells (CD20-/CD79a+), and PD-L1+ and PD-1+ cells, and compared these values with clinical factors. Univariate and multivariable Cox Proportional Hazards assessed overall survival. Unsupervised k-means clustering identified patient subsets with common patterns of immune cell infiltration.

RESULTS

Mean densities of PD1+ cells, PD-L1- macrophages, CD4+ and CD8+ T cells, and FOXP3+ Tregs were higher in the stroma compared to the epithelium. Tumors from advanced (Stage III/IV) MOC had greater epithelial infiltration of PD-L1- macrophages, and fewer PD-L1+ macrophages compared with Stage I/II cancers (p = 0.004 and p = 0.014 respectively). Patients with high epithelial density of FOXP3+ cells, CD8+/FOXP3+ cells, or PD-L1- macrophages, had poorer survival, and high epithelial CD79a + plasma cells conferred better survival, all upon univariate analysis only. Clustering showed that most MOC (86%) had an immune depleted (cold) phenotype, with only a small proportion (11/76,14%) considered immune inflamed (hot) based on T cell and PD-L1 infiltrates.

CONCLUSION

In summary, MOCs are mostly immunogenically 'cold', suggesting they may have limited response to current immunotherapies.

Metabolic dysfunction and obesity-related cancer: Results from the cross-sectional National Health and Nutrition Examination Survey

BACKGROUND

Metabolic syndrome (MetS), a group of risk factors that define metabolic dysfunction in adults, is strongly associated with obesity and is an emerging risk factor for cancer. However, the association of MetS and degree of metabolic dysfunction with obesity-related cancer is unknown.

METHODS

Using National Health and Nutrition Examination Survey data from 1999 to 2018, we identified 528 obesity-related cancer cases and 18,972 cancer-free participants. MetS was defined as the presence of or treatment for ≥3 of hyperglycemia, hypertension, hypertriglyceridemia, low HDL-cholesterol, and abdominal obesity. A metabolic syndrome score (MSS) was computed as the total number of abnormal MetS parameters to determine the severity of metabolic dysfunction. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression models, adjusting for sociodemographic and lifestyle factors.

RESULTS

About 45.7% of obesity-related cancer cases were classified as having MetS compared with only 33.0% of cancer-free participants. Overall, MetS and MSS were not associated with obesity-related cancer. However, MSS was associated with higher obesity-related cancer risk among participants under 50 years of age (OR [95% CI] = 1.28 [1.08-1.52]). When evaluating MSS categorically, compared with healthy participants with no abnormal MetS parameters (MSS = 0), participants with one or two abnormal parameters had a statistically significant higher risk of obesity-related cancer (OR [95% CI] = 1.73 [1.06-2.83]).

CONCLUSIONS

Metabolic dysfunction is associated with a higher risk of obesity-related cancer, particularly in young adults under 50 years of age, and among participants with one or two abnormal metabolic parameters. A more accurate indicator of metabolic dysfunction, beyond metabolic syndrome, is needed to better assist in stratifying individuals for obesity-related cancer risk.

Modification of the Association Between Frequent Aspirin Use and Ovarian Cancer Risk: A Meta-Analysis Using Individual-Level Data From Two Ovarian Cancer Consortia

PURPOSE

Frequent aspirin use has been associated with reduced ovarian cancer risk, but no study has comprehensively assessed for effect modification. We leveraged harmonized, individual-level data from 17 studies to examine the association between frequent aspirin use and ovarian cancer risk, overall and across subgroups of women with other ovarian cancer risk factors.

METHODS

Nine cohort studies from the Ovarian Cancer Cohort Consortium (n = 2,600 cases) and eight case-control studies from the Ovarian Cancer Association Consortium (n = 5,726 cases) were included. We used Cox regression and logistic regression to assess study-specific associations between frequent aspirin use (≥ 6 days/week) and ovarian cancer risk and combined study-specific estimates using random-effects meta-analysis. We conducted analyses within subgroups defined by individual ovarian cancer risk factors (endometriosis, obesity, family history of breast/ovarian cancer, nulliparity, oral contraceptive use, and tubal ligation) and by number of risk factors (0, 1, and ≥ 2).

RESULTS

Overall, frequent aspirin use was associated with a 13% reduction in ovarian cancer risk (95% CI, 6 to 20), with no significant heterogeneity by study design (P = .48) or histotype (P = .60). Although no association was observed among women with endometriosis, consistent risk reductions were observed among all other subgroups defined by ovarian cancer risk factors (relative risks ranging from 0.79 to 0.93, all P-heterogeneity > .05), including women with ≥ 2 risk factors (relative risk, 0.81; 95% CI, 0.73 to 0.90).

CONCLUSION

This study, the largest to-date on aspirin use and ovarian cancer, provides evidence that frequent aspirin use is associated with lower ovarian cancer risk regardless of the presence of most other ovarian cancer risk factors. Risk reductions were also observed among women with multiple risk factors, providing proof of principle that chemoprevention programs with frequent aspirin use could target higher-risk subgroups.

Gene-Expression Profiling of Mucinous Ovarian Tumors and Comparison with Upper and Lower Gastrointestinal Tumors Identifies Markers Associated with Adverse Outcomes

PURPOSE

Advanced-stage mucinous ovarian carcinoma (MOC) has poor chemotherapy response and prognosis and lacks biomarkers to aid stage I adjuvant treatment. Differentiating primary MOC from gastrointestinal (GI) metastases to the ovary is also challenging due to phenotypic similarities. Clinicopathologic and gene-expression data were analyzed to identify prognostic and diagnostic features.

EXPERIMENTAL DESIGN

Discovery analyses selected 19 genes with prognostic/diagnostic potential. Validation was performed through the Ovarian Tumor Tissue Analysis consortium and GI cancer biobanks comprising 604 patients with MOC (n = 333), mucinous borderline ovarian tumors (MBOT, n = 151), and upper GI (n = 65) and lower GI tumors (n = 55).

RESULTS

Infiltrative pattern of invasion was associated with decreased overall survival (OS) within 2 years from diagnosis, compared with expansile pattern in stage I MOC [hazard ratio (HR), 2.77; 95% confidence interval (CI), 1.04-7.41, P = 0.042]. Increased expression of THBS2 and TAGLN was associated with shorter OS in MOC patients (HR, 1.25; 95% CI, 1.04-1.51, P = 0.016) and (HR, 1.21; 95% CI, 1.01-1.45, P = 0.043), respectively. ERBB2 (HER2) amplification or high mRNA expression was evident in 64 of 243 (26%) of MOCs, but only 8 of 243 (3%) were also infiltrative (4/39, 10%) or stage III/IV (4/31, 13%).

CONCLUSIONS

An infiltrative growth pattern infers poor prognosis within 2 years from diagnosis and may help select stage I patients for adjuvant therapy. High expression of THBS2 and TAGLN in MOC confers an adverse prognosis and is upregulated in the infiltrative subtype, which warrants further investigation. Anti-HER2 therapy should be investigated in a subset of patients. MOC samples clustered with upper GI, yet markers to differentiate these entities remain elusive, suggesting similar underlying biology and shared treatment strategies.

Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci

BACKGROUND

Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.

METHODS

Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types.

RESULTS

We identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types.

CONCLUSIONS

CNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

Pathways to ovarian cancer diagnosis: a qualitative study

Background

Ovarian cancer is often diagnosed at a late stage, when survival is poor. Qualitative narratives of patients’ pathways to ovarian cancer diagnoses may identify opportunities for earlier cancer detection and, consequently, earlier stage at diagnosis.

Methods

We conducted semi-structured interviews of ovarian cancer patients and survivors (n = 14) and healthcare providers (n = 11) between 10/2019 and 10/2021. Interviews focused on the time leading up to an ovarian cancer diagnosis. Thematic analysis was conducted by two independent reviewers using a two-phase deductive and inductive coding approach. Deductive coding used a priori time intervals from the validated Model of Pathways to Treatment (MPT), including self-appraisal and management of symptoms, medical help-seeking, diagnosis, and pre-treatment. Inductive coding identified common themes within each stage of the MPT across patient and provider interviews.

Results

The median age at ovarian cancer diagnosis was 61.5 years (range, 29–78 years), and the majority of participants (11/14) were diagnosed with advanced-stage disease. The median time from first symptom to initiation of treatment was 2.8 months (range, 19 days to 4.7 years). The appraisal and help-seeking intervals contributed the greatest delays in time-to-diagnosis for ovarian cancer. Nonspecific symptoms, perceptions of health and aging, avoidant coping strategies, symptom embarrassment, and concerns about potential judgment from providers prolonged the appraisal and help-seeking intervals. Patients and providers also emphasized access to care, including financial access, as critical to a timely diagnosis.

Conclusion

Interventions are urgently needed to reduce ovarian cancer morbidity and mortality. Population-level screening remains unlikely to improve ovarian cancer survival, but findings from our study suggest that developing interventions to improve self-appraisal of symptoms and reduce barriers to help-seeking could reduce time-to-diagnosis for ovarian cancer. Affordability of care and insurance may be particularly important for ovarian cancer patients diagnosed in the United States.

Abstract 736: Exploring the impact of infertility and its treatments on risk of ovarian cancer

Background: Infertility is related to both nulligravidity and endometriosis, which are both well-established risk factors for ovarian cancer. Infertility is also characterized by various underlying causes and can be treated with different types of fertility drugs. However, most studies to date have been unable to properly address these important issues when examining the infertility-ovarian cancer association due to small numbers of patients and a lack of detailed infertility and risk factor information.

Methods: We pooled self-reported data from 8,324 invasive, epithelial ovarian cancer cases and 13,325 control women in eight population-based case-control studies participating in the Ovarian Cancer Association Consortium (OCAC) to study the infertility-ovarian cancer relationship. Women classified as having a history of infertility were those who had spoken to a doctor about infertility problems or those who had regular sexual intercourse without birth control for a prolonged period (usually one year) without getting pregnant. Cause of infertility as well as use of fertility drugs was examined among those who experienced infertility issues. These associations with risk of ovarian cancer were evaluated using logistic regression models and quantified using odds ratios (ORs) and 95% confidence intervals (CIs). Gravidity and endometriosis were considered in the analyses as well as potential confounding factors.

Results: Overall, infertility was not associated with risk of ovarian cancer (OR=1.02, 95% CI 0.95-1.09). However, women who reported their infertility was due to problems with ovulation or menstruation showed a decreased risk (OR=0.72, 95% CI 0.52-1.01 and OR=0.62, 95% CI 0.43-0.91, respectively) whereas women who reported their infertility was due to endometriosis were at an increased risk (OR=1.54, 95% CI 1.19-1.98). Among women who reported infertility issues, use of fertility drugs was not associated with an increased risk of ovarian cancer regardless of their gravidity status (OR=0.89, 95% CI 0.76-1.05).

Conclusions: The relationship between infertility and risk of ovarian cancer is complex. Although infertility does not appear to be an independent risk factor for ovarian cancer, specific causes of infertility may be differentially associated with ovarian cancer risk, which may shed light on the disease’s underlying etiology. In addition, for women experiencing infertility issues, use of fertility drugs did not show an increased risk of ovarian cancer, which may have important clinical implications.

Citation Format: Alice W. Lee, Minh T. Phung, Allan Jensen, Anna H. Wu, Daniel W. Cramer, Francesmary Modugno, Holly Harris, Jennifer A. Doherty, Joellen Schildkraut, Kathryn L. Terry, Kirsten B. Moysich, Malcolm C. Pike, Marc T. Goodman, Penelope M. Webb, Susanne K. Kjaer, Celeste L. Pearce. Exploring the impact of infertility and its treatments on risk of ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 736.

Abstract 30: A pedigree-based approach to ovarian cancer risk variant discovery in the Utah Population Database

Introduction: Genetic risk variants are critical to risk prediction for invasive epithelial ovarian cancer (EOC), yet an estimated 50-55% of EOC heritability remains missing. Novel approaches to risk variant discovery are needed to detect variants that have not been uncovered by linkage analysis or genome-wide association studies (GWAS). We approach risk variant discovery using Shared Genomic Segment analysis (SGS), a novel statistical genetics method that enables risk variant discovery in extended high-risk pedigrees.

Methods: The Utah Population Database (UPDB) is a population-based resource of over ten million individuals connected to the state of Utah, five million of whom are linked to a minimum of three generations of genealogy data. By linking this genealogy data with cancer data from the Utah Cancer Registry, we identified pedigrees with an excess risk of EOC. We generated germline genotyping data from cases (diagnosed 1983-2018) in a subset of these high-risk pedigrees, focusing on pedigrees well-suited for SGS (i.e., at least 3 cases separated by a total of at least 12 meioses). SGS identifies all runs of consecutive alleles that are shared identical-by-state by cases in a pedigree and determines which of these genomic segments are longer than would be expected by chance. These long segments are likely to be identical-by-descent, inherited from a common founder, and may harbor risk variants.

Results: We successfully linked UPDB genealogy data to information from the Utah Cancer Registry to identify approximately 2,000 extended high-risk pedigrees with ≥5 ovarian cancer cases, an average of 7-10 meioses between pairs cases, and a statistically significant excess risk of ovarian cancer (α=0.05). We obtained biospecimens for 141 cases in 36 of the most promising pedigrees (i.e., high familial standardized incidence ratio, p-value&lt;0.005, not attributable to known risk variants in BRCA1 or BRCA2 as observed in first-, second- or third-degree relatives of EOC cases). We genotyped 96 out of the 141 cases in these pedigrees (68%). SGS analyses to identify genomic regions that may harbor risk variants are currently underway.

Conclusions: Using pedigrees identified in the UPBD, SGS has identified risk loci and novel risk variants for a number of diseases, including breast and hematologic cancers. We have identified a set of EOC high-risk pedigrees for SGS analysis and will leverage SGS to identify genomic regions that may harbor EOC risk variants.

Citation Format: Mollie E. Barnard, Robert Sargent, G. Bryce Christensen, Bonita A. Mahaffey, James Albro, Elke A. Jarboe, Terence Rhodes, Nicola J. Camp, Jennifer A. Doherty. A pedigree-based approach to ovarian cancer risk variant discovery in the Utah Population Database [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 30.

Multi-modal immune profiling of mucinous ovarian carcinoma: analysis from the Ovarian Tumor Tissue Analysis/Multidisciplinary Ovarian Cancer Outcomes Group consortia

Mucinous ovarian carcinoma (MOC) is a rare histotype of ovarian cancer. Women with advanced disease (FIGO stage III/IV) have very poor outcomes, with 5-year survival of &lt;20%. Little is known about the anti-tumor immune response in MOC, limiting potential immunotherapeutic options for patients.

Immune data from 3 platforms were analysed. A NanoString mRNA expression panel with 39 immune-related genes (n=60 MOC, n=4198 other ovarian histotypes), a NanoString mRNA plexset with PD-1, PD-L1 (n=241 MOC, n=115 upper and lower gastrointestinal (GI) cancers), and 2 multicolor immunofluorescence (mcIF) panels (n=121 MOC) for CD68, PD-L1, PD-1, CD8 and FOXP3. Data overlapped all platforms for 22 MOC. Immune marker expression by ovarian cancer histotype was measured. Uni- and multivariable Cox Proportional Hazards assessed overall survival (OS) within MOC. Hierarchical clustering looked for subgroups of patients based on co-expression of immune genes.

Compared to more common high-grade serous ovarian cancer (HGSC) and GI cancers, MOC were less immunologically active. High IGHM expression was associated with poorer OS (HR 1.31 (95% CI 1.02–1.69), p=0.033). High tumor densities of FOXP3 and PD-1 positive cells conferred poorer OS in a model with age, stage and site; however, these and PD-L1 and CD68 were associated with grade. The 39 gene NanoString and mcIF datasets revealed 4 clusters, roughly translating to immune cold, moderate and hot (groups 3,4). mcIF analysis revealed a subset with PD-L1 expression in the absence of T-regulatory cell infiltrates.

This study provides novel insights into the MOC immune landscape. Despite relatively low immune activity overall, immunotherapy could be explored for a subset of patients with MOC.

Supported by NSW Ministry of Health and UNSW Sydney, through the NSW Health PhD Scholarship Program 2017-2022; Translational Cancer Research Network top-up scholarship 2021

Validated biomarker assays confirm that ARID1A loss is confounded with MMR deficiency, CD8+ TIL infiltration, and provides no independent prognostic value in endometriosis-associated ovarian carcinomas

ARID1A (BAF250a) is a component of the SWI/SNF chromatin modifying complex, plays an important tumour suppressor role, and is considered prognostic in several malignancies. However, in ovarian carcinomas there are contradictory reports on its relationship to outcome, immune response, and correlation with clinicopathological features. We assembled a series of 1623 endometriosis-associated ovarian carcinomas, including 1078 endometrioid (ENOC) and 545 clear cell (CCOC) ovarian carcinomas, through combining resources of the Ovarian Tumor Tissue Analysis (OTTA) Consortium, the Canadian Ovarian Unified Experimental Resource (COEUR), local, and collaborative networks. Validated immunohistochemical surrogate assays for ARID1A mutations were applied to all samples. We investigated associations between ARID1A loss/mutation, clinical features, outcome, CD8+ tumour-infiltrating lymphocytes (CD8+ TILs), and DNA mismatch repair deficiency (MMRd). ARID1A loss was observed in 42% of CCOCs and 25% of ENOCs. We found no associations between ARID1A loss and outcomes, stage, age, or CD8+ TIL status in CCOC. Similarly, we found no association with outcome or stage in endometrioid cases. In ENOC, ARID1A loss was more prevalent in younger patients (p = 0.012) and was associated with MMRd (p < 0.001) and the presence of CD8+ TILs (p = 0.008). Consistent with MMRd being causative of ARID1A mutations, in a subset of ENOCs we also observed an association with ARID1A loss-of-function mutation as a result of small indels (p = 0.035, versus single nucleotide variants). In ENOC, the association with ARID1A loss, CD8+ TILs, and age appears confounded by MMRd status. Although this observation does not explicitly rule out a role for ARID1A influence on CD8+ TIL infiltration in ENOC, given current knowledge regarding MMRd, it seems more likely that effects are dominated by the hypermutation phenotype. This large dataset with consistently applied biomarker assessment now provides a benchmark for the prevalence of ARID1A loss-of-function mutations in endometriosis-associated ovarian cancers and brings clarity to the prognostic significance. © 2021 The Pathological Society of Great Britain and Ireland.

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.

High Prediagnosis Inflammation-Related Risk Score Associated with Decreased Ovarian Cancer Survival

BACKGROUND

There is suggestive evidence that inflammation is related to ovarian cancer survival. However, more research is needed to identify inflammation-related factors that are associated with ovarian cancer survival and to determine their combined effects.

METHODS

This analysis used pooled data on 8,147 women with invasive epithelial ovarian cancer from the Ovarian Cancer Association Consortium. The prediagnosis inflammation-related exposures of interest included alcohol use; aspirin use; other nonsteroidal anti-inflammatory drug use; body mass index; environmental tobacco smoke exposure; history of pelvic inflammatory disease, polycystic ovarian syndrome, and endometriosis; menopausal hormone therapy use; physical inactivity; smoking status; and talc use. Using Cox proportional hazards models, the relationship between each exposure and survival was assessed in 50% of the data. A weighted inflammation-related risk score (IRRS) was developed, and its association with survival was assessed using Cox proportional hazards models in the remaining 50% of the data.

RESULTS

There was a statistically significant trend of increasing risk of death per quartile of the IRRS [HR = 1.09; 95% confidence interval (CI), 1.03-1.14]. Women in the upper quartile of the IRRS had a 31% higher death rate compared with the lowest quartile (95% CI, 1.11-1.54).

CONCLUSIONS

A higher prediagnosis IRRS was associated with an increased mortality risk after an ovarian cancer diagnosis. Further investigation is warranted to evaluate whether postdiagnosis exposures are also associated with survival.

IMPACT

Given that pre- and postdiagnosis exposures are often correlated and many are modifiable, our study results can ultimately motivate the development of behavioral recommendations to enhance survival among patients with ovarian cancer.

Gene-gene interaction of AhRwith and within the Wntcascade affects susceptibility to lung cancer

BACKGROUND

Aberrant Wnt signalling, regulating cell development and stemness, influences the development of many cancer types. The Aryl hydrocarbon receptor (AhR) mediates tumorigenesis of environmental pollutants. Complex interaction patterns of genes assigned to AhR/Wnt-signalling were recently associated with lung cancer susceptibility.

AIM

To assess the association and predictive ability of AhR/Wnt-genes with lung cancer in cases and controls of European descent.

METHODS

Odds ratios (OR) were estimated for genomic variants assigned to the Wnt agonist and the antagonistic genes DKK2, DKK3, DKK4, FRZB, SFRP4 and Axin2. Logistic regression models with variable selection were trained, validated and tested to predict lung cancer, at which other previously identified SNPs that have been robustly associated with lung cancer risk could also enter the model. Furthermore, decision trees were created to investigate variant × variant interaction. All analyses were performed for overall lung cancer and for subgroups.

RESULTS

No genome-wide significant association of AhR/Wnt-genes with overall lung cancer was observed, but within the subgroups of ever smokers (e.g., maker rs2722278 SFRP4; OR  = 1.20; 95% CI 1.13-1.27; p  = 5.6 × 10-10) and never smokers (e.g., maker rs1133683 Axin2; OR  = 1.27; 95% CI 1.19-1.35; p  = 1.0 × 10-12). Although predictability is poor, AhR/Wnt-variants are unexpectedly overrepresented in optimized prediction scores for overall lung cancer and for small cell lung cancer. Remarkably, the score for never-smokers contained solely two AhR/Wnt-variants. The optimal decision tree for never smokers consists of 7 AhR/Wnt-variants and only two lung cancer variants.

CONCLUSIONS

The role of variants belonging to Wnt/AhR-pathways in lung cancer susceptibility may be underrated in main-effects association analysis. Complex interaction patterns in individuals of European descent have moderate predictive capacity for lung cancer or subgroups thereof, especially in never smokers.

Iam hiQ-a novel pair of accuracy indices for imputed genotypes

BACKGROUND

Imputation of untyped markers is a standard tool in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy with which genotypes are imputed is fundamental. Several accuracy measures have been proposed and some are implemented in imputation software, unfortunately diversely across platforms. In the present paper, we introduce Iam hiQ, an independent pair of accuracy measures that can be applied to dosage files, the output of all imputation software. Iam (imputation accuracy measure) quantifies the average amount of individual-specific versus population-specific genotype information in a linear manner. hiQ (heterogeneity in quantities of dosages) addresses the inter-individual heterogeneity between dosages of a marker across the sample at hand.

RESULTS

Applying both measures to a large case-control sample of the International Lung Cancer Consortium (ILCCO), comprising 27,065 individuals, we found meaningful thresholds for Iam and hiQ suitable to classify markers of poor accuracy. We demonstrate how Manhattan-like plots and moving averages of Iam and hiQ can be useful to identify regions enriched with less accurate imputed markers, whereas these regions would by missed when applying the accuracy measure info (implemented in IMPUTE2).

CONCLUSION

We recommend using Iam hiQ additional to other accuracy scores for variant filtering before stepping into the analysis of imputed GWAS data.

Improving Precision of Do Not Contact Codes: Results of a Manual Review to Inform Coding and Case Contact Procedures

Introduction

Central cancer registries are responsible for managing appropriate research contacts and record releases. Do not contact (DNC) flags are used by some registries to indicate patients who should not be contacted or included in research. Longitudinal changes in DNC coding practices and definitions may result in a lack of code standardization and inaccurately include or exclude individuals from research.

Purpose

We performed a comprehensive manual review of DNC cases in the Utah Cancer Registry to inform updates to standardization of DNC code definitions, and use of DNC codes for exclusion/inclusion in research.

Methods

We identified 858 cases with a current or prior DNC flag in the SEER Data Management System (SEER*DMS) or a research database, with cancers diagnosed from 1957-2021. We reviewed scanned images of correspondence with cases and physicians, incident forms, and comments in SEER*DMS and research databases. We evaluated whether there was evidence to support the current DNC code, a different DNC code, or insufficient evidence for any code.

Results

Of the 755 cases that had a current DNC flag and reason code in SEER*DMS, the distribution was as follows: 58%, Patient requested no contact; 20%, Physician denied; 13%, Patient is not aware they have cancer; 4%, Patient is mentally disabled [sic]; 4%, Other; and 1%, Unknown. In 5% of these cases, we found evidence supporting a different DNC reason code. Among cases included because of a prior DNC flag in SEER*DMS (n = 10) or a DNC flag in a research database (ie, cases with no current DNC flag or reason code in SEER*DMS, n = 93), we found evidence supporting the addition of a SEER*DMS DNC flag and reason code in 50% and 40% of cases, respectively. We identified DNC reason codes with outdated terminology (Patient is mentally disabled) and codes that may not accurately reflect patient research preferences (Physician denied without asking the patient). To address this, we identified new reason codes, retired old reason codes, and updated current reason code definitions and research handlings.

Conclusion

The time and resource investment in manual review allowed us to identify and, in most cases, resolve discordance in DNC flags and reason codes, adding reason codes when they were missing. This process was valuable because it informed recommended changes to DNC code definitions and research handlings that will ensure more appropriate inclusion and exclusion of cancer cases in research.

Pre-diagnosis neutrophil-to-lymphocyte ratio and mortality in individuals who develop lung cancer

Purpose

The neutrophil-to-lymphocyte ratio (NLR) is a marker of systemic inflammation that has been reported to be associated with survival after chronic disease diagnoses, including lung cancer. We hypothesized that the inflammatory profile reflected by pre-diagnosis NLR, rather than the well-studied pre-treatment NLR at diagnosis, may be associated with increased mortality after lung cancer is diagnosed in high-risk heavy smokers.

Methods

We examined associations between pre-diagnosis methylation-derived NLR (mdNLR) and lung cancer-specific and all-cause mortality in 279 non-small lung cancer (NSCLC) and 81 small cell lung cancer (SCLC) cases from the β-Carotene and Retinol Efficacy Trial (CARET). Cox proportional hazards models were adjusted for age, sex, smoking status, pack years, and time between blood draw and diagnosis, and stratified by stage of disease. Models were run separately by histotype.

Results

Among SCLC cases, those with pre-diagnosis mdNLR in the highest quartile had 2.5-fold increased mortality compared to those in the lowest quartile. For each unit increase in pre-diagnosis mdNLR, we observed 22–23% increased mortality (SCLC-specific hazard ratio [HR] = 1.23, 95% confidence interval [CI]: 1.02, 1.48; all-cause HR = 1.22, 95% CI 1.01, 1.46). SCLC associations were strongest for current smokers at blood draw (Interaction Ps = 0.03). Increasing mdNLR was not associated with mortality among NSCLC overall, nor within adenocarcinoma (N = 148) or squamous cell carcinoma (N = 115) case groups.

Conclusion

Our findings suggest that increased mdNLR, representing a systemic inflammatory profile on average 4.5 years before a SCLC diagnosis, may be associated with mortality in heavy smokers who go on to develop SCLC but not NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10552-021-01469-3.

Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer

Familial, sequencing, and genome-wide association studies (GWASs) and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWASs) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through application of a pleiotropy-guided conditional/conjunction false discovery rate (FDR) approach in the setting of a TWASs. This identified 14 candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were >1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. The 22 genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk.

Abstract 32: Body mass index and mammographic density by race and ethnicity

Background: Women with high breast density have a 4-6 fold increased risk of breast cancer compared to women with low breast density. There is a strong inverse association between body mass index (BMI) and breast density, so we hypothesized that some of the racial/ethnic variation in mammographic density may reflect differences in the prevalence of high BMI or the strength of the association between BMI and mammographic density by race/ethnicity.

Methods: We leveraged data from the Utah Population Database (UPDB) mammography cohort, including 140,200 non-Hispanic White (NHW) women, 703 non-Hispanic Black (NHB) women, 15,560 Hispanic women, 713 American Indian/Alaskan Native (AIAN) women, 2,525 Asian women, and 434 Native Hawaiian/Pacific Islander (NHPI) women with a screening mammogram obtained 2005-2019. We estimated the association between BMI and binary mammographic density (BI-RADS A & B versus C & D) using logistic regression adjusted for age, education, and parity in Utah. Menopausal status was not available, so we used age 55 as a proxy. We considered effect modification by running stratified analyses and conducting a likelihood ratio test of models with and without an interaction between BMI and race/ethnicity. We also calculated population attributable risks (PAR%).

Results: The prevalence of high BMI differed by race/ethnicity with the highest BMI among NHPI women (29.4% overweight and 52.2% obese) and lowest BMI among Asian women (17.9% overweight and 5.7% obese). Results from multivariable models were consistent with a strong inverse association between BMI and mammographic density (ORBMI&gt;30v≤25=0.21, 95% CI=0.21-0.22, p-trend &lt;0.001) that did not differ by race/ethnicity (p=0.07). There was also no evidence of heterogeneity by racial/ethnic group among women aged &lt;55 (p=0.15), but some evidence of heterogeneity among women ≥55 years (p=0.004). We jointly considered prevalence of high BMI and estimates of association between BMI and mammographic density by calculating PARs. For age &lt;55, after accounting for HT use, 26.7% (95% CI 26.3-27.2) of high mammographic density was explained by BMI ≤25. PARs were similar for NHW, Asian, and AIAN women, but lower for other groups, especially NHPI women (PAR%=9.8, 95% CI=6.4-13.3). For women age ≥55, 22.2% (95% CI 21.6-22.9) of high mammographic density was explained by BMI ≤25. PARs were similar for NHW, Hispanic, AIAN and NHPI women, and highest in NHB women (PAR%=42.2, 95% CI=35.9-48.5).

Discussion: We observed the strongest evidence of racial/ethnic differences in BMI when comparing the two groups most commonly studied together: Asians and NHPIs. While we present only limited evidence to suggest that BMI is differentially associated with breast density by race/ethnicity, differences in the prevalence of high BMI were substantial. Overall, our findings suggest that risk factor prevalence should not be overlooked when evaluating potential contributors to cancer disparities.

Citation Format: Mollie E. Barnard, Tarun Martheswaran, Karen Curtin, Jennifer A. Doherty. Body mass index and mammographic density by race and ethnicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 32.

Abstract 795: County-level radon and smoking exposure and lung cancer risk by histotype, sex, and race/ethnicity

Background: Radon and smoking synergistically increase risk of lung cancer, particularly for small cell and squamous cell carcinoma; however, associations by sex and race/ethnicity have not been reported.

Methods: We used data from the Behavioral Risk Factor Surveillance System (BRFSS), Environmental Protection Agency (EPA), and SEER21, excluding Alaska, to investigate the associations between county-level radon and smoking prevalence with lung cancer incidence by histotype, sex, and race/ethnicity (2006-2016). We only examined Non-Hispanic (NH) White and NH Black race/ethnicities due to the small proportion of cases from other groups. We used tertiles of sex-specific smoking prevalence estimates (1996-2000) from the BRFSS and EPA-defined radon zones of low, moderate, and high, to categorize 729 counties by both radon levels and smoking prevalence by sex. We fit generalized linear models using modified Poisson regression with Huber-White robust standard errors to compute rate ratios (RRs) and 95% confidence intervals (CIs) associating radon exposure, stratified by smoking tertile with histotype-specific lung cancer incidence.

Results: The smoking prevalence captured by each tertile was considerably lower for women (Low=9.0-22.4%, Moderate&gt;22.4-25.3, High&gt;25.3-36.6) than men (Low=14.4-27.3, Moderate&gt;27.3-31.6, High&gt;31.6-40.3). Among women, we observed the most pronounced associations between high radon and lung cancer risk compared to low radon within the highest female smoking tertile. These associations were evident among NH Black women, particularly for small cell carcinoma (RR=1.34, 95% CI: 1.05-1.71) and squamous cell carcinoma (RR=1.41, CI: 1.14-1.74), but were smaller and non-significant among NH White women. For men, the associations with radon were observed even in counties with low male smoking prevalence. For example, in counties in the lowest tertile of male smokers, associations of high radon with squamous cell and small cell lung cancer were observed among NH Black men (RR=1.27, 95% CI: 1.11-1.44, and RR=1.37, 95% CI:1.15-1.63, respectively) and NH White men (RR=1.18, 95% CI: 1.11-1.26, and RR=1.20, 95% CI: 1.11-1.29, respectively). When we considered that the percent of current smokers in the lowest smoking tertile for men overlaps the highest tertile for women, we observed radon-associated small cell and squamous cell lung cancer risk for NH Black men and women at comparable absolute smoking prevalence, and a similar but attenuated pattern in NH White men and women.

Discussion: While our analysis is limited by the ecological nature of the radon and smoking data, this research suggests that previously reported associations between radon and smoking exposure and histotype-specific lung cancer risk may differ by race and sex. Further research is needed to understand the impact of combined radon and smoking exposure on lung cancer risk in other racial and ethnic groups.

Citation Format: Rachel McCarty, Lindsay Collin, Laurie Grieshober, Judy Ou, Carol Sweeney, Mollie E. Barnard, Jennifer A. Doherty. County-level radon and smoking exposure and lung cancer risk by histotype, sex, and race/ethnicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 795.

Pregnancy outcomes and risk of endometrial cancer: A pooled analysis of individual participant data in the Epidemiology of Endometrial Cancer Consortium

A full-term pregnancy is associated with reduced endometrial cancer risk; however, whether the effect of additional pregnancies is independent of age at last pregnancy is unknown. The associations between other pregnancy-related factors and endometrial cancer risk are less clear. We pooled individual participant data from 11 cohort and 19 case-control studies participating in the Epidemiology of Endometrial Cancer Consortium (E2C2) including 16 986 women with endometrial cancer and 39 538 control women. We used one- and two-stage meta-analytic approaches to estimate pooled odds ratios (ORs) for the association between exposures and endometrial cancer risk. Ever having a full-term pregnancy was associated with a 41% reduction in risk of endometrial cancer compared to never having a full-term pregnancy (OR = 0.59, 95% confidence interval [CI] 0.56-0.63). The risk reduction appeared the greatest for the first full-term pregnancy (OR = 0.78, 95% CI 0.72-0.84), with a further ~15% reduction per pregnancy up to eight pregnancies (OR = 0.20, 95% CI 0.14-0.28) that was independent of age at last full-term pregnancy. Incomplete pregnancy was also associated with decreased endometrial cancer risk (7%-9% reduction per pregnancy). Twin births appeared to have the same effect as singleton pregnancies. Our pooled analysis shows that, while the magnitude of the risk reduction is greater for a full-term pregnancy than an incomplete pregnancy, each additional pregnancy is associated with further reduction in endometrial cancer risk, independent of age at last full-term pregnancy. These results suggest that the very high progesterone level in the last trimester of pregnancy is not the sole explanation for the protective effect of pregnancy.

Pathology Laboratory Policies and Procedures for Releasing Diagnostic Tissue for Cancer Research

CONTEXT.—

The Surveillance, Epidemiology, and End Results (SEER) cancer registry program is currently evaluating the use of archival, diagnostic, formalin-fixed, paraffin-embedded (FFPE) tissue obtained through SEER cancer registries, functioning as honest brokers for deidentified tissue and associated data. To determine the feasibility of this potential program, laboratory policies for sharing tissue for research needed to be assessed.

OBJECTIVE.—

To understand the willingness of pathology laboratories to share archival diagnostic tissue for cancer research and related policies.

DESIGN.—

Seven SEER registries administered a 27-item questionnaire to pathology laboratories within their respective registry catchment areas. Only laboratories that processed diagnostic FFPE specimens and completed the questionnaire were included in the analysis.

RESULTS.—

Of the 153 responding laboratories, 127 (83%) responded that they process FFPE specimens. Most (n = 88; 69%) were willing to share tissue specimens for research, which was not associated with the number of blocks processed per year by the laboratories. Most laboratories retained the specimens for at least 10 years. Institutional regulatory policies on sharing deidentified tissue varied considerably, ranging from requiring a full Institutional Review Board review to considering such use exempt from Institutional Review Board review, and 43% (55 of 127) of the laboratories did not know their terms for sharing tissue for research.

CONCLUSIONS.—

This project indicated a general willingness of pathology laboratories to participate in research by sharing FFPE tissue. Given the variability of research policies across laboratories, it is critical for each SEER registry to work with laboratories in their catchment area to understand such policies and state legislation regulating tissue retention and guardianship.

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.

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.

Determinants of telomere length across human tissues

Telomere shortening is a hallmark of aging. Telomere length (TL) in blood cells has been studied extensively as a biomarker of human aging and disease; however, little is known regarding variability in TL in nonblood, disease-relevant tissue types. Here, we characterize variability in TLs from 6391 tissue samples, representing >20 tissue types and 952 individuals from the Genotype-Tissue Expression (GTEx) project. We describe differences across tissue types, positive correlation among tissue types, and associations with age and ancestry. We show that genetic variation affects TL in multiple tissue types and that TL may mediate the effect of age on gene expression. Our results provide the foundational knowledge regarding TL in healthy tissues that is needed to interpret epidemiological studies of TL and human health.

Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE)

PURPOSE

Gene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features.

EXPERIMENTAL DESIGN

Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting.

RESULTS

Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations.

CONCLUSIONS

We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications.See related commentary by McMullen et al., p. 5271.

AHRR methylation in heavy smokers: associations with smoking, lung cancer risk, and lung cancer mortality

BACKGROUND

A low level of methylation at cg05575921 in the aryl-hydrocarbon receptor repressor (AHRR) gene is robustly associated with smoking, and some studies have observed associations between cg05575921 methylation and increased lung cancer risk and mortality. To prospectively examine whether decreased methylation at cg05575921 may identify high risk subpopulations for lung cancer screening among heavy smokers, and mortality in cases, we evaluated associations between cg05575921 methylation and lung cancer risk and mortality, by histotype, in heavy smokers.

METHODS

The β-Carotene and Retinol Efficacy Trial (CARET) included enrollees ages 45-69 with ≥ 20 pack-year smoking histories and/or occupational asbestos exposure. A subset of CARET participants had cg05575921 methylation available from HumanMethylationEPIC assays of blood collected on average 4.3 years prior to lung cancer diagnosis in cases. Cg05575921 methylation β-values were treated continuously for a 10% methylation decrease and as quintiles, where quintile 1 (Q1, referent) represents high methylation and Q5, low methylation. We used conditional logistic regression models to examine lung cancer risk overall and by histotype in a nested case-control study including 316 lung cancer cases (diagnosed through 2005) and 316 lung cancer-free controls matched on age (±5 years), sex, race/ethnicity, enrollment year, current/former smoking, asbestos exposure, and follow-up time. Mortality analyses included 372 lung cancer cases diagnosed between 1985 and 2013 with available methylation data. We used Cox proportional hazards models to examine mortality overall and by histotype.

RESULTS

Decreased cg05575921 methylation was strongly associated with smoking, even in our population of heavy smokers. We did not observe associations between decreased pre-diagnosis cg05575921 methylation and increased lung cancer risk, overall or by histotype. We observed linear increasing trends for lung cancer-specific mortality across decreasing cg05575921 methylation quintiles for adenocarcinoma and small cell carcinoma (P-trends = 0.01 and 0.04, respectively).

CONCLUSIONS

In our study of heavy smokers, decreased cg05575921 methylation was strongly associated with smoking but not increased lung cancer risk. The observed association between cg05575921 methylation and increased mortality in adenocarcinoma and small cell histotypes requires further examination. Our results do not support using decreased cg05575921 methylation as a biomarker for lung cancer screening risk stratification.

Abstract A20: AHRR hypomethylation in heavy smokers: Associations with lung cancer risk and mortality

Hypomethylation of cg05575921 in the aryl-hydrocarbon receptor repressor (AHRR) gene is consistently and strongly associated with higher exposure to smoking (e.g., current smoking, greater number of pack years, and less time since quitting). Although cg05575921 hypomethylation has been reported to be associated with lung cancer risk and mortality, this has not been explored within heavy smokers or by histotype. We assessed cg05575921 methylation for associations with smoking behavior, prospective lung cancer risk, and mortality in 313 cases and controls from the Beta Carotene and Retinol Efficacy Trial (CARET) with ≥20 pack years of smoking and matched on age (±5 years), sex, race/ethnicity, enrollment year, smoking status, occupational asbestos exposure, and follow-up time. Methylation of cg05575921 in blood collected on average 4.3 years prior to diagnosis in cases was assayed using the 850K Illumina EPIC array. Quintiles of cg05575921 methylation were defined based on the control distribution, with the lowest quintile (Q1, referent) representing hypermethylation and the highest (Q5), hypomethylation. Among controls, increasing quintiles of cg05575921 hypomethylation were associated with current smoking status (Cochran-Armitage trend p=3.0 × 10-21), and with decreasing years since last smoked, increasing cigarettes per day, and decreasing body mass index (BMI) (ordinal ANOVA p=3.1 × 10-21, 1.3 × 10-17, and 0.002, respectively). We observed similar patterns in cases. We evaluated associations between cg05575921 methylation and lung cancer risk using logistic regression models conditioned on matching factors and adjusted for age, years since quit, and BMI. We evaluated cg05575921 methylation and lung cancer-specific mortality using Cox proportional hazards models adjusted for stage, age, sex, race, smoking status, intervention arm, asbestos exposure, and pack years smoked. We did not observe clear patterns of associations between cg05575921 methylation and lung cancer risk overall or by histotype. However, we found a linear relationship (p=0.03) between increasing cg05575921 hypomethylation and overall lung cancer mortality, with Q5 vs Q1 Hazard Ratio (HR)=1.60 (95% Confidence Interval (95% CI): 1.00-2.57) for mortality from lung cancer overall, and HR=2.09, 95% CI: 0.96-4.54 for adenocarcinoma (N=121). Our findings provide preliminary support that even among heavy smokers, cg05575921 hypomethylation is associated with more recent and extensive exposure to cigarette smoking, and that prediagnosis cg05575921 hypomethylation in lung cancer cases is associated with an increased hazard of death. However, since the CARET population represents a group who would largely qualify for lung cancer screening with annual low-dose computed tomography per the United States Preventive Task Force guidelines, our results do not provide support for the use of cg05575921 hypomethylation as an indicator for screening-based lung cancer risk stratification.

Citation Format: Stefan Graw, Matt J. Barnett, Mark D. Thornquist, Gary E. Goodman, Chu Chen, Devin C. Koestler, Carmen J. Marsit, Jennifer A. Doherty, Laurie Grieshober. AHRR hypomethylation in heavy smokers: Associations with lung cancer risk and mortality [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 A20.

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.

Prognostic gene expression signature for high-grade serous ovarian cancer

BACKGROUND

Median overall survival (OS) for women with high-grade serous ovarian cancer (HGSOC) is ∼4 years, yet survival varies widely between patients. There are no well-established, gene expression signatures associated with prognosis. The aim of this study was to develop a robust prognostic signature for OS in patients with HGSOC.

PATIENTS AND METHODS

Expression of 513 genes, selected from a meta-analysis of 1455 tumours and other candidates, was measured using NanoString technology from formalin-fixed paraffin-embedded tumour tissue collected from 3769 women with HGSOC from multiple studies. Elastic net regularization for survival analysis was applied to develop a prognostic model for 5-year OS, trained on 2702 tumours from 15 studies and evaluated on an independent set of 1067 tumours from six studies.

RESULTS

Expression levels of 276 genes were associated with OS (false discovery rate < 0.05) in covariate-adjusted single-gene analyses. The top five genes were TAP1, ZFHX4, CXCL9, FBN1 and PTGER3 (P < 0.001). The best performing prognostic signature included 101 genes enriched in pathways with treatment implications. Each gain of one standard deviation in the gene expression score conferred a greater than twofold increase in risk of death [hazard ratio (HR) 2.35, 95% confidence interval (CI) 2.02-2.71; P < 0.001]. Median survival [HR (95% CI)] by gene expression score quintile was 9.5 (8.3 to -), 5.4 (4.6-7.0), 3.8 (3.3-4.6), 3.2 (2.9-3.7) and 2.3 (2.1-2.6) years.

CONCLUSION

The OTTA-SPOT (Ovarian Tumor Tissue Analysis consortium - Stratified Prognosis of Ovarian Tumours) gene expression signature may improve risk stratification in clinical trials by identifying patients who are least likely to achieve 5-year survival. The identified novel genes associated with the outcome may also yield opportunities for the development of targeted therapeutic approaches.

Abstract 3485: Body mass index and mammographic density among Native Hawaiians and Pacific Islanders

Background: Mammographic density is an important breast cancer risk factor, yet data on mammographic density is limited for some racial/ethnic groups, including Native Hawaiians and Pacific Islanders (NHPI). Obesity is highly prevalent in the NHPI population and prior work, primarily in non-Hispanic White (NHW) women, has reported that high body mass index (BMI) is inversely associated with mammographic density but positively associated with risk of breast cancer. We used data from the Utah Population Database (UPDB) to estimate the association between BMI and mammographic density in Utah's NHPI population and evaluate if the association differs for NHPI women compared to NHW women.

Methods: We included women ages 18-79 years with at least one mammogram from 2005-2012 and no history of breast cancer. Data on BMI and race/ethnicity were collected from the UPDB, and mammographic density was evaluated using Breast Imaging Reporting and Data System (BIRADS) scores. We estimated the association between BMI and BIRADS using multinomial logistic regression adjusted for age and stratified at age 55 (a proxy for menopausal status). Heterogeneity by race/ethnicity was evaluated using likelihood ratio tests.

Results: Our analyses included data from 102 Native Hawaiian, 112 Samoan, 344 other Pacific Islander, and 143,259 NHW women. High mammographic density (BIRADS=4) was less common among Samoan women (2.7%) and other Pacific Islanders (4.7%) compared to NHW women (5.8%), but more common among Native Hawaiians (11.8%). Age-standardized BMI was highest in Samoan women (mean=32.3, SD=6.3) followed by other Pacific Islander women (mean=31.2, SD=7.1) then Native Hawaiian women (mean=27.8, SD=6.4), and lowest among NHW women (mean=26.1, SD=5.4). Among women younger than age 55, a one-unit increase in BMI was associated with 0.76 (95% CI=0.69-0.84) times lower odds of high (BIRADS=4) versus low (BIRADS=1) breast density in NHPI women. The comparable odds ratio (OR) in NHW women was 0.66 (95% CI=0.65-0.66; p-heterogeneity=6.9 × 10^-10). For women age 55 and older, the association between BMI and mammographic density was stronger among NHPI women, OR=0.62 (95%CI=0.45-0.84), compared to NHW women, OR=0.70 (95%CI=0.69-0.72; p-heterogeneity=0.018).

Discussion: Mammographic density differs among racial/ethnic subgroups of the NHPI population with Native Hawaiians having the highest mammographic density. Given the high prevalence of obesity in the NHPI population and evidence that the association between BMI and mammographic density may differ by race/ethnicity, more research is needed to understand how BMI and mammographic density influence risk of breast cancer in understudied racial/ethnic minorities, such as NHPIs.

Citation Format: Mollie E. Barnard, Tarun Martheswaran, Jennifer A. Doherty, Karen Curtin. Body mass index and mammographic density among Native Hawaiians and Pacific Islanders [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 3485.