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

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

Exome sequencing identifies HELB as a novel susceptibility gene for non-mucinous, non-high-grade-serous epithelial ovarian cancer.

Rare, germline loss-of-function variants in a handful of genes that encode DNA repair proteins have been shown to be associated with epithelial ovarian cancer with a stronger association for the high-grade serous hiostotype. The aim of this study was to collate exome sequencing data from multiple epithelial ovarian cancer case cohorts and controls in order to systematically evaluate the role of coding, loss-of-function variants across the genome in epithelial ovarian cancer risk. We assembled exome data for a total of 2,573 non-mucinous cases (1,876 high-grade serous and 697 non-high grade serous) and 13,925 controls. Harmonised variant calling and quality control filtering was applied across the different data sets. We carried out a gene-by-gene simple burden test for association of rare loss-of-function variants (minor allele frequency < 0.1%) with all non-mucinous ovarian cancer, high grade serous ovarian cancer and non-high grade serous ovarian cancer using logistic regression adjusted for the top four principal components to account for cryptic population structure and genetic ancestry. Seven of the top 10 associated genes were associations of the known ovarian cancer susceptibility genes BRCA1, BRCA2, BRIP1, RAD51C, RAD51D, MSH6 and PALB2 (false discovery probability < 0.1). A further four genes (HELB, OR2T35, NBN and MYO1A) had a false discovery rate of less than 0.1. Of these, HELB was most strongly associated with the non-high grade serous histotype (P = 1.3×10-6, FDR = 9.1×10-4). Further support for this association comes from the observation that loss of function variants in this gene are also associated with age at natural menopause and Mendelian randomisation analysis shows an association between genetically predicted age at natural menopause and endometrioid ovarian cancer, but not high-grade serous ovarian cancer.

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

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

Risk Factors for Ovarian Cancer by BRCA Status: A Collaborative Case-Only Analysis.

BACKGROUND: Women with an inherited pathogenic variant in BRCA1 or BRCA2 have a greatly increased risk of developing ovarian cancer, but the importance of behavioral factors is less clear. We used a case-only design to compare the magnitude of associations with established reproductive, hormonal, and lifestyle risk factors between BRCA mutation carriers and noncarriers. METHODS: We pooled data from five studies from the Ovarian Cancer Association Consortium including 637 BRCA carriers and 4,289 noncarriers. Covariate-adjusted generalized linear mixed models were used to estimate interaction risk ratios (IRR) and 95% confidence intervals (CI), with BRCA (carrier vs. noncarrier) as the response variable. RESULTS: IRRs were above 1.0 for known protective factors including ever being pregnant (IRR = 1.29, 95% CI; 1.00-1.67) and ever using the oral contraceptive pill (1.30, 95% CI; 1.07-1.60), suggesting the protective effects of these factors may be reduced in carriers compared with noncarriers. Conversely, the IRRs for risk factors including endometriosis and menopausal hormone therapy were below 1.0, suggesting weaker positive associations among BRCA carriers. In contrast, associations with lifestyle factors including smoking, physical inactivity, body mass index, and aspirin use did not appear to differ by BRCA status. CONCLUSIONS: Our results suggest that associations with hormonal and reproductive factors are generally weaker for those with a pathogenic BRCA variant than those without, while associations with modifiable lifestyle factors are similar for carriers and noncarriers. IMPACT: Advice to maintain a healthy weight, be physically active, and refrain from smoking will therefore benefit BRCA carriers as well as noncarriers.

Leveraging GWAS: Path to Prevention?

Developing novel cancer prevention medication strategies is important for reducing mortality. Identification of common genetic variants associated with cancer risk suggests the potential to leverage these discoveries to define causal targets for cancer interception. Although each risk variant confers small increases in risk, researchers propose that blocking those that produce causal carcinogenic effects might have large impacts on cancer prevention. While a promising concept, we describe potential hurdles that may need to be scaled to reach this goal, including: (i) understanding the complexity of risk; (ii) achieving statistical power in studies with binary outcomes (cancer development: yes or no); (iii) characterization of cancer precursors; (iv) heterogeneity of cancer subtypes and the populations in which these diseases occur; (v) impact of static genetic markers across complex events of the life course; (vi) defining gene-gene and gene-environment interactions and (vii) demonstrating functional effects of markers in human populations. We assess short-term prospects for this research against the backdrop of these challenges and the potential to prevent cancer through other means. See related commentary by Peters and Tomlinson, p. 7.

Benign Breast Disease and Breast Cancer Risk in the Percutaneous Biopsy Era.

Importance: Benign breast disease (BBD) comprises approximately 75% of breast biopsy diagnoses. Surgical biopsy specimens diagnosed as nonproliferative (NP), proliferative disease without atypia (PDWA), or atypical hyperplasia (AH) are associated with increasing breast cancer (BC) risk; however, knowledge is limited on risk associated with percutaneously diagnosed BBD. Objectives: To estimate BC risk associated with BBD in the percutaneous biopsy era irrespective of surgical biopsy. Design, Setting, and Participants: In this retrospective cohort study, BBD biopsy specimens collected from January 1, 2002, to December 31, 2013, from patients with BBD at Mayo Clinic in Rochester, Minnesota, were reviewed by 2 pathologists masked to outcomes. Women were followed up from 6 months after biopsy until censoring, BC diagnosis, or December 31, 2021. Exposure: Benign breast disease classification and multiplicity by pathology panel review. Main Outcomes: The main outcome was diagnosis of BC overall and stratified as ductal carcinoma in situ (DCIS) or invasive BC. Risk for presence vs absence of BBD lesions was assessed by Cox proportional hazards regression. Risk in patients with BBD compared with female breast cancer incidence rates from the Iowa Surveillance, Epidemiology, and End Results (SEER) program were estimated. Results: Among 4819 female participants, median age was 51 years (IQR, 43-62 years). Median follow-up was 10.9 years (IQR, 7.7-14.2 years) for control individuals without BC vs 6.6 years (IQR, 3.7-10.1 years) for patients with BC. Risk was higher in the cohort with BBD than in SEER data: BC overall (standard incidence ratio [SIR], 1.95; 95% CI, 1.76-2.17), invasive BC (SIR, 1.56; 95% CI, 1.37-1.78), and DCIS (SIR, 3.10; 95% CI, 2.54-3.77). The SIRs increased with increasing BBD severity (1.42 [95% CI, 1.19-1.71] for NP, 2.19 [95% CI, 1.88-2.54] for PDWA, and 3.91 [95% CI, 2.97-5.14] for AH), comparable to surgical cohorts with BBD. Risk also increased with increasing lesion multiplicity (SIR: 2.40 [95% CI, 2.06-2.79] for ≥3 foci of NP, 3.72 [95% CI, 2.31-5.99] for ≥3 foci of PDWA, and 5.29 [95% CI, 3.37-8.29] for ≥3 foci of AH). Ten-year BC cumulative incidence was 4.3% for NP, 6.6% for PDWA, and 14.6% for AH vs an expected population cumulative incidence of 2.9%. Conclusions and Relevance: In this contemporary cohort study of women diagnosed with BBD in the percutaneous biopsy era, overall risk of BC was increased vs the general population (DCIS and invasive cancer combined), similar to that in historical BBD cohorts. Development and validation of pathologic classifications including both BBD severity and multiplicity may enable improved BC risk stratification.

Impact of Artificial Intelligence System and Volumetric Density on Risk Prediction of Interval, Screen-Detected, and Advanced Breast Cancer.

PURPOSE: Artificial intelligence (AI) algorithms improve breast cancer detection on mammography, but their contribution to long-term risk prediction for advanced and interval cancers is unknown. METHODS: We identified 2,412 women with invasive breast cancer and 4,995 controls matched on age, race, and date of mammogram, from two US mammography cohorts, who had two-dimensional full-field digital mammograms performed 2-5.5 years before cancer diagnosis. We assessed Breast Imaging Reporting and Data System density, an AI malignancy score (1-10), and volumetric density measures. We used conditional logistic regression to estimate odds ratios (ORs), 95% CIs, adjusted for age and BMI, and C-statistics (AUC) to describe the association of AI score with invasive cancer and its contribution to models with breast density measures. Likelihood ratio tests (LRTs) and bootstrapping methods were used to compare model performance. RESULTS: On mammograms between 2-5.5 years prior to cancer, a one unit increase in AI score was associated with 20% greater odds of invasive breast cancer (OR, 1.20; 95% CI, 1.17 to 1.22; AUC, 0.63; 95% CI, 0.62 to 0.64) and was similarly predictive of interval (OR, 1.20; 95% CI, 1.13 to 1.27; AUC, 0.63) and advanced cancers (OR, 1.23; 95% CI, 1.16 to 1.31; AUC, 0.64) and in dense (OR, 1.18; 95% CI, 1.15 to 1.22; AUC, 0.66) breasts. AI score improved prediction of all cancer types in models with density measures (PLRT values < .001); discrimination improved for advanced cancer (ie, AUC for dense volume increased from 0.624 to 0.679, Δ AUC 0.065, P = .01) but did not reach statistical significance for interval cancer. CONCLUSION: AI imaging algorithms coupled with breast density independently contribute to long-term risk prediction of invasive breast cancers, in particular, advanced cancer.

Pharmacotherapy exposure as a marker of disease complexity in bipolar disorder: Associations with clinical & genetic risk factors.

Individuals with bipolar disorder (BD) require chronic pharmacotherapy, typically including medication switches or polypharmacy due to persisting symptoms or intolerable side effects. Here, we quantified pharmacotherapy exposure (PE) of Mayo Clinic BD Biobank participants using the number of cross-sectional (at enrollment) and lifetime BD-specific medications and medication classes, to understand the relationship between PE and markers of disease severity or treatment failure, psychiatric comorbidities, and polygenic risk scores (PRS) for six major psychiatric disorders. Being female (p < 0.05), older (p < 0.01), having history of suicide attempts (p < 0.0001), and comorbid attention-deficit/hyperactivity disorder (p < 0.05) or generalized anxiety disorder (p < 0.05) were uniformly associated with higher PE. Lifetime exposure to unique medication classes among participants with BD-I was significantly lower than for those with schizoaffective disorder (estimate = -2.1, p < 0.0001) while significantly higher than for those with BD-II (estimate = 0.5, p < 0.01). Further, higher PRS for schizophrenia (SCZ) and anxiety resulted in greater lifetime medication counts (p < 0.01), both driven by antipsychotic (p < 0.001) and anxiolytic use (p < 0.05). Our results provide initial evidence of the utility of PE as a measure of disease complexity or treatment resistance, and that PE may be predicted by higher genetic risk for SCZ and anxiety.

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.

Benign Breast Disease, NSAIDs, and Postmenopausal Breast Cancer Risk in the CPS-II Cohort.

ABSTRACT: Nonsteroidal anti-inflammatory agents (NSAID) are associated with modest inconsistent reductions in breast cancer risk in population-based cohorts, whereas two focused studies of patients with benign breast disease (BBD) have found lower risk with NSAID use. Given that BBD includes fibroinflammatory lesions linked to elevated breast cancer risk, we assessed whether NSAID use was associated with lower breast cancer risk among patients with BBD.Participants were postmenopausal women in the Cancer Prevention Study-II (CPS-II), a prospective study of cancer incidence and mortality, who completed follow-up surveys in 1997 with follow-up through June 30, 2015. History of BBD, NSAID use, and covariate data were updated biennially. This analysis included 23,615 patients with BBD and 36,751 patients with non-BBD, including 3,896 incident breast cancers over an average of 12.72 years of follow-up among participants. NSAID use, overall and by formulation, recency, duration, and pills per month was analyzed versus breast cancer risk overall and by BBD status using multivariable-adjusted Cox models; BBD status and NSAID use were modeled as time-dependent exposures.Patients with BBD who reported using NSAIDs experienced lower breast cancer risk (HR, 0.87; 95% CI, 0.78-0.97), with similar effects for estrogen receptor (ER)-positive breast cancers [HR, 0.85; 95% confidence interval (CI), 0.74-0.97] and ER-negative breast cancers (HR, 0.87; 95% CI, 0.59-1.29); among women without BBD, NSAID use was unrelated to risk (HR, 1.02; 95% CI, 0.92-1.13; Pinteraction = 0.04). Associations stratified by age, obesity, menopausal hormone use, and cardiovascular disease were similar.Among patients with BBD, NSAID use appears linked to lower breast cancer risk. Further studies to assess the value of NSAID use among patients with BBD are warranted. PREVENTION RELEVANCE: We examined whether NSAID use, a modifiable exposure, is associated with breast cancer risk in postmenopausal women from the Cancer Prevention Study-II with self-reported benign breast disease, an often inflammatory condition associated with higher rates of breast cancer.

Associations of sex-related steroid hormones and proteins with alcohol dependence: A United Kingdom Biobank study.

BACKGROUND: Sex-related steroid hormones and proteins may contribute to the sex differences in the characteristics and health consequences of alcohol use disorder. This study aimed to examine the associations between alcohol dependence (AD) and sex-related hormones/proteins using a population-based dataset. METHODS: We retrieved serum total testosterone (TT) and estradiol (TE2), sex hormone binding globulin (SHBG), and albumin levels along with clinical data from the UK Biobank. Hormone/protein levels were compared between AD (lifetime AD and/or related diagnoses; 2218 males; 682 females) and control (no aforementioned diagnoses and AUDIT<8; 198,058 males; 250,830 females) groups with sex-dependent linear regression models adjusting for age and body mass index. Moderation and mediation analyses were performed to test whether SHBG was a moderator and/or mediator between hormones and AD or current drinking. RESULTS: AD males had higher TT, TE2, and SHBG levels but lower bioavailable testosterone, bioavailable estradiol, and albumin levels than controls (padjusted<0.001). After adjusting for menopause, AD females had higher TT and lower albumin levels than controls (padjusted<0.001). These differences remained after accounting for current drinking frequency (p < 0.001). SHBG moderated TT's effect on AD in males (pinteraction<0.001). SHBG was a positive mediator between TT and AD in both sexes and between TE2 and AD in males (p < 0.001), but a negative mediator between TT and current drinking in controls (both sexes) and AD males (p < 0.001). CONCLUSIONS: Testosterone and estradiol levels are altered in males and females with AD distinctly regardless of current drinking frequency. SHBG may play a critical role in these associations.

Immune cells are increased in normal breast tissues of BRCA1/2 mutation carriers.

PURPOSE: Breast cancer risk is elevated in pathogenic germline BRCA 1/2 mutation carriers due to compromised DNA quality control. We hypothesized that if immunosurveillance promotes tumor suppression, then normal/benign breast lobules from BRCA carriers may demonstrate higher immune cell densities. METHODS: We assessed immune cell composition in normal/benign breast lobules from age-matched women with progressively increased breast cancer risk, including (1) low risk: 19 women who donated normal breast tissue to the Komen Tissue Bank (KTB) at Indiana University Simon Cancer Center, (2) intermediate risk: 15 women with biopsy-identified benign breast disease (BBD), and (3) high risk: 19 prophylactic mastectomies from women with germline mutations in BRCA1/2 genes. We performed immunohistochemical stains and analysis to quantitate immune cell densities from digital images in up to 10 representative lobules per sample. Median cell counts per mm2 were compared between groups using Wilcoxon rank-sum tests. RESULTS: Normal/benign breast lobules from BRCA carriers had significantly higher densities of immune cells/mm2 compared to KTB normal donors (all p < 0.001): CD8 + 354.4 vs 150.9; CD4 + 116.3 vs 17.7; CD68 + 237.5 vs 57.8; and CD11c + (3.5% vs 0.4% pixels positive). BBD tissues differed from BRCA carriers only in CD8 + cells but had higher densities of CD4 + , CD11c + , and CD68 + immune cells compared to KTB donors. CONCLUSIONS: These preliminary analyses show that normal/benign breast lobules of BRCA mutation carriers contain increased immune cells compared with normal donor breast tissues, and BBD tissues appear overall more similar to BRCA carriers.

The genomic and immune landscape of long-term survivors of high-grade serous ovarian cancer.

Fewer than half of all patients with advanced-stage high-grade serous ovarian cancers (HGSCs) survive more than five years after diagnosis, but those who have an exceptionally long survival could provide insights into tumor biology and therapeutic approaches. We analyzed 60 patients with advanced-stage HGSC who survived more than 10 years after diagnosis using whole-genome sequencing, transcriptome and methylome profiling of their primary tumor samples, comparing this data to 66 short- or moderate-term survivors. Tumors of long-term survivors were more likely to have multiple alterations in genes associated with DNA repair and more frequent somatic variants resulting in an increased predicted neoantigen load. Patients clustered into survival groups based on genomic and immune cell signatures, including three subsets of patients with BRCA1 alterations with distinctly different outcomes. Specific combinations of germline and somatic gene alterations, tumor cell phenotypes and differential immune responses appear to contribute to long-term survival in HGSC.

A genome-wide association study of mammographic texture variation.

BACKGROUND: Breast parenchymal texture features, including grayscale variation (V), capture the patterns of texture variation on a mammogram and are associated with breast cancer risk, independent of mammographic density (MD). However, our knowledge on the genetic basis of these texture features is limited. METHODS: We conducted a genome-wide association study of V in 7040 European-ancestry women. V assessments were generated from digitized film mammograms. We used linear regression to test the single-nucleotide polymorphism (SNP)-phenotype associations adjusting for age, body mass index (BMI), MD phenotypes, and the top four genetic principal components. We further calculated genetic correlations and performed SNP-set tests of V with MD, breast cancer risk, and other breast cancer risk factors. RESULTS: We identified three genome-wide significant loci associated with V: rs138141444 (6q24.1) in ECT2L, rs79670367 (8q24.22) in LINC01591, and rs113174754 (12q22) near PGAM1P5. 6q24.1 and 8q24.22 have not previously been associated with MD phenotypes or breast cancer risk, while 12q22 is a known locus for both MD and breast cancer risk. Among known MD and breast cancer risk SNPs, we identified four variants that were associated with V at the Bonferroni-corrected thresholds accounting for the number of SNPs tested: rs335189 (5q23.2) in PRDM6, rs13256025 (8p21.2) in EBF2, rs11836164 (12p12.1) near SSPN, and rs17817449 (16q12.2) in FTO. We observed significant genetic correlations between V and mammographic dense area (rg = 0.79, P = 5.91 × 10-5), percent density (rg = 0.73, P = 1.00 × 10-4), and adult BMI (rg = - 0.36, P = 3.88 × 10-7). Additional significant relationships were observed for non-dense area (z = - 4.14, P = 3.42 × 10-5), estrogen receptor-positive breast cancer (z = 3.41, P = 6.41 × 10-4), and childhood body fatness (z = - 4.91, P = 9.05 × 10-7) from the SNP-set tests. CONCLUSIONS: These findings provide new insights into the genetic basis of mammographic texture variation and their associations with MD, breast cancer risk, and other breast cancer risk factors.

A genome-wide gene-based gene-environment interaction study of breast cancer in more than 90,000 women.

Background: Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene-environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. Methods: We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P<0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. Results: After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE=4.44×10-6). Conclusion: In this transcriptome-informed genome-wide gene-environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Impact: Our study suggests a limited role of gene-environment interactions in breast cancer risk.

Computational tumor stroma reaction evaluation led to novel prognosis-associated fibrosis and molecular signature discoveries in high-grade serous ovarian carcinoma.

Background: As one of the key criteria to differentiate benign vs. malignant tumors in ovarian and other solid cancers, tumor-stroma reaction (TSR) is long observed by pathologists and has been found correlated with patient prognosis. However, paucity of study aims to overcome subjective bias or automate TSR evaluation for enabling association analysis to a large cohort. Materials and methods: Serving as positive and negative sets of TSR studies, H&E slides of primary tumors of high-grade serous ovarian carcinoma (HGSOC) (n = 291) and serous borderline ovarian tumor (SBOT) (n = 15) were digitally scanned. Three pathologist-defined quantification criteria were used to characterize the extents of TSR. Scores for each criterion were annotated (0/1/2 as none-low/intermediate/high) in the training set consisting of 18,265 H&E patches. Serial of deep learning (DL) models were trained to identify tumor vs. stroma regions and predict TSR scores. After cross-validation and independent validations, the trained models were generalized to the entire HGSOC cohort and correlated with clinical characteristics. In a subset of cases tumor transcriptomes were available, gene- and pathway-level association studies were conducted with TSR scores. Results: The trained models accurately identified the tumor stroma tissue regions and predicted TSR scores. Within tumor stroma interface region, TSR fibrosis scores were strongly associated with patient prognosis. Cancer signaling aberrations associated 14 KEGG pathways were also found positively correlated with TSR-fibrosis score. Conclusion: With the aid of DL, TSR evaluation could be generalized to large cohort to enable prognostic association analysis and facilitate discovering novel gene and pathways associated with disease progress.

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

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

Molecular Subclasses of Clear Cell Ovarian Carcinoma and Their Impact on Disease Behavior and Outcomes.

PURPOSE: To identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes. EXPERIMENTAL DESIGN: We profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival. RESULTS: We detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy. CONCLUSIONS: Our study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838.

Towards defining morphologic parameters of normal parous and nulliparous breast tissues by artificial intelligence.

BACKGROUND: Breast terminal duct lobular units (TDLUs), the source of most breast cancer (BC) precursors, are shaped by age-related involution, a gradual process, and postpartum involution (PPI), a dramatic inflammatory process that restores baseline microanatomy after weaning. Dysregulated PPI is implicated in the pathogenesis of postpartum BCs. We propose that assessment of TDLUs in the postpartum period may have value in risk estimation, but characteristics of these tissues in relation to epidemiological factors are incompletely described. METHODS: Using validated Artificial Intelligence and morphometric methods, we analyzed digitized images of tissue sections of normal breast tissues stained with hematoxylin and eosin from donors ≤ 45 years from the Komen Tissue Bank (180 parous and 545 nulliparous). Metrics assessed by AI, included: TDLU count; adipose tissue fraction; mean acini count/TDLU; mean dilated acini; mean average acini area; mean "capillary" area; mean epithelial area; mean ratio of epithelial area versus intralobular stroma; mean mononuclear cell count (surrogate of immune cells); mean fat area proximate to TDLUs and TDLU area. We compared epidemiologic characteristics collected via questionnaire by parity status and race, using a Wilcoxon rank sum test or Fisher's exact test. Histologic features were compared between nulliparous and parous women (overall and by time between last birth and donation [recent birth: ≤ 5 years versus remote birth: > 5 years]) using multivariable regression models. RESULTS: Normal breast tissues of parous women contained significantly higher TDLU counts and acini counts, more frequent dilated acini, higher mononuclear cell counts in TDLUs and smaller acini area per TDLU than nulliparas (all multivariable analyses p < 0.001). Differences in TDLU counts and average acini size persisted for > 5 years postpartum, whereas increases in immune cells were most marked ≤ 5 years of a birth. Relationships were suggestively modified by several other factors, including demographic and reproductive characteristics, ethanol consumption and breastfeeding duration. CONCLUSIONS: Our study identified sustained expansion of TDLU numbers and reduced average acini area among parous versus nulliparous women and notable increases in immune responses within five years following childbirth. Further, we show that quantitative characteristics of normal breast samples vary with demographic features and BC risk factors.

Serum hormone levels and normal breast histology among premenopausal women.

PURPOSE: Breast terminal duct lobular units (TDLUs) are the main source of breast cancer (BC) precursors. Higher serum concentrations of hormones and growth factors have been linked to increased TDLU numbers and to elevated BC risk, with variable effects by menopausal status. We assessed associations of circulating factors with breast histology among premenopausal women using artificial intelligence (AI) and preliminarily tested whether parity modifies associations. METHODS: Pathology AI analysis was performed on 316 digital images of H&E-stained sections of normal breast tissues from Komen Tissue Bank donors ages ≤ 45 years to assess 11 quantitative metrics. Associations of circulating factors with AI metrics were assessed using regression analyses, with inclusion of interaction terms to assess effect modification. RESULTS: Higher prolactin levels were related to larger TDLU area (p < 0.001) and increased presence of adipose tissue proximate to TDLUs (p < 0.001), with less significant positive associations for acini counts (p = 0.012), dilated acini (p = 0.043), capillary area (p = 0.014), epithelial area (p = 0.007), and mononuclear cell counts (p = 0.017). Testosterone levels were associated with increased TDLU counts (p < 0.001), irrespective of parity, but associations differed by adipose tissue content. AI data for TDLU counts generally agreed with prior visual assessments. CONCLUSION: Among premenopausal women, serum hormone levels linked to BC risk were also associated with quantitative features of normal breast tissue. These relationships were suggestively modified by parity status and tissue composition. We conclude that the microanatomic features of normal breast tissue may represent a marker of BC risk.