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.

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.

Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk

Background

Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS).

Methods

We analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank Japan.

Results

Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding that TP53 3'-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76×10-9). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62).

Conclusions

This study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC.

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.

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.

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.

Age-Dependent Sex Differences in the Prevalence of Selective Serotonin Reuptake Inhibitor Treatment: A Retrospective Cohort Analysis

Background: Antidepressants are among the most prescribed medications in the United States. The aim of this study was to explore the prevalence of antidepressant prescriptions and investigate sex differences and age-sex interactions in adults enrolled in the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT) study. Materials and Methods: We conducted a retrospective analysis of the RIGHT study. Using electronic prescriptions, we assessed 12-month prevalence of antidepressant treatment. Sex differences and age-sex interactions were evaluated using multivariable logistic regression and flexible recursive smoothing splines. Results: The sample consisted of 11,087 participants (60% women). Antidepressant prescription prevalence was 22.24% (27.96% women, 13.58% men). After adjusting for age and enrollment year, women had significantly greater odds of antidepressant prescription (odds ratio = 2.29; 95% confidence interval = 2.07, 2.54). Furthermore, selective serotonin reuptake inhibitors (SSRIs) had a significant age-sex interaction. While SSRI prescriptions in men showed a sustained decrease with age, there was no such decline for women until after reaching ∼50 years of age. There are important limitations to consider in this study. Electronic prescription data were cross-sectional; information on treatment duration or adherence was not collected; this cohort is not nationally representative; and enrollment occurred over a broad period, introducing confounding by changes in temporal prescribing practices. Conclusions: Underscored by the significant interaction between age and sex on odds of SSRI prescription, our results warrant age to be incorporated as a mediator when investigating sex differences in mental illness, especially mood disorders and their treatment.

Long-term effects of premenopausal bilateral oophorectomy with or without hysterectomy on physical aging and chronic medical conditions

OBJECTIVE

We examined the long-term effects of premenopausal bilateral oophorectomy (PBO) with or without concurrent or preceding hysterectomy on physical and cognitive function and on odds of chronic conditions.

METHODS

We enrolled 274 women with PBO with or without concurrent or preceding hysterectomy and 240 referents aged 55 years and older who were residents of Olmsted County, MN as of the PBO or index date. Chronic conditions were assessed via medical record abstraction. Cognitive diagnoses were based on neurocognitive testing. A physical function assessment included measures of strength and mobility. Multivariable regression models compared characteristics for women with PBO <46 years, PBO 46-49 years, and referent women with adjustments for age and other confounders.

RESULTS

The clinical visits (median age, 67 years) were a median of 22 years after the PBO or index date. Of 274 women with PBO, 161 (59%) were <46 years at PBO and 113 (41%) were 46-49 years. Compared with referents, women with a history of PBO <46 years had increased odds of arthritis (odds ratio [OR], 1.64; 95% confidence interval [CI], 1.06-2.55), asthma (OR, 1.74; 95% CI, 1.03-2.93), obstructive sleep apnea (OR, 2.00; 95% CI, 1.23-3.26), and bone fractures (OR, 2.86; 95% CI, 1.17-6.98), and walked a shorter mean distance on a 6-minute walk test ( b = -18.43; P = 0.034). Compared with referents, women with a history of PBO at age 46-49 years had increased odds of arthritis (OR, 1.92; 95% CI, 1.16-3.18) and obstructive sleep apnea (OR, 2.21; 95% CI, 1.33-3.66). There were no significant differences in cognitive status in women with PBO compared with referents.

CONCLUSIONS

Women with a history of PBO with or without concurrent or preceding hysterectomy, especially at age <46 years, have more chronic conditions in late mid-life compared with referents.

Mendelian randomization in hepatology: A review of principles, opportunities, and challenges

Mendelian randomization has become a popular tool to assess causal relationships using existing observational data. While randomized controlled trials are considered the gold standard for establishing causality between exposures and outcomes, it is not always feasible to conduct a trial. Mendelian randomization is a causal inference method that uses observational data to infer causal relationships by using genetic variation as a surrogate for the exposure of interest. Publications using the approach have increased dramatically in recent years, including in the field of hepatology. In this concise review, we describe the concepts, assumptions, and interpretation of Mendelian randomization as related to studies in hepatology. We focus on the strengths and weaknesses of the approach for a non-statistical audience, using an illustrative example to assess the causal relationship between body mass index and NAFLD.

Polygenic prediction of bipolar disorder in a Latin American sample

To date, bipolar disorder (BD) genetic studies and polygenic risk scores (PRSs) for BD are based primarily on populations of European descent (EUR) and lack representation from other ancestries including Latin American (LAT). Here, we describe a new LAT cohort from the Mayo Clinic Bipolar Biobank (MCBB), a multisite collaboration with recruitment sites in the United States (EUR; 1,443 cases and 777 controls) and Mexico and Chile (LAT; 211 cases and 161 controls) and use the sample to explore the performance of a BD-PRS in a LAT population. Using results from the largest genome-wide association study of BD in EUR individuals, PRSice2 and LDpred2 were used to compute BD-PRSs in the LAT and EUR samples from the MCBB. PRSs explained up to 1.4% (PRSice) and 4% (LDpred2) of the phenotypic variance on the liability scale in the LAT sample compared to 3.8% (PRSice2) and 3.4% (LDpred2) in the EUR samples. Future larger studies should further explore the differential performance of different PRS approaches across ancestries. International multisite studies, such as this one, have the potential to address diversity-related limitations of prior genomic studies and ultimately contribute to the reduction of health disparities.

A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

BACKGROUND

Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.

METHODS

Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.

RESULTS

Assuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94).

CONCLUSIONS

Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.

Leadership Development in Early Career Scientists: Themes and Feedback from Executive Coaching and Mindful Leadership Training

Background: Career development is essential for all academic stages, but particularly critical for the growth and retention of early career scientists. In addition to scientific technical training, professional skill development is crucial for the upward transition from postdoctoral trainee to early faculty member and beyond. Building leadership skills, specifically, is an important component of professional development, and the evaluation and reporting of professional development are important to improve and enhance the impact of programs. Methods: The purpose of this article is to share the program evaluation performed on leadership development activities, including executive coaching and mindful leadership training provided to a small group of early career scientists who participated in the National Institutes of Health (NIH)-funded Mayo Clinic Specialized Center of Research Excellence (SCORE) in Sex Differences Career Enhancement Core and Building Interdisciplinary Research Careers in Women's Health (BIRCWH) K12 programs during 2020-2022. Results: Eighty-seven percent of participants rated their satisfaction with the executive coaching program as "Very Satisfied" or "Satisfied," and 75% of participants were "Very Satisfied" or "Satisfied" with the mindful leadership training program. The findings of this program evaluation highlight the value of communication skills for navigating precarious situations, building self-efficacy and intentionality in making and holding boundaries for an individual's time and energy. Further, the individualized small group format of the activities allowed for deeper introspection and peer to peer connection. Conclusion: The identification of common themes within the Mayo Clinic program provides guidance to other academic environments on areas where they can support their early career scientists.

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.

Quality control and analytic best practices for testing genetic models of sex differences in large populations

Phenotypic sex-based differences exist for many complex traits. In other cases, phenotypes may be similar, but underlying biology may vary. Thus, sex-aware genetic analyses are becoming increasingly important for understanding the mechanisms driving these differences. To this end, we provide a guide outlining the current best practices for testing various models of sex-dependent genetic effects in complex traits and disease conditions, noting that this is an evolving field. Insights from sex-aware analyses will not only teach us about the biology of complex traits but also aid in achieving the goals of precision medicine and health equity for all.

Toward a deeper understanding of gene-by-sex interaction models

In this issue of Cell Genomics, Zhu et al.1 propose amplification as the primary mode for gene-by-sex interactions in complex traits. Khramtsova et al. preview their modeling approach and discuss implications for the future work on the genomics of sex differences.

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.

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.

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.

The Interaction Between Brain-Derived Neurotrophic Factor Levels and Alcohol Consumption, Sleep Disturbance and Sex-Hormones in Alcohol Use Disorders

AIMS

Brain-derived neurotrophic factor (BDNF) levels may be associated with alcohol use disorders (AUD) and alcohol consumption, correlate with sleep disturbance and be influenced by sex differences and sex hormones. These associations have not been examined in a single sample accounting for all these factors.

METHODS

Data from 190 participants (29.4% female) with AUD were utilized. Sleep quality, craving intensity, depression, anxiety and alcohol consumption were assessed using the Pittsburgh Sleep Quality Index (PSQI), Penn Alcohol Craving Scale (PACS), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7) and Timeline Follow Back for 90 days(TLFB 90). Inventory of Drug Taking Situations (IDTS) assessed the tendency to drink in positive/negative emotional states. Serum BDNF (sBDNF) and plasma sex hormones (estrogen, progesterone, testosterone, FSH and SHBG) were measured. Pearson correlation analyses were used to examine the association between sBDNF and these measures in the entire sample and in men and women separately. Higher order interaction effects between these factors were evaluated for their association with sBDNF using a backward selection model.

RESULTS

No significant correlations between sBDNF levels and sex hormones, PSQI, PHQ-9, PACS, IDTS scores and alcohol consumption were found (all P-values > 0.05). sBDNF levels were negatively correlated with GAD-7 scores in men (r = -0.1841; P = 0.03). When considering all quadratic and two-way interactions among PSQI, PHQ-9, GAD-7, mean and max drinks/day, number of drinking days, heavy drinking days, and sex no higher order moderating effects of sBDNF levels were found.

CONCLUSION

Our study revealed no significant associations between sBDNF and alcohol measures, sleep, depression and sex hormones suggesting limited utility as a biomarker.

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.

CCNE1 and survival of patients with tubo-ovarian high-grade serous carcinoma: An Ovarian Tumor Tissue Analysis consortium study

BACKGROUND

Cyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo-ovarian high-grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large-scale, histotype-specific validation has been performed. The hypothesis was that high-level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC.

METHODS

Within the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated.

RESULTS

High-level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high-level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08-1.47, p = .034, and HR, 1.18; 95% CI, 1.05-1.32, p = .015, respectively). This was also true for cases with combined high-level amplification/overexpression (HR, 1.26; 95% CI, 1.09-1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1-SD increase; 95% CI, 0.94-1.06; p = .58). CCNE1 high-level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss.

CONCLUSION

This study provides large-scale validation that CCNE1 high-level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC.

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.

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.

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.

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.

Quality control recommendations for RNASeq using FFPE samples based on pre-sequencing lab metrics and post-sequencing bioinformatics metrics

Background

Formalin-fixed, paraffin-embedded (FFPE) tissues have many advantages for identification of risk biomarkers, including wide availability and potential for extended follow-up endpoints. However, RNA derived from archival FFPE samples has limited quality. Here we identified parameters that determine which FFPE samples have the potential for successful RNA extraction, library preparation, and generation of usable RNAseq data.

Methods

We optimized library preparation protocols designed for use with FFPE samples using seven FFPE and Fresh Frozen replicate pairs, and tested optimized protocols using a study set of 130 FFPE biopsies from women with benign breast disease. Metrics from RNA extraction and preparation procedures were collected and compared with bioinformatics sequencing summary statistics. Finally, a decision tree model was built to learn the relationship between pre-sequencing lab metrics and qc pass/fail status as determined by bioinformatics metrics.

Results

Samples that failed bioinformatics qc tended to have low median sample-wise correlation within the cohort (Spearman correlation < 0.75), low number of reads mapped to gene regions (< 25 million), or low number of detectable genes (11,400 # of detected genes with TPM > 4). The median RNA concentration and pre-capture library Qubit values for qc failed samples were 18.9 ng/ul and 2.08 ng/ul respectively, which were significantly lower than those of qc pass samples (40.8 ng/ul and 5.82 ng/ul). We built a decision tree model based on input RNA concentration, input library qubit values, and achieved an F score of 0.848 in predicting QC status (pass/fail) of FFPE samples.

Conclusions

We provide a bioinformatics quality control recommendation for FFPE samples from breast tissue by evaluating bioinformatic and sample metrics. Our results suggest a minimum concentration of 25 ng/ul FFPE-extracted RNA for library preparation and 1.7 ng/ul pre-capture library output to achieve adequate RNA-seq data for downstream bioinformatics analysis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01355-0.

The genetics of bipolar disorder with obesity and type 2 diabetes

BACKGROUND

Bipolar disorder (BD) presents with high obesity and type 2 diabetes (T2D) and pathophysiological and phenomenological abnormalities shared with cardiometabolic disorders. Genomic studies may help define if they share genetic liability. This selective review of BD with obesity and T2D will focus on genomic studies, stress their current limitations and guide future steps in developing the field.

METHODS

We searched electronic databases (PubMed, Scopus) until December 2021 to identify genome-wide association studies, polygenic risk score analyses, and functional genomics of BD accounting for body mass index (BMI), obesity, or T2D.

RESULTS

The first genome-wide association studies (GWAS) of BD accounting for obesity found a promising genome-wide association in an intronic gene variant of TCF7L2 that was further replicated. Polygenic risk scores of obesity and T2D have also been associated with BD, yet, no genetic correlations have been demonstrated. Finally, human-induced stem cell studies of the intronic variant in TCF7L2 show a potential biological impact of the products of this genetic variant in BD risk.

LIMITATIONS

The narrative nature of this review.

CONCLUSIONS

Findings from BD GWAS accounting for obesity and their functional testing, have prompted potential biological insights. Yet, BD, obesity, and T2D display high phenotypic, genetic, and population-related heterogeneity, limiting our ability to detect genetic associations. Further studies should refine cardiometabolic phenotypes, test gene-environmental interactions and add population diversity.

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.

Quantification of diet quality utilizing the rapid eating assessment for participants-shortened version in bipolar disorder: Implications for prospective depression and cardiometabolic studies

OBJECTIVES

Recognizing bipolar disorder as a multi-system metabolic condition driven, in part, by binge eating behavior and atypical depressive symptoms, this study aimed to quantify diet quality and evaluate clinical correlates in a bipolar disorder cohort.

METHODS

Participants from the Mayo Clinic Bipolar Disorder Biobank (n = 734) completed the Rapid Eating Assessment for Participants - Shortened version (REAP-S) to determine diet quality. The average REAP-S score for a U.S. omnivorous diet is 32 (range 13 to 39) with higher scores indicating healthier diet. Demographic variables were collected in a standardized clinical questionnaire. Depressive symptoms were assessed by the Bipolar Inventory of Symptoms Scale. Cardiometabolic variables were retrieved from the electronic health record. Associations between continuous variables and REAP-S scores (total, 'healthy foods' and 'avoidance of unhealthy foods') were assessed using linear regression.

RESULTS

Overall, our sample had a mean REAP-S score of 27.6 (4.9), suggestive of a lower diet quality than the average general population in the US. There was a significant inverse relationship between mean REAP-S lower scores with increased BMI, waist circumference, disordered eating and depression. All these associations were significantly stronger in female participants.

LIMITATIONS

EHR cross-sectional data.

CONCLUSIONS

Our data suggest unhealthy diet quality in bipolar disorder is associated with depression, obesity and cardiometabolic abnormalities. Additional work is encouraged to prospectively track mood and diet quality to further understand the bidirectional relationship and clarify if dietary interventions can positively impact mood. Further delineating potential sex differences in diet quality and depression may provide greater appreciation of modifiable risk factors for future cardiometabolic burden.

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.

Abstract 2203: Towards prediction of breast cancer risk in benign biopsies with high-plex GeoMx spatial protein profiling

Background: Biopsy diagnoses of benign breast disease (BBD) confer a 1.5- to 4-fold increased risk of developing breast cancer (BC) compared with women without BBD. Previously, we reported that decreased numbers of specific immune cell types in lobules of BBD biopsies predicted increased BC risk, suggesting the promise of future tissue biomarker studies to define BC risk markers among BBD patients. Thus, we applied protein-based GeoMx® Digital Spatial Profiling (DSP) to BBD biopsies preceding BC (cases) and to BBD biopsies from cancer-free patients (controls) to identify possible BC risk markers, which we then evaluated in subsequent BC tissues and in surrounding normal lobules of cases.

Methods: Archived pathology slides of BBD biopsies were reviewed and used to guide preparation of TMAs containing 1.0-mm diameter FFPE cores of lobules from an age- and cohort-period-matched set of 91 cases and 88 controls from the Mayo Clinic BBD Cohort. For patients who later developed BC, we prepared TMAs of BC tissue and surrounding mapped normal lobules. We applied GeoMx® DSP (immune and canonical signaling proteins) to both sets of TMAs. Following QC and data normalization, associations of case status with log-transformed biomarker expression in lobules of BBD biopsies were carried out using linear mixed modeling approaches, accounting for multiple ROIs per individual. Biomarkers significantly associated with case status (p&lt;0.05) were further examined in BCs and adjacent normal lobules, using similar approaches.

Results: The mean age at BBD biopsy was 52 years, and at BC diagnosis of cases, 61.4 years (mean time from BBD to BC was 10.2 years). A family history of BC was more frequent among cases (70% versus 43%; chi-square p=0.002). Of 72 biomarkers tested, 46 (64.4%) were evaluable after QC and normalization and 5 were associated with BC risk after adjustment for family history of BC: BCL2 (p=0.005), STING (p=0.006), CD44 (p=0.02), S100 protein (p=0.03) and pan-AKT (p=0.05); each showed higher levels in lobules of BBD biopsies of controls than cases. Three unique patterns appeared when examining these biomarkers across tissue type within cases: for BCL2 (p=5 x 10-9) and STING (p=2 x 10-19), levels were high in both BC and lobules surrounding BC but low in preceding BBD; for GAPDH (p=4 x 10-53) and pan-AKT (p=2 x 10-33), levels were high in BC, low in preceding BBD, and moderate in lobules surrounding BC; and for CD44 (p=2 x 10-6) and S100B (p=2 x 10-49), levels were low in BC, high in lobules surrounding BC and moderate in preceding BBD.

Conclusions: Using a novel TMA of lobules in combination with DSP, we preliminarily identified immune-based and PI3 kinase-related protein biomarkers in BBD biopsies associated with BC risk. In case-only analyses, these markers demonstrated complex differences between lobules in BBD biopsies, subsequent BCs and adjacent normal lobules.

Citation Format: Robert Alan Vierkant, Jodi M. Carter, Stacey J. Winham, Chen Wang, Jennifer M. Kachergus, Ji Shi, Raymond M. Moore, Bryan M. McCauley, Laura M. Pacheco-Spann, E A. Thompson, Derek C. Radisky, Amy C. Degnim, Mark E. Sherman. Towards prediction of breast cancer risk in benign biopsies with high-plex GeoMx spatial protein profiling [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 2203.

Abstract 5947: Immune biomarkers in breast tissues of patients with BRCA1/2 mutations, benign breast disease, and normal tissue donors

Introduction: The immune microenvironment of the breast is critical in the development and progression of breast cancer. By analyzing the immune components of breast tissues from patients at varying degrees of breast cancer risk, we may gain enhanced understanding of breast cancer risk and mechanisms of carcinogenesis.

Methods: We compared the immune cell composition in breast lobules of age-matched patients with normal and benign breast disease (BBD) at progressively lower breast cancer risk: 1) 18 women with germline mutations in (BRCA1/2); 2) women at intermediate risk (BBD), and 3) women at normal risk (Komen Tissue Bank- (KTB)). We performed immunohistochemical stains for T lymphocytes (CD4, CD8); dendritic cells (CD11c); B lymphocytes (CD20) and macrophages (CD68) and quantitated immune cell densities in up to 10 representative lobules per sample.

Results: The median age of all groups was 43.8 years (range: 34-67). BRCA carriers and BBD patients had a higher percentage of fibrocystic lobules (50% fibrocystic) compared to KTB samples (15% fibrocystic), p&lt;0.001. BRCA carriers had significantly higher densities of CD4, CD8, CD11c, and CD68 positive immune cells compared to KTB donor breast tissues, see Table. Compared with BBD patients, mutation carriers had higher densities of CD8+ cells and suggestively higher CD4+ cells, with similar results for other markers assessed.

Conclusions: Preliminarily, these data showed that benign prophylactic breast tissues from BRCA mutation carriers contain increased numbers of several immune cell types versus tissues from patients at lower breast cancer risk, including BBD patients and research tissue donors. Further investigation is needed to confirm and expand these findings in relation to breast cancer risk.

Table: Pairwise Wilcoxon rank-sum p-values comparing immune cell densities in breast lobules from women with BRCA germline mutations, vs BBD and KTB groups. All Lobules BRCA BBD KTB BRCA vs BBD BRCA vs KTB Median Median Median p-value p-value (IQR) (IQR) (IQR) CD4+, cells/mm2 116.3 63.8 17.7 0.08 &lt;0.001 (46.4-183.6) (25.0-121.1) (13.3-40.6) CD8+, cells/mm2 354.4 200 150.9 0.01 &lt;0.001 (285.5-473.2) (118.9-385) (110.1-225.0) CD11c+, % pp 3.5 3.4 0.4 0.66 &lt;0.001 (1.9-6.8) (1.6-4.7) (0-0.6) CD20+, cells/mm2 6.2 16.7 0 0.16 0.65 (0-25.4) (0-58.3) (0-20.8) CD68, cells/mm2 237.5 219 57.8 0.99 &lt;0.001 (122.9-281.8) (75.0-459.4) (29.2-100.0) IQR - Interquartile Range pp - pixel positive

Citation Format: Joshua W. Ogony, Tanya L. Hoskin, Melody L. Stallings Mann, Stacey J. Winham, Rushin Brahmbhatt, Muhammad Asad Arshad, Alvaro Pena Jimenez, Teresa M. Allers, Mark E. Sherrman, Daniel W. Visscher, Derek C. Radisky, Amy C. Degnim. Immune biomarkers in breast tissues of patients with BRCA1/2 mutations, benign breast disease, and normal tissue donors [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 5947.

Germline BRCA variants, lifestyle and ovarian cancer survival

OBJECTIVE

Women with ovarian cancer who have a pathogenic germline variant in BRCA1 or BRCA2 (BRCA) have been shown to have better 5-year survival after diagnosis than women who are BRCA-wildtype (non-carriers). Modifiable lifestyle factors, including smoking, physical activity and body mass index (BMI) have previously been associated with ovarian cancer survival; however, it is unknown whether these associations differ by germline BRCA status.

METHODS

We investigated measures of lifestyle prior to diagnosis in two cohorts of Australian women with invasive epithelial ovarian cancer, using Cox proportional hazards regression to calculate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

In the combined studies (n = 1923), there was little association between physical activity, BMI or alcohol intake and survival, and no difference by BRCA status. However, the association between current smoking status before diagnosis and poorer survival was stronger for BRCA variant carriers (HR 1.98; 95% CI 1.20-3.27) than non-carriers (HR 1.18; 95% CI 0.96-1.46; p-interaction 0.02). We saw a similar differential association with smoking when we pooled results from two additional cohorts from the USA and UK (n = 2120). Combining the results from all four studies gave a pooled-HR of 1.94 (95% CI 1.28-2.94) for current smoking among BRCA variant carriers compared to 1.08 (0.90-1.29) for non-carriers.

CONCLUSIONS

Our results suggest that the adverse effect of smoking on survival may be stronger for women with a BRCA variant than those without. Thus, while smoking cessation may improve outcomes for all women with ovarian cancer, it might provide a greater benefit for BRCA variant carriers.

Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women

Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10-8 as genome-wide significant, and p-values < 1 × 10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10-7), which showed genome-wide significant interaction (p-value = 3.8 × 10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.

MCM3 is a novel proliferation marker associated with longer survival for patients with tubo-ovarian high-grade serous carcinoma

Tubo-ovarian high-grade serous carcinomas (HGSC) are highly proliferative neoplasms that generally respond well to platinum/taxane chemotherapy. We recently identified minichromosome maintenance complex component 3 (MCM3), which is involved in the initiation of DNA replication and proliferation, as a favorable prognostic marker in HGSC. Our objective was to further validate whether MCM3 mRNA expression and possibly MCM3 protein levels are associated with survival in patients with HGSC. MCM3 mRNA expression was measured using NanoString expression profiling on formalin-fixed and paraffin-embedded tissue (N = 2355 HGSC) and MCM3 protein expression was assessed by immunohistochemistry (N = 522 HGSC) and compared with Ki-67. Kaplan-Meier curves and the Cox proportional hazards model were used to estimate associations with survival. Among chemotherapy-naïve HGSC, higher MCM3 mRNA expression (one standard deviation increase in the score) was associated with longer overall survival (HR = 0.87, 95% CI 0.81-0.92, p < 0.0001, N = 1840) in multivariable analysis. MCM3 mRNA expression was highest in the HGSC C5.PRO molecular subtype, although no interaction was observed between MCM3, survival and molecular subtypes. MCM3 and Ki-67 protein levels were significantly lower after exposure to neoadjuvant chemotherapy compared to chemotherapy-naïve tumors: 37.0% versus 46.4% and 22.9% versus 34.2%, respectively. Among chemotherapy-naïve HGSC, high MCM3 protein levels were also associated with significantly longer disease-specific survival (HR = 0.52, 95% CI 0.36-0.74, p = 0.0003, N = 392) compared to cases with low MCM3 protein levels in multivariable analysis. MCM3 immunohistochemistry is a promising surrogate marker of proliferation in HGSC.

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.

Automated quantification of levels of breast terminal duct lobular (TDLU) involution using deep learning

Convolutional neural networks (CNNs) offer the potential to generate comprehensive quantitative analysis of histologic features. Diagnostic reporting of benign breast disease (BBD) biopsies is usually limited to subjective assessment of the most severe lesion in a sample, while ignoring the vast majority of tissue features, including involution of background terminal duct lobular units (TDLUs), the structures from which breast cancers arise. Studies indicate that increased levels of age-related TDLU involution in BBD biopsies predict lower breast cancer risk, and therefore its assessment may have potential value in risk assessment and management. However, assessment of TDLU involution is time-consuming and difficult to standardize and quantitate. Accordingly, we developed a CNN to enable automated quantitative measurement of TDLU involution and tested its performance in 174 specimens selected from the pathology archives at Mayo Clinic, Rochester, MN. The CNN was trained and tested on a subset of 33 biopsies, delineating important tissue types. Nine quantitative features were extracted from delineated TDLU regions. Our CNN reached an overall dice-score of 0.871 (±0.049) for tissue classes versus reference standard annotation. Consensus of four reviewers scoring 705 images for TDLU involution demonstrated substantial agreement with the CNN method (unweighted κappa = 0.747 ± 0.01). Quantitative involution measures showed anticipated associations with BBD histology, breast cancer risk, breast density, menopausal status, and breast cancer risk prediction scores (p < 0.05). Our work demonstrates the potential to improve risk prediction for women with BBD biopsies by applying CNN approaches to generate automated quantitative evaluation of TDLU involution.

DNA Methylation Profiles of Ovarian Clear Cell Carcinoma

BACKGROUND

Ovarian clear cell carcinoma (OCCC) is a rare ovarian cancer histotype that tends to be resistant to standard platinum-based chemotherapeutics. We sought to better understand the role of DNA methylation in clinical and biological subclassification of OCCC.

METHODS

We interrogated genome-wide methylation using DNA from fresh frozen tumors from 271 cases, applied nonsmooth nonnegative matrix factorization (nsNMF) clustering, and evaluated clinical associations and biological pathways.

RESULTS

Two approximately equally sized clusters that associated with several clinical features were identified. Compared with Cluster 2 (N = 137), Cluster 1 cases (N = 134) presented at a more advanced stage, were less likely to be of Asian ancestry, and tended to have poorer outcomes including macroscopic residual disease following primary debulking surgery (P < 0.10). Subset analyses of targeted tumor sequencing and IHC data revealed that Cluster 1 tumors showed TP53 mutation and abnormal p53 expression, and Cluster 2 tumors showed aneuploidy and ARID1A/PIK3CA mutation (P < 0.05). Cluster-defining CpGs included 1,388 CpGs residing within 200 bp of the transcription start sites of 977 genes; 38% of these genes (N = 369 genes) were differentially expressed across cluster in transcriptomic subset analysis (P < 10-4). Differentially expressed genes were enriched for six immune-related pathways, including IFNα and IFNγ responses (P < 10-6).

CONCLUSIONS

DNA methylation clusters in OCCC correlate with disease features and gene expression patterns among immune pathways.

IMPACT

This work serves as a foundation for integrative analyses that better understand the complex biology of OCCC in an effort to improve potential for development of targeted therapeutics.

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 (r_g = 0.79, P = 5.91 × 10⁻⁵), percent density (r_g = 0.73, P = 1.00 × 10⁻⁴), and adult BMI (r_g =  − 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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-022-01570-8.

Plasma Cell-Free DNA Methylomics of Bipolar Disorder With and Without Rapid Cycling

Rapid cycling (RC) burdens bipolar disorder (BD) patients further by causing more severe disability and increased suicidality. Because diagnosing RC can be challenging, RC patients are at risk of rapid decline due to delayed suitable treatment. Here, we aimed to identify the differences in the circulating cell-free DNA (cfDNA) methylome between BD patients with and without RC. The cfDNA methylome could potentially be developed as a diagnostic test for BD RC. We extracted cfDNA from plasma samples of BD1 patients (46 RC and 47 non-RC). cfDNA methylation levels were measured by 850K Infinium MethylationEPIC array. Principal component analysis (PCA) was conducted to assess global differences in methylome. cfDNA methylation levels were compared between RC groups using a linear model adjusted for age and sex. PCA suggested differences in methylation profiles between RC groups (p = 0.039) although no significant differentially methylated probes (DMPs; q > 0.15) were found. The top four CpG sites which differed between groups at p < 1E-05 were located in CGGPB1, PEX10, NR0B2, and TP53I11. Gene set enrichment analysis (GSEA) on top DMPs (p < 0.05) showed significant enrichment of gene sets related to nervous system tissues, such as neurons, synapse, and glutamate neurotransmission. Other top notable gene sets were related to parathyroid regulation and calcium signaling. To conclude, our study demonstrated the feasibility of utilizing a microarray method to identify circulating cfDNA methylation sites associated with BD RC and found the top differentially methylated CpG sites were mostly related to the nervous system and the parathyroid.

Understanding Verbosity: Funding Source and the Length of Consent Forms for Cancer Clinical Trials

Consent forms are an important educational tool that helps cancer patients decide on whether or not to enroll on a clinical trial, but wordiness potentially detracts from their educational value. This single-institution study examined word counts of consent forms for all phase I, II, and III solid tumor clinical trials between 2004 and 2010. Consent forms were categorized by trial funding source: (1) pharmaceutical company; (2) National Clinical Trials Network (NCTN); (3) R01- or other non-government grants; and (4) mixed (funding from multiple sources). Three hundred fifteen consent forms were studied; these included 106 (34%) pharmaceutical company; 145 (46%) NCTN; 44 (14%) R01 type; and 20 (6%) mixed. The overall median word count was 5129 words per consent form (interquartile range (IQR) range, 4226 to 6695). The median word counts per consent form (IQR) were 5648 (4814, 6803), 5243 (4139, 6932), 4365 (3806, 5124), and 4319 (3862, 5944), respectively, based on the above funding sources, showing that pharmaceutical company trial consent forms had the highest median word count. Of note, phase of trial was associated with consent form length (phase III were wordier), and consent forms manifested a consistent increase in wordiness over time. These observations underscore a timely need to find ways to limit the verbosity of consent forms, particularly in those from pharmaceutical company trials.

Incorporating Robustness to Imaging Physics into Radiomic Feature Selection for Breast Cancer Risk Estimation

Digital mammography has seen an explosion in the number of radiomic features used for risk-assessment modeling. However, having more features is not necessarily beneficial, as some features may be overly sensitive to imaging physics (contrast, noise, and image sharpness). To measure the effects of imaging physics, we analyzed the feature variation across imaging acquisition settings (kV, mAs) using an anthropomorphic phantom. We also analyzed the intra-woman variation (IWV), a measure of how much a feature varies between breasts with similar parenchymal patterns-a woman's left and right breasts. From 341 features, we identified "robust" features that minimized the effects of imaging physics and IWV. We also investigated whether robust features offered better case-control classification in an independent data set of 575 images, all with an overall BI-RADS® assessment of 1 (negative) or 2 (benign); 115 images (cases) were of women who developed cancer at least one year after that screening image, matched to 460 controls. We modeled cancer occurrence via logistic regression, using cross-validated area under the receiver-operating-characteristic curve (AUC) to measure model performance. Models using features from the most-robust quartile of features yielded an AUC = 0.59, versus 0.54 for the least-robust, with p < 0.005 for the difference among the quartiles.

Randomized, Double-Blind Trial on the Impact of Word Count in Cancer Clinical Trial Consent Forms

PURPOSE

This randomized, double-blind study sought to understand whether cancer clinical trial consent form verbosity detracts from patients' decision making on trial enrollment.

METHODS

This trial tested mock consent forms of 2,000, 4,000, and 6,000 words. The first two comprised the two experimental arms and the third the control arm. Phase II was conducted to identify the promising arm, which, in phase III, was compared with the control arm. Each consent form described the same trial. Eligible adult patients reported a cancer history and English literacy. The primary end point used a patient-reported Likert scale to assess the relationship between information in the consent form and trial decision making.

RESULTS

In phase II, 93 patients were accrued and prompted the selection of the 2,000-word consent form for phase III. In phase III, 182 patients were recruited, resulting in 240 total evaluable patients to compare the 2,000-word versus the 6,000-word arm (control). For the primary end point, 103 (84%) and 107 (91%) patients in the 2,000- and 6,000-word arms, respectively, strongly agreed or agreed with the following: "The information in this consent form helped me make a decision about whether or not to enroll in the trial" (two-sided, P = .14). Median time to read each consent form was 8 and 12 minutes, respectively (two-sided, P < .0001). Among those assigned these consent forms, 84% and 73%, respectively (two-sided, P = .04) signed or expressed a willingness to sign.

CONCLUSION

This study's primary end point was not met. However, secondary outcomes suggest a need to further study the efficiency and efficacy of shorter consent forms for cancer clinical trial enrollment.

Fully Automated Volumetric Breast Density Estimation from Digital Breast Tomosynthesis

Background While digital breast tomosynthesis (DBT) is rapidly replacing digital mammography (DM) in breast cancer screening, the potential of DBT density measures for breast cancer risk assessment remains largely unexplored. Purpose To compare associations of breast density estimates from DBT and DM with breast cancer. Materials and Methods This retrospective case-control study used contralateral DM/DBT studies from women with unilateral breast cancer and age- and ethnicity-matched controls (September 19, 2011-January 6, 2015). Volumetric percent density (VPD%) was estimated from DBT using previously validated software. For comparison, the publicly available Laboratory for Individualized Breast Radiodensity Assessment software package, or LIBRA, was used to estimate area-based percent density (APD%) from raw and processed DM images. The commercial Quantra and Volpara software packages were applied to raw DM images to estimate VPD% with use of physics-based models. Density measures were compared by using Spearman correlation coefficients (r), and conditional logistic regression was performed to examine density associations (odds ratios [OR]) with breast cancer, adjusting for age and body mass index. Results A total of 132 women diagnosed with breast cancer (mean age ± standard deviation [SD], 60 years ± 11) and 528 controls (mean age, 60 years ± 11) were included. Moderate correlations between DBT and DM density measures (r = 0.32-0.75; all P < .001) were observed. Volumetric density estimates calculated from DBT (OR, 2.3 [95% CI: 1.6, 3.4] per SD for VPD%_DBT) were more strongly associated with breast cancer than DM-derived density for both APD% (OR, 1.3 [95% CI: 0.9, 1.9] [P < .001] and 1.7 [95% CI: 1.2, 2.3] [P = .004] per SD for LIBRA raw and processed data, respectively) and VPD% (OR, 1.6 [95% CI: 1.1, 2.4] [P = .01] and 1.7 [95% CI: 1.2, 2.6] [P = .04] per SD for Volpara and Quantra, respectively). Conclusion The associations between quantitative breast density estimates and breast cancer risk are stronger for digital breast tomosynthesis compared with digital mammography. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Yaffe in this issue.

Identification of a Locus Near ULK1 Associated With Progression-Free Survival in Ovarian Cancer

BACKGROUND

Many loci have been found to be associated with risk of epithelial ovarian cancer (EOC). However, although there is considerable variation in progression-free survival (PFS), no loci have been found to be associated with outcome at genome-wide levels of significance.

METHODS

We carried out a genome-wide association study (GWAS) of PFS in 2,352 women with EOC who had undergone cytoreductive surgery and standard carboplatin/paclitaxel chemotherapy.

RESULTS

We found seven SNPs at 12q24.33 associated with PFS (P < 5 × 10-8), the top SNP being rs10794418 (HR = 1.24; 95% CI, 1.15-1.34; P = 1.47 × 10-8). High expression of a nearby gene, ULK1, is associated with shorter PFS in EOC, and with poor prognosis in other cancers. SNP rs10794418 is also associated with expression of ULK1 in ovarian tumors, with the allele associated with shorter PFS being associated with higher expression, and chromatin interactions were detected between the ULK1 promoter and associated SNPs in serous and endometrioid EOC cell lines. ULK1 knockout ovarian cancer cell lines showed significantly increased sensitivity to carboplatin in vitro.

CONCLUSIONS

The locus at 12q24.33 represents one of the first genome-wide significant loci for survival for any cancer. ULK1 is a plausible candidate for the target of this association.

IMPACT

This finding provides insight into genetic markers associated with EOC outcome and potential treatment options.See related commentary by Peres and Monteiro, p. 1604.