Couch, Fergus J.

ABSTRACT The normal adult male breast has not been characterized at single-cell resolution, leaving the cellular basis of male breast cancer (MBC) biology undefined. Here we present an integrated single-cell RNA sequencing atlas of the adult human breast comprising 174,471 cells from 17 donors (3 male, 14 female), including 18,117 male-derived cells. This revealed that the male breast retains all three epithelial populations, basal (BC), luminal progenitor (LP), and luminal committed cells (LC), but with an increase in LC at the expense of BC and LP across all three male donors. Male LC were distinguished from female by elevated ESR1 and PGR mRNA, enrichment of RNA processing and ribosome biogenesis programs, reduced inflammatory cytokine and growth factor signaling, elevated estradiol gene set enrichment scores, and higher inferred activity of developmental patterning transcription factors. This pattern was observed across differential expression, gene ontology, ligand profiling, and regulon-based analyses, and was not restricted to sex chromosome-linked gene expression. This is consistent with the near-universal estrogen receptor (ER) positivity that characterizes MBC clinically. This atlas provides the first cellular and transcriptional reference for the normal male breast and a resource for investigating sex differences in mammary biology, germline susceptibility variant interpretation, and modeling breast malignancies.

Abstract Background Artificial intelligence (AI)–based, mammography breast cancer risk prediction models show improved discriminatory accuracy relative to clinical risk models. However, data on their calibration are limited. This study compared model performance of 3 clinical breast cancer risk models: Gail, Tyrer–Cuzick v8, and Breast Cancer Surveillance Consortium v3 with the MIRAI AI-risk model. Methods Digital mammograms were ascertained from a screening mammography cohort of 12 308 women within the Mayo Clinic Biobank with 250 incident breast cancers (176 invasive) within 5 years. We predicted 5-year breast cancer risk, estimated discriminatory accuracy (C-index), and calibration (observed-to-expected ratio) of both overall and invasive breast cancer and compared estimates using bootstrapping approaches. Results MIRAI demonstrated similar or improved discriminatory accuracy of overall breast cancer (C-index = 0.71, 95% confidence interval [CI] = 0.68 to 0.74) and invasive breast cancer (C-index = 0.71, 95% CI = 0.67 to 0.75) compared with clinical models (overall breast cancer: C-index = 0.59-0.68; invasive breast cancer: C-index = 0.60-0.68). MIRAI’s calibration for risk of overall breast cancer (observed-to-expected ratio = 0.96, 95% CI = 0.85 to 1.08) was improved compared with Gail (observed-to-expected ratio = 1.22, 95% CI = 1.07 to 1.38) and Breast Cancer Surveillance Consortium (observed-to-expected ratio = 1.38, 95% CI = 1.22 to 1.56) but similar to TC with volumetric percent density and polygenic risk score (observed-to-expected ratio = 0.99, 95% CI = 0.87 to 1.13). However, for low-risk women (approximately 50%), MIRAI overestimated risk of overall breast cancer. MIRAI also overestimated risk of invasive breast cancer across the risk spectrum (observed-to-expected ratio = 0.68, 95% CI = 0.58 to 0.78), whereas clinical models had good calibration (observed-to-expected ratio = 0.86–0.99). Conclusion MIRAI demonstrated stronger discriminatory accuracy than clinical models for 5-year overall and invasive breast cancer risk prediction but overestimated risk for both breast cancer endpoints. AI-based risk models should consider discriminatory accuracy and calibration for invasive cancer before implementation.

PURPOSE To compare mortality risk among long-term survivors of high-grade serous ovarian cancer (HGSOC) with that of the general US population and to examine how mortality and recurrence trends have evolved under changing treatment approaches. MATERIALS AND METHODS This is a retrospective cohort study including patients with histologically confirmed HGSOC treated at a single referral cancer center from 1991 to 2022. Mortality risk, expressed as standardized mortality ratios (SMRs, ratio of observed deaths in the study population to expected deaths in an age-matched US population), was assessed at diagnosis and yearly on patients without events (disease persistence, recurrence, or death from any cause). RESULTS A total of 2,074 consecutive patients were included. The median follow-up was 12.5 years (IQR, 11.7-13.8). Most patients were stage III (1,396, 69.2%), 1,299 (62.8%) underwent primary cytoreductive surgery, and 1,688 (87.4%) received platinum-taxane as first-line therapy. At diagnosis, the mortality rate was 7.40 times higher than that in the general population (95% CI, 7.04 to 7.77). By 7 event-free years, the 95% CI for the SMR included 1 for the first time, and at 10 years, the SMR was 1.05 (95% CI, 0.72 to 1.49), indicating no statistically significant excess mortality compared with the general population. In those event-free at 10 years, the 5-year cumulative incidence of ovarian cancer–related deaths (8.2% [95% CI, 4.2 to 16.0]) was comparable with that of non–ovarian cancer–related deaths (6.3% [95% CI, 2.9 to 13.8]). CONCLUSION In this cohort, mortality risk steadily declined for patients who remained event-free, approaching that of the general population by 7 years after diagnosis. These results emphasize the importance of individualized, long-term follow-up to address both recurrence risk and survivorship needs.

Abstract Background The association of germline pathogenic and likely pathogenic variants (GPVs) in hereditary breast cancer genes with underlying tumor biology and clinical outcomes remains incompletely understood. This study characterized differences in somatic alterations and intrinsic subtypes between sporadic and hereditary breast cancers associated with GPVs in ATM, BRCA1, BRCA2, CHEK2, or PALB2. Methods This retrospective cohort study included women with breast cancer and an ATM, BRCA1, BRCA2, CHEK2, or PALB2 GPV who had undergone tumor sequencing and whole transcriptome RNA expression analysis. Clinicopathological features, intrinsic subtypes, somatic alterations, and survival were compared by GPV status and immunohistochemistry-defined subtype and to sporadic cases. All statistical significance tests were 2-sided. Results The 4988 women with breast cancer in this study included 98 BRCA1, 126 BRCA2, 74 PALB2, 54 ATM, and 83 CHEK2 GPVs. Compared with sporadic cases, hormone receptor–positive/(ERBB2) formerly HER2–negative tumors in BRCA1 GPVs were statistically significantly enriched for basal subtype (45.5% vs 11.4%; P < .001), while CHEK2 carriers had a higher prevalence of luminal A subtype (80.4% vs 60.3%; P = .006). In hormone receptor–positive/(ERBB2)-negative breast cancers, BRCA1 GPVs were enriched for TP53 alterations (84.6% vs 29.8%; q < 0.001), ATM GPVs with FGFR1 alterations (35.4% vs 12.7%; q = 0.04), and BRCA2 GPVs with APC alterations (10.1% vs 1.5%; q = 0.004). Conversely, BRCA2 GPVs were inversely associated with PIK3CA alterations (13.0% vs 34.1%; q = 0.005) and CHEK2 GPVs with TP53 alterations (8.0% vs 29.8%; q = 0.02). Conclusions The GPVs in BRCA1, BRCA2, ATM, CHEK2, and PALB2 are associated with distinct intrinsic breast cancer subtypes and somatic genomic alterations. These findings may enhance precision in risk stratification and guide personalized treatment strategies.

PURPOSE BRCA carriers face high risks of developing both breast and ovarian/fallopian tube cancers (hereafter referred to as ovarian ). Among BRCA carriers with ovarian cancer, it is not clear whether the risk of breast cancer is sufficiently high that risk-reducing mastectomy should be offered. This study aimed to assess the risk of breast cancer BRCA carriers after a diagnosis of ovarian cancer. METHODS We included women with a pathogenic/likely pathogenic variant in BRCA1 or BRCA2 , a diagnosis of ovarian cancer, and no other cancer history and no risk-reducing bilateral mastectomy. Women were followed for incident breast cancer from the date of ovarian cancer diagnosis or the date of baseline questionnaire, whichever came last. The 5-, 10-, and 15-year cumulative risks of breast cancer were compared for women with ovarian cancer and an age-matched set of control women without ovarian cancer. RESULTS A total of 960 participants with ovarian cancer were identified (814 BRCA1 and 146 BRCA2 carriers). After a mean follow-up of 4.9 years, 41 women (4.3%) developed breast cancer, at a mean age at diagnosis of 57.5 years (range, 39-74). Actuarial cumulative breast cancer risks after ovarian cancer were 4.4%, 8.9%, and 11.5% at 5, 10, and 15 years, respectively. Only three breast cancer–related deaths occurred. Among 741 age-matched BRCA carriers without ovarian cancer, actuarial cumulative risks of breast cancer were 20.9%, 38.6%, and 47.2% at 5, 10, and 15 years, respectively. The hazard ratio for breast cancer, after an ovarian cancer diagnosis, compared with no ovarian cancer, was 0.18 ([95% CI, 0.12 to 0.27]; P < .0001). CONCLUSION After ovarian cancer, BRCA carriers have a relatively low risk of breast cancer. Risk-reducing mastectomy should not be recommended routinely, but might be considered for long-term survivors. Magnetic resonance imaging surveillance and/or mammography is a realistic alternative.

Abstract Purpose To evaluate alcohol intake trends and identify demographic, clinical, lifestyle and socioeconomic factors associated with alcohol consumption in late survivorship among breast cancer survivors. Methods Individuals diagnosed with stage 0–3 breast cancer enrolled in the Mayo Clinic Breast Disease registry between 2014 to 2022 reported their average weekly alcohol intake at baseline (time of diagnosis) and at approximately four years post-diagnosis. Alcohol intake was divided into four categories and cross-sectional associations with demographic, clinical, and lifestyle factors were examined using Monte Carlo-based Fisher exact tests and multivariable multinomial logistic regression. Changes in alcohol consumption from baseline to Year 4 were evaluated using Bowker’s test of symmetry and multinomial models. Results Among 719 participants, alcohol intake 4 years post diagnosis closely resembled baseline patterns, with 30.2% of patients reporting no alcohol use and 48.8% of patients consuming 1–4 drinks per week. Younger age and current smoking status were strongly associated with higher intake at Year 4. Exercise and better physical health were associated with higher alcohol intake in univariable models, however not in adjusted models. From time of diagnosis to Year 4, 15.6% of patients decreased their alcohol intake, 10.2% increased alcohol intake, and 74.3% reported no change. Higher levels of mild intensity exercise were associated with an elevation in alcohol intake over time. Conclusion Alcohol consumption remained stable in late survivorship, in contrast to the initial decline in alcohol use during early survivorship seen in this cohort. Younger age and smoking were key associations with higher alcohol intake.

Poly(ADP-ribose) polymerase (PARP) inhibitors (PARPis) are an important therapy for high-grade serous ovarian cancer (HGSOC). However, PARPi resistance frequently emerges, necessitating previously unrecognized approaches to improve HGSOC responses. Here, we showed that the anaplastic lymphoma kinase (ALK) inhibitor brigatinib enhances PARPi activity in HGSOC cells by disrupting an adaptive survival mechanism orchestrated by Fos-related antigen 1 (FRA1) in response to PARPi. This effect of brigatinib occurred through an ALK-independent pathway, wherein brigatinib induced a dual blockade of focal adhesion kinase (FAK) and EPH receptor A2 (EPHA2) tyrosine kinases, leading to the suppression of protein kinase B (Akt) and extracellular-regulated kinase (ERK) signaling accompanied by disruption of a phosphorylation event crucial for FRA1 protein stability. Moreover, in HGSOC patient-derived xenograft (PDX) models, brigatinib and PARPi combination therapy induced tumor regression and improved overall survival compared with PARPi alone, particularly in models with high FAK and EPHA2. These findings support dual targeting of FAK and EPHA2 as a strategy to achieve effective and durable PARPi responses and identify a promising biomarker-based combinatorial approach using brigatinib and PARPi for HGSOC, particularly the subset characterized by high FAK and EPHA2.

Abstract Background Women with a pathogenic variant in BRCA1 or BRCA2 are at high risk of developing ovarian cancer, and it is often recommended that they undergo bilateral salpingo-oophorectomy at an early age, resulting in surgical menopause. Menopausal hormone replacement therapy (HRT) is an effective way to mitigate the adverse outcomes of early menopause; however, the safety of menopausal HRT on breast cancer risk in this population has not been established. Methods We conducted a prospective matched analysis of HRT use following menopause and breast cancer risk in BRCA carriers. Women who initiated HRT were matched one-to-one with women who had not initiated menopausal HRT by gene, year of birth, and age at menopause, resulting in 676 matched pairs. Menopausal HRT use collected by questionnaire included formulation and mode of administration. Results After a mean of 5.6 years, there were 87 (12.9%) incident breast cancer cases in the 676 exposed women and 128 (18.9%) cases in the 676 unexposed women (P = .002). Compared with unexposed matched control individuals, women who used estrogen alone experienced a statistically significantly decreased risk of breast cancer (hazard ratio = 0.37, 95% CI = 0.24 to 0.57). No protective or adverse effect was associated with the use of estrogen plus progestogen (hazard ratio = 0.94, 95% CI = 0.54 to 1.63). Conclusions Our findings suggest no substantial increase in the risk of breast cancer in BRCA carriers with the use of HRT and that estrogen alone might be protective.

Background: Endometriosis affects an estimated 10% of reproductive-aged women and is associated with increased ovarian cancer risk. While BRCA1/2 mutations are established risk factors for ovarian cancer, their association with endometriosis remains unclear. This study aimed to characterize the prevalence and clinical features of endometriosis within a large cohort of BRCA mutation carriers. Methods: A descriptive analysis was conducted using data from a multi-center longitudinal cohort of women with pathogenic BRCA variants. Reproductive history and related factors were collected through self-reported questionnaires and compared. Results: Among 16,950 BRCA carriers, the prevalence of endometriosis was 2.4%. Compared to BRCA carriers without endometriosis, those with endometriosis were more likely to carry a BRCA2 mutation, have post-secondary education, and experience earlier menarche. BRCA carriers with endometriosis had a lower ovarian cancer prevalence than those without (10% vs. 15%, p < 0.001). Conclusions: This is the first study of this scale to report the prevalence of endometriosis among BRCA mutation carriers, which was lower than previously reported in the general population. The association between endometriosis and ovarian cancer does not appear to be generalizable to this population. Further prospective studies are warranted to clarify this association among BRCA mutation carriers.

Treatment-induced ovarian function loss is a significant concern for many young patients with breast cancer. Accurately predicting this risk is crucial for counselling young patients and informing their fertility-related decision-making. However, current risk prediction models for treatment-related ovarian function loss have limitations. To provide a broader representation of patient cohorts and improve feature selection, we combined retrospective data from six datasets within the FoRECAsT (Infertility after Cancer Predictor) databank, including 2679 pre-menopausal women diagnosed with breast cancer. This combined dataset presented notable missingness, prompting us to employ cross imputation using the k-nearest neighbours (KNN) machine learning (ML) algorithm. Employing Lasso regression, we developed an ML model to forecast the risk of treatment-related amenorrhea as a surrogate marker of ovarian function loss at 12 months after starting chemotherapy. Our model identified 20 variables significantly associated with risk of developing amenorrhea. Internal validation resulted in an area under the receiver operating characteristic curve (AUC) of 0.820 (95% CI: 0.817–0.823), while external validation with another dataset demonstrated an AUC of 0.743 (95% CI: 0.666–0.818). A cutoff of 0.20 was chosen to achieve higher sensitivity in validation, as false negatives—patients incorrectly classified as likely to regain menses—could miss timely opportunities for fertility preservation if desired. At this threshold, internal validation yielded sensitivity and precision rates of 91.3% and 61.7%, respectively, while external validation showed 92.9% and 60.0%. Leveraging ML methodologies, we not only devised a model for personalised risk prediction of amenorrhea, demonstrating substantial enhancements over existing models but also showcased a robust framework for maximally harnessing available data sources.