Androgen deprivation induces double-null prostate cancer via aberrant nuclear export and ribosomal biogenesis through HGF and Wnt activation.

Androgen deprivation therapy (ADT) targeting androgen/androgen receptor (AR)- signaling pathways is the main therapy for advanced prostate cancer (PCa). However, ADT eventually fails in most patients who consequently develop castration-resistant prostate cancer (CRPC). While more potent AR antagonists and blockers for androgen synthesis were developed to improve clinical outcomes, they also show to induce more diverse CRPC phenotypes. Specifically, the AR- and neuroendocrine-null PCa, DNPC, occurs in abiraterone and enzalutamide-treated patients. Here, we uncover that current ADT induces aberrant HGF/MET signaling activation that further elevates Wnt/ß-catenin signaling in human DNPC samples. Co-activation of HGF/MET and Wnt/ß-catenin axes in mouse prostates induces DNPC-like lesions. Single-cell RNA sequencing analyses identify increased expression and activity of XPO1 and ribosomal proteins in mouse DNPC-like cells. Elevated expression of XPO1 and ribosomal proteins is also identified in clinical DNPC specimens. Inhibition of XPO1 and ribosomal pathways represses DNPC growth in both in vivo and ex vivo conditions, evidencing future therapeutic targets.

XIAP overexpressing inflammatory breast cancer patients have high infiltration of immunosuppressive subsets and increased TNFR1 signaling targetable with Birinapant.

OBJECTIVE: To assess the expression pattern of X-linked inhibitor of apoptosis protein (XIAP), a cellular stress sensor, and delineate the associated changes in the tumor immune microenvironment (TiME) for prognostic value and new therapeutic targets in inflammatory breast cancer (IBC). METHODS: Immunohistochemistry was conducted to assess the spatial localization of immune subsets, XIAP, and PDL1 expression in IBC and non-inflammatory breast cancer (nIBC) pretreatment tumors (n = 142). Validation and further exploration were performed by gene expression analysis of patient tumors along with signaling studies in a co-culture model. RESULTS: High XIAP in 37/81 IBC patients correlated significantly with high PD-L1, increased infiltration of FOXP3+ Tregs, CD163+ tumor-associated macrophages (TAMs), low CD8/CD163 ratio in both tumor stroma (TS) and invasive margins (IM), and higher CD8+ T cells and CD79α+ B cells in the IM. Gene set enrichment analysis identified cellular stress response- and inflammation-related genes along with tumor necrosis factor receptor 1 (TNFR1) expression in high-XIAP IBC tumors. Induction of TNFR1 and XIAP was observed when patient-derived SUM149 IBC cells were co-cultured with human macrophage-conditioned media simulating TAMs, further demonstrating that the TNF-α signaling pathway is a likely candidate governing TAM-induced XIAP overexpression in IBC cells. Finally, addition of Birinapant, a pan IAP antagonist, induced cell death in the pro-survival cytokine-enriched conditions. CONCLUSION: Using immunophenotyping and gene expression analysis in patient biospecimens along with in silico modeling and a preclinical model with a pan-IAP antagonist, this study revealed an interplay between increased TAMs, TNF-α signaling, and XIAP activation during (immune) stress in IBC. These data demonstrate the potential of IAP antagonists as immunomodulators for improving IBC therapeutic regimens.

Predicting early breast cancer recurrence from histopathological images in the Carolina Breast Cancer Study.

Approaches for rapidly identifying patients at high risk of early breast cancer recurrence are needed. Image-based methods for prescreening hematoxylin and eosin (H&E) stained tumor slides could offer temporal and financial efficiency. We evaluated a data set of 704 1-mm tumor core H&E images (2-4 cores per case), corresponding to 202 participants (101 who recurred; 101 non-recurrent matched on age and follow-up time) from breast cancers diagnosed between 2008-2012 in the Carolina Breast Cancer Study. We leveraged deep learning to extract image information and trained a model to identify recurrence. Cross-validation accuracy for predicting recurrence was 62.4% [95% CI: 55.7, 69.1], similar to grade (65.8% [95% CI: 59.3, 72.3]) and ER status (66.3% [95% CI: 59.8, 72.8]). Interestingly, 70% (19/27) of early-recurrent low-intermediate grade tumors were identified by our image model. Relative to existing markers, image-based analyses provide complementary information for predicting early recurrence.

Growth Dynamics of Ductal Carcinoma in Situ Recapitulate Normal Breast Development.

Ductal carcinoma in situ (DCIS) and invasive breast cancer share many morphologic, proteomic, and genomic alterations. Yet in contrast to invasive cancer, many DCIS tumors do not progress and may remain indolent over decades. To better understand the heterogenous nature of this disease, we reconstructed the growth dynamics of 18 DCIS tumors based on the geo-spatial distribution of their somatic mutations. The somatic mutation topographies revealed that DCIS is multiclonal and consists of spatially discontinuous subclonal lesions. Here we show that this pattern of spread is consistent with a new 'Comet' model of DCIS tumorigenesis, whereby multiple subclones arise early and nucleate the buds of the growing tumor. The discontinuous, multiclonal growth of the Comet model is analogous to the branching morphogenesis of normal breast development that governs the rapid expansion of the mammary epithelium during puberty. The branching morphogenesis-like dynamics of the proposed Comet model diverges from the canonical model of clonal evolution, and better explains observed genomic spatial data. Importantly, the Comet model allows for the clinically relevant scenario of extensive DCIS spread, without being subjected to the selective pressures of subclone competition that promote the emergence of increasingly invasive phenotypes. As such, the normal cell movement inferred during DCIS growth provides a new explanation for the limited risk of progression in DCIS and adds biologic rationale for ongoing clinical efforts to reduce DCIS overtreatment.

Differential distribution of actual and surrogate oncotype DX recurrence scores in breast cancer patients by age, menopausal status, race, and body mass index.

PURPOSE: The Oncotype DX Recurrence Score (RS) is a widely used prognostic tool for estrogen receptor-positive breast cancer patients. Multiple surrogate models can predict RS with good accuracy. In this study we aimed to determine whether the RS and two surrogate indices were differentially distributed by age, menopausal status, race, and body mass index (BMI). METHODS: 516 breast cancer cases treated at a single institution were analyzed. Epidemiologic data, RS, tumor size, grade, and biomarker data were abstracted. Breast Cancer Prognostic Score (BCPS) and modified Magee equation 2 were used to calculate surrogate RS. Patients were stratified into different groups based on age, menopausal status, race, BMI, or a combination of strata. Mean and standard deviation were calculated for each group/subgroup. RESULTS: Age below median (< 63) was associated with higher RS, especially in obese and Black patients. RS was also higher in obese and Black patients in the premenopausal subgroup. Black patients had a higher RS compared to White women in the premenopausal and non-obese subgroups. BMI < 30 was associated with higher RS, especially in older, postmenopausal, and Black patients. Some of these observations were replicated by the two surrogate models. The surrogate recurrence scores were higher in the younger age group, in non-obese older/postmenopausal women, and in younger/premenopausal obese individuals. CONCLUSIONS: Higher RS was observed in younger and premenopausal breast cancer patients, especially among the Black and obese subgroups, and in non-obese patients, especially among Black and older/postmenopausal women, suggesting more aggressive disease in these subgroups. Some statistical differences could be replicated by both surrogate models, suggesting that they may have utility in breast cancer epidemiology studies that do not have access to Oncotype DX RS or patient outcome data.

Reproducibility and intratumoral heterogeneity of the PAM50 breast cancer assay.

BACKGROUND: The PAM50 assay is used routinely in clinical practice to determine breast cancer prognosis and management; however, research assessing how technical variation and intratumoral heterogeneity contribute to misclassification and reproducibility of these tests is limited. METHODS: We evaluated the impact of intratumoral heterogeneity on the reproducibility of results for the PAM50 assay by testing RNA extracted from formalin-fixed paraffin embedded breast cancer blocks sampled at distinct spatial locations. Samples were classified according to intrinsic subtype (Luminal A, Luminal B, HER2-enriched, Basal-like, or Normal-like) and risk of recurrence with proliferation score (ROR-P, high, medium, or low). Intratumoral heterogeneity and technical reproducibility (replicate assays on the same RNA) were assessed as percent categorical agreement between paired intratumoral and replicate samples. Euclidean distances between samples, calculated across the PAM50 genes and the ROR-P score, were compared for concordant vs. discordant samples. RESULTS: Technical replicates (N = 144) achieved 93% agreement for ROR-P group and 90% agreement on PAM50 subtype. For spatially distinct biological replicates (N = 40 intratumoral replicates), agreement was lower (81% for ROR-P and 76% for PAM50 subtype). The Euclidean distances between discordant technical replicates were bimodal, with discordant samples showing higher Euclidian distance and biologic heterogeneity. CONCLUSION: The PAM50 assay achieved very high technical reproducibility for breast cancer subtyping and ROR-P, but intratumoral heterogeneity is revealed by the assay in a small proportion of cases.

Race-Related Differences in the Clinical Presentation and Histopathologic Features of Phyllodes Tumor.

BACKGROUND: Phyllodes tumor (PT) is a rare fibroepithelial lesion of the breast with variable malignant potential. Black women have a higher incidence of a related benign tumor, fibroadenoma, but there are limited epidemiological data on PT. The aim of our study was to evaluate race-related differences in the clinicopathologic features and outcomes of PT. METHODS: Our institutional pathology database was queried for breast specimen reports from 01/2009 to 10/2019 to identify patients with a pathologic diagnosis of PT. Chart review and detailed slide review were performed to obtain clinical and histopathologic variables, respectively. RESULTS: Among twelve patients, two had malignant PT, three had borderline PT, and seven had benign PT. All patients with malignant and borderline PT were black, compared with 29% of those with benign PT. There were no apparent race-related differences in specific histopathologic features among black vs. non-black women with benign PT. Malignant and borderline PT were relatively larger than benign PT, with mean tumor sizes of 9.0 cm (standard deviation [SD] 4.7 cm), 12.2 cm (SD 9.4 cm), and 5.4 cm (SD 5.8 cm), respectively. Two women had a local recurrence, both of whom were black. DISCUSSION: In this single-institution retrospective study, we observed disproportionate rates of aggressive histopathologic features and disparate outcomes among black women with PT. A multi-institutional PT registry would facilitate improved knowledge about race-related differences in the presentation and outcomes of this rare tumor.

Stromal androgen signaling acts as tumor niches to drive prostatic basal epithelial progenitor-initiated oncogenesis.

The androgen receptor (AR)-signaling pathways are essential for prostate tumorigenesis. Although significant effort has been devoted to directly targeting AR-expressing tumor cells, these therapies failed in most prostate cancer patients. Here, we demonstrate that loss of AR in stromal sonic-hedgehog Gli1-lineage cells diminishes prostate epithelial oncogenesis and tumor development using in vivo assays and mouse models. Single-cell RNA sequencing and other analyses identified a robust increase of insulin-like growth factor (IGF) binding protein 3 expression in AR-deficient stroma through attenuation of AR suppression on Sp1-regulated transcription, which further inhibits IGF1-induced Wnt/ß-catenin activation in adjacent basal epithelial cells and represses their oncogenic growth and tumor development. Epithelial organoids from stromal AR-deficient mice can regain IGF1-induced oncogenic growth. Loss of human prostate tumor basal cell signatures reveals in basal cells of stromal AR-deficient mice. These data demonstrate a distinct mechanism for prostate tumorigenesis and implicate co-targeting stromal and epithelial AR-signaling for prostate cancer.

Gene expression signatures of individual ductal carcinoma in situ lesions identify processes and biomarkers associated with progression towards invasive ductal carcinoma.

Ductal carcinoma in situ (DCIS) is considered a non-invasive precursor to breast cancer, and although associated with an increased risk of developing invasive disease, many women with DCIS will never progress beyond their in situ diagnosis. The path from normal duct to invasive ductal carcinoma (IDC) is not well understood, and efforts to do so are hampered by the substantial heterogeneity that exists between patients, and even within patients. Here we show gene expression analysis from > 2,000 individually micro-dissected ductal lesions representing 145 patients. Combining all samples into one continuous trajectory we show there is a progressive loss in basal layer integrity heading towards IDC, coupled with two epithelial to mesenchymal transitions, one early and a second coinciding with the convergence of DCIS and IDC expression profiles. We identify early processes and potential biomarkers, including CAMK2N1, MNX1, ADCY5, HOXC11 and ANKRD22, whose reduced expression is associated with the progression of DCIS to invasive breast cancer.

Pathobiologic Stratification of Oncotype DX Recurrence Scores and Comparative Validation of 3 Surrogate Models.

CONTEXT.­: The Oncotype DX Recurrence Score (RS) predicts recurrence and chemotherapy benefit in early-stage estrogen receptor-positive breast cancer patients. Cost and unavailability are 2 major disadvantages of the assay. Multiple models have been developed to predict the RS. OBJECTIVE.­: To predict RS based on histopathologic and biomarker features, and to measure concordance and correlation with RS of the following 3 algorithms: breast cancer prognostic score, Magee0, and Magee2. DESIGN.­: Breast cancer cases with available RSs were reviewed (n = 442). RS categories were stratified by pathologic and biomarker variables. Histopathologic and biomarker data were abstracted from pathology reports, and RS was calculated by each model. Correlation and concordance between models and RS were calculated. RESULTS.­: Less than 5% of breast cancers with lobular features, low-grade tumors, carcinomas with high progesterone receptor content, or luminal A tumors had an RS greater than 25. Breast cancer prognostic score, Magee0, and Magee2 demonstrated correlation coefficients with RS of 0.63, 0.61, and 0.62, respectively. Two-step discordances were uncommon. When an RS of 25 was used to separate high-risk from non-high-risk cases, concordance rates of 86% to 88% were achieved. CONCLUSIONS.­: High RS was observed only in a small percentage of pure or mixed lobular carcinomas, low-grade or luminal A tumors, and tumors with high progesterone receptor expression, suggesting that these cancers may not require Oncotype testing. All 3 surrogate models demonstrated comparable correlation and high concordance with the RS when a cutoff of 25 was used, suggesting their utility in cases where the actual RS is unavailable.

Expression of X-Linked Inhibitor of Apoptosis Protein (XIAP) in Breast Cancer Is Associated with Shorter Survival and Resistance to Chemotherapy.

XIAP, the most potent inhibitor of cell death pathways, is linked to chemotherapy resistance and tumor aggressiveness. Currently, multiple XIAP-targeting agents are in clinical trials. However, the characterization of XIAP expression in relation to clinicopathological variables in large clinical series of breast cancer is lacking. We retrospectively analyzed non-metastatic, non-inflammatory, primary, invasive breast cancer samples for XIAP mRNA (n = 2341) and protein (n = 367) expression. XIAP expression was analyzed as a continuous value and correlated with clinicopathological variables. XIAP mRNA expression was heterogeneous across samples and significantly associated with younger patients' age (≤50 years), pathological ductal type, lower tumor grade, node-positive status, HR+/HER2- status, and PAM50 luminal B subtype. Higher XIAP expression was associated with shorter DFS in uni- and multivariate analyses in 909 informative patients. Very similar correlations were observed at the protein level. This prognostic impact was significant in the HR+/HER2- but not in the TN subtype. Finally, XIAP mRNA expression was associated with lower pCR rate to anthracycline-based neoadjuvant chemotherapy in both uni- and multivariate analyses in 1203 informative patients. Higher XIAP expression in invasive breast cancer is independently associated with poorer prognosis and resistance to chemotherapy, suggesting the potential therapeutic benefit of targeting XIAP.

Outcomes of Hormone-Receptor Positive, HER2-Negative Breast Cancers by Race and Tumor Biological Features.

Background: Black women have higher hormone receptor positive (HR+) breast cancer mortality than White women. Early recurrence rates differ by race, but little is known about genomic predictors of early recurrence among HR+ women. Methods: Using data from the Carolina Breast Cancer Study (phase III, 2008-2013), we estimated associations between race and recurrence among nonmetastatic HR+/HER2-negative tumors, overall and by PAM50 Risk of Recurrence score, PAM50 intrinsic subtype, and tumor grade using survival curves and Cox models standardized for age and stage. Relative frequency differences (RFD) were estimated using multivariable linear regression. To assess intervention opportunities, we evaluated treatment patterns by race among patients with high-risk disease. Results: Black women had higher recurrence risk relative to White women (crude hazard ratio = 1.81, 95% confidence interval [CI] = 1.34 to 2.46), which remained elevated after standardizing for clinical covariates (hazard ratio = 1.42, 95% CI = 1.05 to 1.93). Racial disparities were most pronounced among those with high PAM50 Risk of Recurrence score (5-year standardized recurrence risk = 18.9%, 95% CI = 8.6% to 29.1% in Black women vs 12.5%, 95% CI = 2.0% to 23.0% in White women) and high grade (5-year standardized recurrence risk = 16.6%, 95% CI = 11.7% to 21.5% in Black women vs 12.0%, 95% CI = 7.3% to 16.7% in White women). However, Black women with high-grade tumors were statistically significantly less likely to initiate endocrine therapy (RFD = -8.3%, 95% CI = -15.9% to -0.6%) and experienced treatment delay more often than White women (RFD = +9.0%, 95% CI = 0.3% to 17.8%). Conclusions: Differences in recurrence by race appear greatest among women with aggressive tumors and may be influenced by treatment differences. Efforts to identify causes of variation in cancer treatment are critical to reducing outcome disparities.

JOINT AND INDIVIDUAL ANALYSIS OF BREAST CANCER HISTOLOGIC IMAGES AND GENOMIC COVARIATES.

The two main approaches in the study of breast cancer are histopathology (analyzing visual characteristics of tumors) and genomics. While both histopathology and genomics are fundamental to cancer research, the connections between these fields have been relatively superficial. We bridge this gap by investigating the Carolina Breast Cancer Study through the development of an integrative, exploratory analysis framework. Our analysis gives insights - some known, some novel - that are engaging to both pathologists and geneticists. Our analysis framework is based on Angle-based Joint and Individual Variation Explained (AJIVE) for statistical data integration and exploits Convolutional Neural Networks (CNNs) as a powerful, automatic method for image feature extraction. CNNs raise interpretability issues that we address by developing novel methods to explore visual modes of variation captured by statistical algorithms (e.g. PCA or AJIVE) applied to CNN features.

Spatiotemporal strategies to identify aggressive biology in precancerous breast biopsies.

Over 90% of breast cancer is cured; yet there remain highly aggressive breast cancers that develop rapidly and are extremely difficult to treat, much less prevent. Breast cancers that rapidly develop between breast image screening are called "interval cancers." The efforts of our team focus on identifying multiscale integrated strategies to identify biologically aggressive precancerous breast lesions. Our goal is to identify spatiotemporal changes that occur prior to development of interval breast cancers. To accomplish this requires integration of new technology. Our team has the ability to perform single cell in situ transcriptional profiling, noncontrast biological imaging, mathematical analysis, and nanoscale evaluation of receptor organization and signaling. These technological innovations allow us to start to identify multidimensional spatial and temporal relationships that drive the transition from biologically aggressive precancer to biologically aggressive interval breast cancer. This article is categorized under: Cancer > Computational Models Cancer > Molecular and Cellular Physiology Cancer > Genetics/Genomics/Epigenetics.

Quantitative assessment of distant recurrence risk in early stage breast cancer using a nonlinear combination of pathological, clinical and imaging variables.

Use of genomic assays to determine distant recurrence risk in patients with early stage breast cancer has expanded and is now included in the American Joint Committee on Cancer staging manual. Algorithmic alternatives using standard clinical and pathology information may provide equivalent benefit in settings where genomic tests, such as OncotypeDx, are unavailable. We developed an artificial neural network (ANN) model to nonlinearly estimate risk of distant cancer recurrence. In addition to clinical and pathological variables, we enhanced our model using intraoperatively determined global mammographic breast density (MBD) and local breast density (LBD). LBD was measured with optical spectral imaging capable of sensing regional concentrations of tissue constituents. A cohort of 56 ER+ patients with an OncotypeDx score was evaluated. We demonstrated that combining MBD/LBD measurements with clinical and pathological variables improves distant recurrence risk prediction accuracy, with high correlation (r = 0.98) to the OncotypeDx recurrence score.

Androgen receptor with short polyglutamine tract preferably enhances Wnt/ß-catenin-mediated prostatic tumorigenesis.

Polyglutamine (polyQ) tract polymorphism within the human androgen receptor (AR) shows population heterogeneity. African American men possess short polyQ tracts significantly more frequently than Caucasian American men. The length of polyQ tracts is inversely correlated with the risk of prostate cancer, age of onset, and aggressiveness at diagnosis. Aberrant activation of Wnt signaling also reveals frequently in advanced prostate cancer, and an enrichment of androgen and Wnt signaling activation has been observed in African American patients. Here, we assessed aberrant expression of AR bearing different polyQ tracts and stabilized ß-catenin in prostate tumorigenesis using newly generated mouse models. We observed an early onset oncogenic transformation, accelerated tumor cell growth, and aggressive tumor phenotypes in the compound mice bearing short polyQ tract AR and stabilized ß-catenin. RNA sequencing analysis showed a robust enrichment of Myc-regulated downstream genes in tumor samples bearing short polyQ AR versus those with longer polyQ tract AR. Upstream regulator analysis further identified Myc as the top candidate of transcriptional regulators in tumor cells from the above mouse samples with short polyQ tract AR and ß-catenin. Chromatin immunoprecipitation analyses revealed increased recruitment of ß-catenin and AR on the c-Myc gene regulatory locus in the tumor tissues expressing stabilized ß-catenin and shorter polyQ tract AR. These data demonstrate a promotional role of aberrant activation of Wnt/ß-catenin in combination with short polyQ AR expression in prostate tumorigenesis and suggest a potential mechanism underlying aggressive prostatic tumor development, which has been frequently observed in African American patients.

DNA methylation markers predict recurrence-free interval in triple-negative breast cancer.

We lack tools to risk-stratify triple-negative breast cancer (TNBC). Our goal was to develop molecular tools to predict disease recurrence. Methylation array analysis was performed on 110 samples treated by locoregional therapy obtained from institutional cohorts. Discovered marker sets were then tested by Kaplan-Meier analyses in a prospectively collected TNBC cohort of 49 samples from the no-chemotherapy arms of IBCSG trials VIII and IX, and by logistic regression in a chemotherapy-treated cohort of 121 TNBCs from combined IBCSG trials and institutional repositories. High methylation was associated with shorter recurrence-free interval in the no-chemotherapy arm of the IBCSG studies, as well as in the chemotherapy-treated patients within the combined institutional and IBCSG chemotherapy cohorts (100 marker panel, p = 0.002; 30 marker panel, p = 0.05). Chromosome 19 sites were enriched among these loci. In conclusion, our hypermethylation signatures identify increased recurrence risk independent of whether patients receive chemotherapy.

Loss of androgen signaling in mesenchymal sonic hedgehog responsive cells diminishes prostate development, growth, and regeneration.

Prostate embryonic development, pubertal and adult growth, maintenance, and regeneration are regulated through androgen signaling-mediated mesenchymal-epithelial interactions. Specifically, the essential role of mesenchymal androgen signaling in the development of prostate epithelium has been observed for over 30 years. However, the identity of the mesenchymal cells responsible for this paracrine regulation and related mechanisms are still unknown. Here, we provide the first demonstration of an indispensable role of the androgen receptor (AR) in sonic hedgehog (SHH) responsive Gli1-expressing cells, in regulating prostate development, growth, and regeneration. Selective deletion of AR expression in Gli1-expressing cells during embryogenesis disrupts prostatic budding and impairs prostate development and formation. Tissue recombination assays showed that urogenital mesenchyme (UGM) containing AR-deficient mesenchymal Gli1-expressing cells combined with wildtype urogenital epithelium (UGE) failed to develop normal prostate tissue in the presence of androgens, revealing the decisive role of AR in mesenchymal SHH responsive cells in prostate development. Prepubescent deletion of AR expression in Gli1-expressing cells resulted in severe impairment of androgen-induced prostate growth and regeneration. RNA-sequencing analysis showed significant alterations in signaling pathways related to prostate development, stem cells, and organ morphogenesis in AR-deficient Gli1-expressing cells. Among these altered pathways, the transforming growth factor ß1 (TGFß1) pathway was up-regulated in AR-deficient Gli1-expressing cells. We further demonstrated the activation of TGFß1 signaling in AR-deleted prostatic Gli1-expressing cells, which inhibits prostate epithelium growth through paracrine regulation. These data demonstrate a novel role of the AR in the Gli1-expressing cellular niche for regulating prostatic cell fate, morphogenesis, and renewal, and elucidate the mechanism by which mesenchymal androgen-signaling through SHH-responsive cells elicits the growth and regeneration of prostate epithelium.

Bimodal age distribution at diagnosis in breast cancer persists across molecular and genomic classifications.

PURPOSE: Female breast cancer demonstrates bimodal age frequency distribution patterns at diagnosis, interpretable as two main etiologic subtypes or groupings of tumors with shared risk factors. While RNA-based methods including PAM50 have identified well-established clinical subtypes, age distribution patterns at diagnosis as a proxy for etiologic subtype are not established for molecular and genomic tumor classifications. METHODS: We evaluated smoothed age frequency distributions at diagnosis for Carolina Breast Cancer Study cases within immunohistochemistry-based and RNA-based expression categories. Akaike information criterion (AIC) values compared the fit of single density versus two-component mixture models. Two-component mixture models estimated the proportion of early-onset and late-onset categories by immunohistochemistry-based ER (n = 2860), and by RNA-based ESR1 and PAM50 subtype (n = 1965). PAM50 findings were validated using pooled publicly available data (n = 8103). RESULTS: Breast cancers were best characterized by bimodal age distribution at diagnosis with incidence peaks near 45 and 65 years, regardless of molecular characteristics. However, proportional composition of early-onset and late-onset age distributions varied by molecular and genomic characteristics. Higher ER-protein and ESR1-RNA categories showed a greater proportion of late age-at-onset. Similarly, PAM50 subtypes showed a shifting age-at-onset distribution, with most pronounced early-onset and late-onset peaks found in Basal-like and Luminal A, respectively. CONCLUSIONS: Bimodal age distribution at diagnosis was detected in the Carolina Breast Cancer Study, similar to national cancer registry data. Our data support two fundamental age-defined etiologic breast cancer subtypes that persist across molecular and genomic characteristics. Better criteria to distinguish etiologic subtypes could improve understanding of breast cancer etiology and contribute to prevention efforts.

Borderline Estrogen Receptor-Positive Breast Cancers in Black and White Women.

BACKGROUND: Some breast tumors expressing greater than 1% and less than 10% estrogen receptor (ER) positivity (ER-borderline) are clinically aggressive; others exhibit luminal biology. Prior ER-borderline studies included few black participants. METHODS: Using the Carolina Breast Cancer Study (phase I: 1993-1996; 2: 1996-2001; 3: 2008-2013), a population-based study that oversampled black women, we compared ER-borderline (n = 217) to ER-positive (n = 1885) and ER-negative (n = 757) tumors. PAM50 subtype and risk of recurrence score (ROR-PT, incorporates subtype, proliferation, tumor size) were measured. Relative frequency differences (RFD) were estimated using multivariable linear regression. Disease-free interval (DFI) was evaluated by ER category and endocrine therapy receipt, overall and by race, using Kaplan Meier and Cox models. Statistical tests were two-sided. RESULTS: ER-borderlines were more frequently basal-like (RFD = +37.7%, 95% confidence interval [CI] = 27.1% to 48.4%) and high ROR-PT (RFD = +52.4%, 95% CI = 36.8% to 68.0%) relative to ER-positives. Having a high ROR-PT ER-borderline tumor was statistically significantly associated with black race (RFD = +26.2%, 95% CI = 9.0% to 43.3%). Compared to ER-positives, DFI of ER-borderlines treated with endocrine therapy was poorer but not statistically significantly different (hazard ratio [HR] = 2.03, 95% CI = 0.89% to 4.65%), whereas DFI was statistically significantly worse for ER-borderlines without endocrine therapy (HR = 3.33, 95% CI = 1.84% to 6.02%). However, black women with ER-borderline had worse DFI compared to ER-positives, even when treated with endocrine therapy (HR = 2.77, 95% CI = 1.09% to 7.04%). CONCLUSIONS: ER-borderline tumors were genomically heterogeneous, with survival outcomes that differed by endocrine therapy receipt and race. Black race predicted high-risk ER-borderlines and may be associated with poorer endocrine therapy response.