McGee EE, Kim CH, Wang M, Spiegelman D, Stover DG, Heng YJ, Collins LC, Baker GM, Farvid MS, Schedin P, et al. Erythrocyte membrane fatty acids and breast cancer risk by tumor tissue expression of immuno-inflammatory markers and fatty acid synthase: a nested case-control study. Breast Can Res. 2020;22 :78.
DuPre NC, Heng YJ, Raby BA, Glass K, Hart JE, Hu JC, Askew C, Eliassen AH, Hankinson SE, Kraft P, et al. Involvement of fine particulate matter exposure with gene expression pathways in breast tumor and adjacent-normal breast tissue. Environ Res. 2020;186 :109535.
Peng C, Heng YJ, Lu D, DuPre NC, Kensler KH, Glass K, Zeleznik OA, Kraft P, Feldman D, Hankinson SE, et al. Pre-diagnostic 25-hydroxyvitamin D concentrations in relation to tumor molecular alterations and risk of breast cancer recurrence. Cancer Epidemiol Biomarkers Prev. 2020;29 (6) :1253-1263.
Heng YJ, Hankinson SE, Wang J, Alexandrov LB, Ambrosone CB, de Andrade VP, Brufsky AM, Couch FJ, King TA, Modugno F, et al. The association of modifiable breast cancer risk factors and somatic genomic alterations in breast tumors: The Cancer Genome Atlas Network. Cancer Epidemiol Biomarkers Prev. 2020;29 (3) :599-605.
Wetstein SC, Onken AM, Luffman C, Baker GM, Pyle ME, Kensler KH, Liu Y, Bakker B, Vlutters R, van Leeuwen MB, et al. Deep learning assessment of breast terminal duct lobular unit involution: towards automated prediction of breast cancer risk. PLoS ONE. 2020;15 (4) :e0231653. Publisher's Version
Eismann J, Heng YJ, Waldschmidt JM, Vlachos IS, Gray K, Matulonis U, Konstantinopoulos PA, Murphy CJ, Nabavi S, Wulf GM. Transcriptome analysis reveals overlap in fusion genes in a phase I clinical cohort of TNBC and HGSOC patients treated with buparlisib and olaparib. J Cancer Res Clin Oncol. 2020;146 :503–514.
Zhou G, Holzman C, Heng YJ, Kibshull M, Lye SJ, Vazquez A. EBF1 gene mRNA levels in maternal blood and spontaneous preterm birth. Reprod Sci. 2020;27 (1) :316-324.
Baker GM, Pyle ME, Tobias AM, Bartlett RA, Phillips J, Fein-Zachary VJ, Wulf GM, Heng YJ. Establishing a cohort of transgender men and gender nonconforming individuals to understand the molecular impact of testosterone on breast physiology. Transgender Health. 2019;4 (1) :326-330.
Tian K, Rubadue CA, Lin DI, Veta M, Pyle ME, Irshad H, Heng YJ. Automated Clear Cell Renal Carcinoma Grade Classification with Prognostic Significance. PLoS ONE. 2019;14 (10) :e0222641. Publisher's Version
Campbell PT, Ambrosone CB, Nishihara R, Aerts HJ, Bondy M, Chatterjee N, Garcia-Closas M, Giannakis M, Golden JA, Heng YJ, et al. Proceedings of the fourth international molecular pathological epidemiology (MPE) meeting. Cancer Causes Control. 2019;30 (8) :799-811.
Wetstein SC, Onken AM, Baker GM, Pyle ME, Pluim JPW, Tamimi RM, Heng YJ, Veta M. Detection of acini in histopathology slides: towards automated prediction of breast cancer risk, in SPIE Medical Imaging. Vol 10956. San Diego, CA: SPIE ; 2019 :109560Q. Publisher's VersionAbstract
Terminal duct lobular units (TDLUs) are structures in the breast which involute with the completion of childbearing and physiological ageing. Women with less TDLU involution are more likely to develop breast cancer than those with more involution. Thus, TDLU involution may be utilized as a biomarker to predict invasive cancer risk. Manual assessment of TDLU involution is a cumbersome and subjective process. This makes it amenable for automated assessment by image analysis. In this study, we developed and evaluated an acini detection method as a first step towards automated assessment of TDLU involution using a dataset of histopathological whole-slide images (WSIs) from the Nurses’ Health Study (NHS) and NHSII. The NHS/NHSII is among the world's largest investigations of epidemiological risk factors for major chronic diseases in women. We compared three different approaches to detect acini in WSIs using the U-Net convolutional neural network architecture. The approaches differ in the target that is predicted by the network: circular mask labels, soft labels and distance maps. Our results showed that soft label targets lead to a better detection performance than the other methods. F1 scores of 0.65, 0.73 and 0.66 were obtained with circular mask labels, soft labels and distance maps, respectively. Our acini detection method was furthermore validated by applying it to measure acini count per mm2 of tissue area on an independent set of WSIs. This measure was found to be significantly negatively correlated with age.
Kensler KH, Regan MM, Heng YJ, Baker GM, Pyle ME, Schnitt SJ, Hazra A, Kammler R, Thürlimann B, Colleoni M, et al. Prognostic and predictive value of androgen receptor expression in postmenopausal women with estrogen receptor-positive breast cancer: results from the Breast International Group Trial 1–98. Breast Cancer Res. 2019;21 (1) :30. Publisher's Version
Kensler KH, Sankar VN, Wang J, Zhang X, Rubadue CA, Baker GM, Parker JS, Hoadley KA, Stancu AL, Pyle ME, et al. PAM50 Molecular Intrinsic Subtypes in the Nurses’ Health Study Cohorts. Cancer Epidemiology and Prevention Biomarkers. 2019;28 (4) :798-806. Publisher's VersionAbstract
Background: Modified median and subgroup-specific gene centering are two essential pre-processing methods to assign breast cancer molecular subtypes by PAM50. We evaluated the PAM50 subtypes derived from both methods in a subset of Nurses’ Health Study (NHS) and NHSII participants; correlated tumor subtypes by PAM50 with immunohistochemistry (IHC) surrogates; and characterized the PAM50 subtype distribution, proliferation scores and risk of relapse with proliferation and tumor size weighted (ROR-PT) scores in the NHS/NHSII. Methods: PAM50 subtypes, proliferation scores and ROR-PT scores were calculated for 882 invasive breast tumors and 695 histologically normal tumor-adjacent tissues. Cox proportional hazard models evaluated the relationship between PAM50 subtypes or ROR-PT scores/groups with recurrence free survival (RFS) or distant RFS. Results: PAM50 subtypes were highly comparable between the two methods. The agreement between tumor subtypes by PAM50 and IHC surrogates improved to fair when Luminal subtypes were grouped together. Using the modified median method, our study consisted of 46% Luminal A, 18% Luminal B, 14% HER2-enriched, 15% Basal-like and 8% Normal-like subtypes; 53% of tumor-adjacent tissues were Normal-like. Women with the Basal-like subtype had a higher rate of relapse within five years. HER2-enriched subtypes had poorer outcomes prior to 1999. Conclusions: Either pre-processing method may be utilized to derive PAM50 subtypes for future studies. The majority of NHS/NHSII tumor and tumor-adjacent tissues were classified as Luminal A and Normal-like, respectively. Impact: Pre-processing methods are important for the accurate assignment of PAM50 subtypes. These data provide evidence that either pre-processing method can be used in epidemiological studies.
Eismann J, Heng YJ, Fleischmann-Rose K, Tobias AM, Phillips J, Wulf GM, Kansal KJ. Interdisciplinary Management of Transgender Individuals at Risk for Breast Cancer: Case Reports and Review of the Literature. Clinical Breast Cancer. 2019;19 (1) :e12-e19. Publisher's Version
Kensler KH, Poole EM, Heng YJ, Collins LC, Glass B, Beck AH, Hazra A, Rosner BA, Eliassen HA, Hankinson SE, et al. Androgen Receptor Expression and Breast Cancer Survival: Results From the Nurses' Health Studies. J Natl Cancer Inst. 2019;111 (7) :700-708.Abstract
Background: Hormone receptor signaling is critical in the progression of breast cancers, although the role of the androgen receptor (AR) remains unclear, particularly for estrogen receptor (ER)-negative tumors. This study assessed AR protein expression as a prognostic marker for breast cancer mortality. Methods: This study included 4147 pre- and postmenopausal women with invasive breast cancer from the Nurses' Health Study (diagnosed 1976-2008) and Nurses' Health Study II (1989-2008) cohorts. AR protein expression was evaluated by immunohistochemistry and scored through pathologist review and as a digitally quantified continuous measure. Hazard ratios (HR) and 95% confidence intervals (CI) of breast cancer mortality were estimated from Cox proportional hazards models, adjusting for patient, tumor, and treatment covariates. Results: Over a median 16.5 years of follow-up, there were 806 deaths due to breast cancer. In the 7 years following diagnosis, AR expression was associated with a 27% reduction in breast cancer mortality overall (multivariable HR = 0.73, 95% CI = 0.58 to 0.91) a 47% reduction for ER+ cancers (HR = 0.53, 95% CI = 0.41 to 0.69), and a 62% increase for ER- cancers (HR = 1.62, 95% CI = 1.18 to 2.22) (P heterogeneity < .001). A log-linear association was observed between AR expression and breast cancer mortality among ER- cancers (HR = 1.14, 95% CI = 1.02 to 1.26 per each 10% increase in AR), although no log-linear association was observed among ER+ cancers. Conclusions: AR expression was associated with improved prognosis in ER+ tumors and worse prognosis in ER- tumors in the first 5-10 years postdiagnosis. These findings support the continued evaluation of AR-targeted therapies for AR+/ER- breast cancers.
Heng YJ, Wang J, Ahearn TU, Brown SB, Zhang X, Ambrosone CB, de Andrade VP, Brufsky AM, Couch FJ, King TA, et al. Molecular mechanisms linking high body mass index to breast cancer etiology in post-menopausal breast tumor and tumor-adjacent tissues. Breast Cancer Res Treat. 2019;173 (3) :667-77. Publisher's VersionAbstract
In post-menopausal women, high body mass index (BMI) is an established breast cancer risk factor and is associated with worse breast cancer prognosis. We assessed the associations between BMI and gene expression of both breast tumor and adjacent tissue in estrogen receptor-positive (ER+) and estrogen receptor-negative (ER−) diseases to help elucidate the mechanisms linking obesity with breast cancer biology in 519 post-menopausal women from the Nurses’ Health Study (NHS) and NHSII.
Veta M, Heng YJ, Stathonikos N, Ehteshami Bejnordi B, Beca F, Wollmann T, Rohr K, Shah MA, Wang D, Rousson M, et al. Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge. Med Image Anal. 2019;54 :111-121.
Kensler KH, Beca F, Baker GM, Heng YJ, Beck AH, Schnitt SJ, Hazra A, Rosner BA, Eliassen HA, Hankinson SE, et al. Androgen receptor expression in normal breast tissue and subsequent breast cancer risk. NPJ Breast Cancer. 2018;4 :33.Abstract
Sex steroid hormone signaling is critical in the development of breast cancers, although the role of the androgen receptor remains unclear. This study evaluated androgen receptor (AR) expression in normal breast tissue as a potential marker of breast cancer risk. We conducted a nested case-control study of women with benign breast disease (BBD) within the Nurses' Health Studies. Epithelial AR expression was assessed by immunohistochemistry in normal tissue from the BBD biopsy and the percent of positive nuclei was estimated in ordinal categories of 10% for 78 breast cancer cases and 276 controls. Logistic regression models adjusting for the matching factors and BBD lesion type were used to calculate odds ratios (ORs) for the association between AR expression (tertiles: ≤10%, 11-30%, and >30%) and breast cancer risk. AR expression in normal breast tissue was not associated with subsequent breast cancer risk (OR = 0.9, 95% CI = 0.4-1.8, trend = 0.68). In comparison with low AR/low ER women, ORs of 0.4 (95% CI = 0.1-1.2) for high AR/high ER women, 1.8 (95% CI = 0.4-7.8) for low AR/high ER women, and 0.7 (95% CI = 0.3-1.6) for high AR/low ER women were observed ( interaction = 0.21). Ki67 did not modify the association between AR expression and breast cancer risk ( interaction = 0.75). There was little evidence for an overall association between AR expression in normal breast tissue and breast cancer risk. These findings did not show that the AR association varied by Ki67 expression in normal breast tissue, though there was suggestive heterogeneity by ER expression.
Sonzogni O, Haynes J, Seifried LA, Kamel YM, Huang K, BeGora MD, Yeung FA, Robert-Tissot C, Heng YJ, Yuan X, et al. Reporters to mark and eliminate basal or luminal epithelial cells in culture and in vivo. PLoS Biol. 2018;16 (6) :e2004049.Abstract
The contribution of basal and luminal cells to cancer progression and metastasis is poorly understood. We report generation of reporter systems driven by either keratin-14 (K14) or keratin-8 (K8) promoter that not only express a fluorescent protein but also an inducible suicide gene. Transgenic mice express the reporter genes in the right cell compartments of mammary gland epithelia and respond to treatment with toxins. In addition, we engineered the reporters into 4T1 metastatic mouse tumor cell line and demonstrate that K14+ cells, but not K14- or K8+, are both highly invasive in three-dimensional (3D) culture and metastatic in vivo. Treatment of cells in culture, or tumors in mice, with reporter-targeting toxin inhibited both invasive behavior and metastasis in vivo. RNA sequencing (RNA-seq), secretome, and epigenome analysis of K14+ and K14- cells led to the identification of amphoterin-induced protein 2 (Amigo2) as a new cell invasion driver whose expression correlated with decreased relapse-free survival in patients with TP53 wild-type (WT) breast cancer.
Wang J, Heng YJ, Eliassen HA, Tamimi RM, Hazra A, Carey VJ, Ambrosone CB, de Andrade VP, Brufsky A, Couch FJ, et al. Alcohol consumption and breast tumor gene expression. Breast Cancer Res. 2017;19 (1) :108.Abstract
BACKGROUND: Alcohol consumption is an established risk factor for breast cancer and the association generally appears stronger among estrogen receptor (ER)-positive tumors. However, the biological mechanisms underlying this association are not completely understood. METHODS: We analyzed messenger RNA (mRNA) microarray data from both invasive breast tumors (N = 602) and tumor-adjacent normal tissues (N = 508) from participants diagnosed with breast cancer in the Nurses' Health Study (NHS) and NHSII. Multivariable linear regression, controlling for other known breast cancer risk factors, was used to identify differentially expressed genes by pre-diagnostic alcohol intake. For pathway analysis, we performed gene set enrichment analysis (GSEA). Differentially expressed genes or enriched pathway-defined gene sets with false discovery rate (FDR) <0.1 identified in tumors were validated in RNA sequencing data of invasive breast tumors (N = 166) from The Cancer Genome Atlas. RESULTS: No individual genes were significantly differentially expressed by alcohol consumption in the NHS/NHSII. However, GSEA identified 33 and 68 pathway-defined gene sets at FDR <0.1 among 471 ER+ and 127 ER- tumors, respectively, all of which were validated. Among ER+ tumors, consuming 10+ grams of alcohol per day (vs. 0) was associated with upregulation in RNA metabolism and transport, cell cycle regulation, and DNA repair, and downregulation in lipid metabolism. Among ER- tumors, in addition to upregulation in RNA processing and cell cycle, alcohol intake was linked to overexpression of genes involved in cytokine signaling, including interferon and transforming growth factor (TGF)-β signaling pathways, and translation and post-translational modifications. Lower lipid metabolism was observed in both ER+ tumors and ER+ tumor-adjacent normal samples. Most of the significantly enriched gene sets identified in ER- tumors showed a similar enrichment pattern among ER- tumor-adjacent normal tissues. CONCLUSIONS: Our data suggest that moderate alcohol consumption (i.e. 10+ grams/day, equivalent to one or more drinks/day) is associated with several specific and reproducible biological processes and pathways, which adds potential new insight into alcohol-related breast carcinogenesis.