TY - JOUR
T1 - Menstrual Phase and Menopausal Status Classification of Benign Breast Tissue Using Hormone-Regulated Gene Expression and Histomorphology
T2 - A Validation Study
AU - Hosseini, Omid
AU - Wang, Jun
AU - Lee, Oukseub
AU - Pulliam, Natalie
AU - Mohamed, Azza
AU - Shidfar, Ali
AU - Chatterton, Robert T.
AU - Blanco, Luis
AU - Meindl, Amanda
AU - Helenowski, Irene
AU - Zhang, Hui
AU - Khan, Seema A.
N1 - Funding Information:
This study is supported by the Avon Foundation (Center of Excellence Award to Northwestern University) and the Susan G. Komen Foundation (Grant 12222783). The hormone measurements were performed by The University of Virginia Center for Research in Reproduction Ligand Assay and Analysis Core, which is supported by the Eunice Kennedy Shriver NICHD/NIH (NCTRI) Grant P50-HD28934.
Publisher Copyright:
© 2023, Society of Surgical Oncology.
PY - 2023
Y1 - 2023
N2 - Background: The validation of breast cancer risk biomarkers in benign breast samples (BBS) is a long-sought goal, hampered by the fluctuation of gene and protein expression with menstrual phase (MP) and menopausal status (MS). Previously, we identified hormone-related gene expression and histomorphology parameters to classify BBS by MS/MP. We now evaluate both together, to validate our prior results. Patients and Methods: BBS were obtained from consenting women (86 premenopausal, 55 postmenopausal) undergoing reduction mammoplasty (RM) or contralateral unaffected breast (CUB) mastectomy. MP/MS was defined using classical criteria for menstrual dates and hormone levels on the day of surgery. BBS gene expression was measured with reverse transcription quantitative polymerase chain reaction (RT-qPCR) for three luteal phase (LP) genes (TNFSF11, DIO2, MYBPC1) and four menopausal genes (PGR, GREB1, TIFF1, CCND1). Premenopausal samples were classified into LP or non-LP, using published histomorphology parameters. Logistic regression and receiver-operator curve analysis was performed to assess area under the curve (AUC) for prediction of MP/MS. Results: In all 131 women, menopausal genes plus age > 50 years predicted true MS [AUC 0.93, 95% confidence interval (CI) 0.89, 0.97]. Among premenopausal women, high TNFSF11 expression distinguished non-LP from LP samples (AUC 0.80, 95% CI 0.70, 0.91); the addition of histomorphology improved the prediction nonsignificantly (AUC 0.87, 95% CI 0.78, 0.96). In premenopausal subsets, addition of histomorphology improved LP prediction in RM (AUC 0.95, 95% CI 0.87, 1.0), but not in CUB (0.84, 95% CI 0.72, 0.96). Conclusions: Expression of five-gene set accurately predicts menopausal status and menstrual phase in BBS, facilitating the development of breast cancer risk biomarkers using large, archived sample repositories.
AB - Background: The validation of breast cancer risk biomarkers in benign breast samples (BBS) is a long-sought goal, hampered by the fluctuation of gene and protein expression with menstrual phase (MP) and menopausal status (MS). Previously, we identified hormone-related gene expression and histomorphology parameters to classify BBS by MS/MP. We now evaluate both together, to validate our prior results. Patients and Methods: BBS were obtained from consenting women (86 premenopausal, 55 postmenopausal) undergoing reduction mammoplasty (RM) or contralateral unaffected breast (CUB) mastectomy. MP/MS was defined using classical criteria for menstrual dates and hormone levels on the day of surgery. BBS gene expression was measured with reverse transcription quantitative polymerase chain reaction (RT-qPCR) for three luteal phase (LP) genes (TNFSF11, DIO2, MYBPC1) and four menopausal genes (PGR, GREB1, TIFF1, CCND1). Premenopausal samples were classified into LP or non-LP, using published histomorphology parameters. Logistic regression and receiver-operator curve analysis was performed to assess area under the curve (AUC) for prediction of MP/MS. Results: In all 131 women, menopausal genes plus age > 50 years predicted true MS [AUC 0.93, 95% confidence interval (CI) 0.89, 0.97]. Among premenopausal women, high TNFSF11 expression distinguished non-LP from LP samples (AUC 0.80, 95% CI 0.70, 0.91); the addition of histomorphology improved the prediction nonsignificantly (AUC 0.87, 95% CI 0.78, 0.96). In premenopausal subsets, addition of histomorphology improved LP prediction in RM (AUC 0.95, 95% CI 0.87, 1.0), but not in CUB (0.84, 95% CI 0.72, 0.96). Conclusions: Expression of five-gene set accurately predicts menopausal status and menstrual phase in BBS, facilitating the development of breast cancer risk biomarkers using large, archived sample repositories.
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U2 - 10.1245/s10434-023-13192-1
DO - 10.1245/s10434-023-13192-1
M3 - Article
C2 - 36856909
AN - SCOPUS:85149758582
SN - 1068-9265
JO - Annals of Surgical Oncology
JF - Annals of Surgical Oncology
ER -