乳房癌风险生物标记物在良性乳房样本(BBS)中的验证一直是一个长追求的目标，但由于基因和蛋白质表达随月经周期(MP)和绝经状态(MS)的波动而受到限制。之前，我们确定了与激素有关的基因表达和组织形态学参数，以分类BBS按照MS/MP。现在，我们将两者结合起来进行评估，以验证我们之前的结果。BBS样本来自于同意接受减少乳房整形手术(RM)或另一侧未受影响的乳房切除术(CUB)的女性（86名绝经前，55名绝经后）。MP/MS是根据手术当天的月经日期和激素水平使用传统标准定义的。使用反转录定量聚合酶链式反应(RT-qPCR)测量了三个黄体期基因(TNFSF11、DIO2、MYBPC1)和四个绝经期基因(PGR、GREB1、TIFF1、CCND1)的BBS基因表达。使用已发表的组织形态学参数，将绝经前样本分为LP或非LP。进行逻辑回归和接收者操作特征曲线分析，以评估预测MP/MS的曲线下面积(AUC)。在全部131名女性中，绝经期基因+年龄>50岁预测真实MS [AUC 0.93，95%置信区间(CI) 0.89，0.97]。在绝经前女性中，高TNFSF11表达将非LP样本与LP样本区分开来(AUC 0.80，95% CI 0.70，0.91)；组织形态学的补充改进了预测，但没有达到显著水平(AUC 0.87，95% CI 0.78，0.96)。在绝经前的子组中，组织形态学的补充改善了在RM中LP的预测(AUC 0.95，95% CI 0.87，1.0)，但在CUB中没有改善(0.84，95% CI 0.72，0.96)。一个由五个基因组成的集合的表达准确预测了BBS中的绝经状态和月经相，有利于利用大型存档样本库开发乳腺癌风险生物标记物。©2023年。手术肿瘤学协会。

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.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.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).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.© 2023. Society of Surgical Oncology.