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Mammography is the recommended imaging modality for breast cancer screening. Expressions of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) are critical to the development of therapeutic strategies for breast cancer. In this study, a deep learning model (CBAM ResNet-18) was developed to predict the expression of these three receptors on mammography without manual segmentation of masses. Mammography of patients with pathologically proven breast cancer was obtained from two centers. A deep learning-based model (CBAM ResNet-18) for predicting HER2, ER, and PR expressions was trained and validated using five-fold cross-validation on a training dataset. The performance of the model was further tested using an external test dataset. Area under receiver operating characteristic curve (AUC), accuracy (ACC), and F1-score were calculated to assess the ability of the model to predict each receptor. For comparison we also developed original ResNet-18 without attention module and VGG-19 with and without attention module. The AUC (95% CI), ACC, and F1-score were 0.708 (0.609, 0.808), 0.651, 0.528, respectively, in the HER2 test dataset; 0.785 (0.673, 0.897), 0.845, 0.905, respectively, in the ER test dataset; and 0.706 (0.603, 0.809), 0.678, 0.773, respectively, in the PR test dataset. The proposed model demonstrates superior performance compared to the original ResNet-18 without attention module and VGG-19 with and without attention module. The model has the potential to predict HER2, PR, and especially ER expressions, and thus serve as an adjunctive diagnostic tool for breast cancer. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the effect of quercetin on the reversal of tamoxifen resistance in breast cancer cells, and explore the underlying mechanism., Methods: We established a tamoxifen-resistant breast cancer cell line (MCF-7Ca/TAM-R), and exposed it to different concentrations of quercetin (experimental group 1: 10 μM, group 2: 25 μM, and group 3: 50μM). Each group was further subdivided into 2 subgroups: 1) simultaneous administration of quercetin and 4-hydroxytamoxifen (OHT); 2) sequential administration of quercetin (12-h induction) followed by OHT. No drug exposure and OHT alone were used as controls. We determined cell survival, apoptosis, and expression of ERα (estrogen receptor α) and Her-2 (human epidermal growth factor receptor 2)., Results: With increasing dosage of quercetin, significant decrease in proliferation and increase in apoptosis was observed. Low concentrations of quercetin (10 μM) had no effects. We found no significant difference between simultaneous and sequential mode of drug administration. Further, with increasing dosage of quercetin, we observed a gradual reduction in Her-2 expression and upregulation of ERα. Again, no difference in Her-2 and ERα protein levels between simultaneous and sequential drug administration was noticed., Conclusions: Proliferation inhibition and apoptosis in MCF-7Ca/TAM-R cells increase with increasing dosage of quercetin. This suggests that quercetin can reverse tamoxifen resistance in breast cancer cells. The underlying mechanism likely involves upregulation of ERα combined with downregulation of Her-2. However, this effect is independent of whether quercetin and tamoxifen are administered simultaneously or sequentially.