The construction and validation of a radiomics nomogram based on machine learning using magnetic resonance image (MRI) for predicting the efficacy of neoadjuvant chemotherapy (NACT) in patients with breast cancer (BCa). Methods: This retrospective investigation consisted of 158 patients who were diagnosed with BCa and underwent MRI before NACT, of which 33 patients experienced pathological complete response (pCR) by the postoperative pathological examination. The patients with BCa were divided into the training set (n = 110) and test set (n = 48) randomly. The features were selected by the maximum relevance minimum redundancy (mRMR) and absolute shrinkage and selection operator (LASSO) algorithm in the training set. In return, the radiomics signature was established using machine learning. The predictive score of each patient was calculated using the radiomics signature formula. Finally, the predictive scores and clinical factors were used to perform the multivariate logistic regression and construct the nomogram. Receiver operating characteristics (ROC) analyses were used to assess and validate the diagnostic accuracy of the nomogram in the test set. Lastly, the usefulness of the nomogram was confirmed via decision curve analysis (DCA). Results: The radiomics signature was well-discriminated in the training set [AUC 0.835, specificity 71.32%, and sensitivity 82.61%], and test set (AUC 0.834, specificity 73.21%, and sensitivity 80%). Containing the radiomics signature and hormone status, the radiomics nomogram showed good calibration and discrimination in the training set [AUC 0.888, specificity 79.31%, and sensitivity 86.96%] and test set (AUC 0.879, Chen et al. Radiomics Predicted Efficancy of NACT specificity 82.19%, and sensitivity 83.57%). The decision curve indicated the clinical usefulness of our nomogram. Conclusion: Our radiomics nomogram showed good discrimination in patients with BCa who experience pCR after NACT. The model may aid physicians in predicting how specific patients may respond to BCa treatments in the future.

Metastasis can be a fatal step in breast cancer progression. Effective therapies are urgently required due to the limited therapeutic options clinically available. The aim of the present study was to investigate the effect of matrine (MAT), a traditional Chinese medicine, on the proliferation and migration of human breast cancer cells and its underlying mechanisms of action. The proliferation of MDA-MB-231 cells was inhibited and apoptosis was induced following treatment with MAT, as determined by MTT and Annexin-V-FITC/PI assays. Western blot analysis was used to detect the LC-3II/I levels and the results suggested that tumor autophagy is involved in the anti-tumor activity of MAT. To the best of our knowledge, this is the first study to report that MAT inhibits MDA-MB-231 and MCF-7 cell motility, potentially by targeting integrin β1 (ITGB1) and epithelial-to-mesenchymal transition (EMT), as indicated by Transwell® and siRNA interference assays. In conclusion, ITGB1 and EMT are involved in MAT-induced breast carcinoma cell death and the inhibition of metastasis. This may lead to the development of novel compounds for the treatment of breast cancer metastasis.

To investigate whether estrogen receptor (ER), progesterone receptor (PR) and Ki-67 expression discordance before and after neoadjuvant chemotherapy (NAC) correlates with prognosis and treatment of breast cancer patients. Methods The study cohort included 482 breast cancer patients at the Zhejiang Cancer Hospital from January 1, 2008, to December 31, 2018. Core needle biopsies and excised tissue biopsies pre-and post-NAC were obtained. Immunohistochemistry was used to determine ER, PR and Ki-67 status. The relationship between biomarker discordance before and after NAC and clinicopathological features was compared retrospectively. Results ER (n = 482), PR (n = 482) and Ki-67 (n = 448) expression was assessed in the same lesion pre-and post-NAC. Discordance in the three markers pre-and post-NAC was observed in 50 (10.4%), 82 (17.0%) and 373 (77.4%) cases, respectively. Positive-to-negative PR expression changes were the most common type of discordance observed. The risk of death in patients with a PR positive-to-negative conversion was 6.58 times greater than for patients with stable PR expression. The risk of death in patients with increased Ki-67 expression following NAC treatment was 2.05 times greater than for patients with stable Ki-67 expression.