基于紫杉醇和蒽环类药物的化疗是乳腺癌的标准治疗选择之一。然而，只有约6-30%的乳腺癌患者达到了病理完全缓解（pCR），并且造成这种差异的机制仍不清楚。本研究采用随机森林算法筛选特征基因，并采用人工神经网络（ANN）算法构建预测乳腺癌新辅助化疗疗效的ANN模型。此外，还利用数字病理学、细胞学和分子生物学实验来验证新辅助化疗疗效与免疫生态学之间的关系。研究发现，紫杉醇和阿霉素（一种蒽环类药物）可诱导乳腺癌细胞发生典型的细胞焦亡和鼓泡，并伴有gasdermin E (GSDME) 裂解。紫杉醇导致 LDH 释放和膜联蛋白 V/PI 双阳性细胞群，并伴随损伤相关分子模式、HMGB1 和 ATP 释放的增加。细胞共培养实验还表明，紫杉醇治疗后巨噬细胞的吞噬作用增强，IFN-γ和IL-2分泌水平增加。机制上，GSDME可能通过caspase-9/caspase-3通路介导紫杉醇和阿霉素诱导的乳腺癌细胞焦亡，激活抗肿瘤免疫，促进紫杉醇和蒽环类药物新辅助化疗的疗效。该研究对于乳腺癌的精准治疗具有实际指导意义，也可为理解化疗敏感性相关分子机制提供思路。© 2024。作者。

Paclitaxel and anthracycline-based chemotherapy is one of the standard treatment options for breast cancer. However, only about 6-30% of breast cancer patients achieved a pathological complete response (pCR), and the mechanism responsible for the difference is still unclear. In this study, random forest algorithm was used to screen feature genes, and artificial neural network (ANN) algorithm was used to construct an ANN model for predicting the efficacy of neoadjuvant chemotherapy for breast cancer. Furthermore, digital pathology, cytology, and molecular biology experiments were used to verify the relationship between the efficacy of neoadjuvant chemotherapy and immune ecology. It was found that paclitaxel and doxorubicin, an anthracycline, could induce typical pyroptosis and bubbling in breast cancer cells, accompanied by gasdermin E (GSDME) cleavage. Paclitaxel with LDH release and Annexin V/PI doubule positive cell populations, and accompanied by the increased release of damage-associated molecular patterns, HMGB1 and ATP. Cell coculture experiments also demonstrated enhanced phagocytosis of macrophages and increased the levels of IFN-γ and IL-2 secretion after paclitaxel treatment. Mechanistically, GSDME may mediate paclitaxel and doxorubicin-induced pyroptosis in breast cancer cells through the caspase-9/caspase-3 pathway, activate anti-tumor immunity, and promote the efficacy of paclitaxel and anthracycline-based neoadjuvant chemotherapy. This study has practical guiding significance for the precision treatment of breast cancer, and can also provide ideas for understanding molecular mechanisms related to the chemotherapy sensitivity.© 2024. The Author(s).