目的 利用生物信息学研究乳腺癌自噬相关分子模式和肿瘤微环境免疫细胞浸润特征，同时预测具有潜在治疗作用的中药。方法 从TCGA和GEO数据库下载乳腺癌数据，从UCSC Xena数据库获得乳腺癌拷贝数相关数据。使用R语言和Perl分析乳腺癌自噬相关基因在肿瘤组织和癌旁组织表达以及自噬相关基因的拷贝数情况。通过单因素Cox分析、Kaplan-Meier生存分析、最小绝对收缩和选择算子（logistic least absolute shrinkage and selection operator，Lasso）分析、受试者工作特征（receiver operator characteristic，ROC）、列线图构建自噬相关预后模型并评估其预后价值。利用基因集变异分析（gene set variation analysis，GSVA）、京都百科全书（Kyoto encyclopedia of genes and genomes，KEGG）、单样本基因集富集分析（single-sample gene set enrichment analysis，ssGSEA）和CIBERSORT算法，探索其在乳腺癌中的潜在生物学功能和免疫细胞浸润情况。在此基础上，将关键基因导入SymMap数据库获取相关中药，采用Cytocaspe构建“中药-成分-靶点”网络图，并通过体外实验验证代表性自噬相关中药对乳腺癌细胞增殖及侵袭的影响。结果 大部分自噬相关基因在乳腺癌肿瘤组织和癌旁组织中有表达差异和拷贝数变异，其中肿瘤蛋白P53（tumor protein P53，TP53）的突变频率最高。构建的自噬相关预后模型提示高风险乳腺癌患者预后更差。通过ssGSEA、ESTIMATE和CIBERSORT进一步表明，所建立的模型可能对免疫细胞丰度、免疫细胞类型等产生影响。此外，预测结果提示调控乳腺癌自噬的中药功效以清热解毒、活血化瘀、补阳类为主，药性以辛、苦、甘、寒为主，主要归肝、肺、胃经。实验验证进一步表明，清热解毒药白花蛇舌草、活血化瘀药郁金、补阳药肉苁蓉/淫羊藿可通过调控自噬活性抑制乳腺癌发展。结论 自噬指示乳腺癌不良预后，并与肿瘤免疫浸润密切相关。调控乳腺癌自噬的中药以清热解毒、活血化瘀、补阳类为主，为乳腺癌的免疫和中医药治疗提供新的方向。

Objective To study the molecular patterns related to autophagy in breast cancer and the characteristics of immune cell infiltration in tumor microenvironment by bioinformatics, and to predict the potential traditional Chinese Medicine (TCM) with therapeutic effects. Methods Breast cancer data was downloaded from TCGA and GEO databases, and breast cancer copy number-related data were obtained from UCSC Xena database. R language and Perl were used to analyze the expression of breast cancer autophagy-related genes in tumor tissues and adjacent tissues, as well as the copy number of autophagy-related genes. Autophagy-related prognostic models were constructed using single-factor Cox analysis, Kaplan-Meier survival analysis, least absolute shrinkage and selection operator (Lasso) regression analysis, receiver operating characteristic (ROC), and column charts, and their prognostic value was evaluated. Gene set variation analysis (GSVA), Kyoto encyclopedia of genes and genomes (KEGG), single-sample gene set enrichment analysis (ssGSEA), and CIBERSORT algorithm were used to explore its potential biological function and immune infiltration in breast cancer. On such basis, autophagy-related TCM were obtained through importing the key genes into the SymMap database to construct the network diagram of TCM-components-targets based on Cytocaspe, and he effects of representative autophagy-related TCM on the proliferation and invasion of breast cancer cells were verified by in vitro experiments. Results Most of the autophagy-related genes were differentially expressed and existed copy number variations between breast cancer tissues and adjacent tissues. Among them, tumor protein P53 (TP53) had the highest mutation frequency. The autophagy-related prognostic models indicated a worse prognosis for high-risk breast cancer patients. SsGSEA, ESTIMATE and CIBERSORT algorithms further point out that the established model might have an impact on the abundance of immune cells, the type of immune cells and so on. Furthermore, the results indicated that TCM regulating breast cancer autophagy was mainly heat-clearing and detoxifying, blood circulation-promoting & blood stasis-removing, and yang-tonifying. The TCM taste was mainly spicy, bitter, sweet, and cold within the sites of liver, lung, and stomach. The experimental results further indicated that the clearing heat and removing toxicity drug Baihuasheshecao (Scleromitrion diffusum), the activating blood and dissolving stasis drug Yujin (Curcumae Radix) and yang-tonifying drugs Roucongrong (Cistanches Herba)/Yinyanghuo (Epimedii Folium) could inhibit the development of breast cancer by regulating autophagy activity. Conclusion Autophagy indicates poor prognosis of breast cancer and is closely related to tumor immune infiltration. TCM that regulate breast cancer autophagy is mainly clearing heat and removing toxicity, activating blood and dissolving stasis, and yang-tonifying, which can provides new directions for the immunotherapy and TCM treatment of breast cancer.

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国家自然科学基金项目（81973526）；省部共建中医湿证国家重点实验室专项（SZ2021ZZ19）；广东省科技计划项目（2023B1212060063，2022B1515230002，2017B030314166）；2020广东省科技创新战略专项资金（粤港澳联合实验室）项目（2020B1212030006）；广东省中医院院内专项（YN2018MJ07）