三阴性乳腺癌（TNBC）是一种侵袭性强、缺乏有效治疗靶点的乳腺癌亚型，临床预后差，治疗难度大。其恶性进展与代谢重编程密切相关，该过程促进肿瘤微环境适应与耐药形成。代谢组学作为捕捉细胞功能终端表型的关键技术，为系统解析TNBC代谢特征提供了有力工具。综述非靶向、靶向、拟靶向、空间代谢组学及代谢流分析等技术在TNBC研究中的应用进展，揭示谷氨酸、谷氨酰胺等关键代谢物的作用，以及糖酵解、脂质合成、氨基酸代谢等核心通路的重编程机制；总结代谢组学生物标志物在早期诊断、预后评估与耐药预警中的潜力，并探讨代谢酶抑制剂、代谢-免疫协同治疗及中药复方干预等新型治疗策略。此外，还分析TNBC代谢异质性、多平台数据整合与动态监测等临床转化面临的挑战，展望人工智能（AI）驱动的代谢网络解析与类器官药敏模型构建等未来研究方向。代谢组学为TNBC的精准诊疗开辟了新途径，但其深度临床应用仍面临诸多挑战。

Triple-negative breast cancer(TNBC) is a highly aggressive breast cancer subtype characterized by the lack of effective therapeutic targets, poor clinical prognosis, and considerable treatment challenges. Its malignant progression is closely associated with metabolic reprogramming, which facilitates tumor microenvironment adaptation and contributes to drug resistance. Metabolomics, as a key technology for capturing the end-point phenotype of cellular function, provides a powerful tool for systematically deciphering the metabolic features of TNBC. This review summarizes the application progress of untargeted, targeted, pseudo-targeted, and spatial metabolomics, as well as metabolic flux analysis in TNBC research. It highlights the roles of key metabolites such as glutamate and glutamine, and elucidates the reprogramming mechanisms of core pathways including glycolysis, lipid synthesis, and amino acid metabolism. The potential of metabolomic biomarkers in early diagnosis, prognosis assessment, and drug resistance warning is summarized, and novel therapeutic strategies such as metabolic enzyme inhibitors, metabolism–immunity combination therapy, and Chinese herbal compound interventions are discussed. Furthermore, this review addresses challenges in clinical translation, including metabolic heterogeneity in TNBC, multi-platform data integration, and dynamic monitoring, and outlines future research directions such as artificial intelligence-driven metabolic network analysis and organoid-based drug sensitivity models. Metabolomics has opened new avenues for the precise diagnosis and treatment of TNBC, yet its deep clinical application still faces multiple challenges.

R979.1

国家自然科学基金青年项目(82404736); 山西省高等教育“百亿工程”科技引导专项、煤炭环境致病与防治教育部重点实验室项目; 山西省中医药科研课题(2025ZYY8049)