Metabolomics as a tool for understanding and treating triple-negative breast cancer.

Abstract

Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous variant of breast cancer distinguished by a lack of targeted therapies, posing significant challenges in diagnosis and treatment. Metabolomics, the comprehensive study of small compounds in biological systems, has been identified as an instrument for revealing the metabolic underpinnings of TNBC. This review highlights recent advancements in metabolomic approaches, such as mass spectrometry and nuclear magnetic resonance, which have identified metabolic vulnerabilities, resistance mechanisms, and potential therapeutic targets. Key findings include alterations in fatty acid, amino acid, and glutathione metabolism, along with hypoxia-driven metabolic reprogramming that contributes to disease progression. The combination of metabolomics with multi-omics techniques, supported by advanced computational methods such as machine learning, offers a pathway to overcome challenges in data standardization and biological complexity. Emerging strategies, including the use of artificial intelligence and multidimensional omics approaches, are paving the way for personalized medicine by enabling the discovery of novel biomarkers and targeted therapies. Despite these advances, significant hurdles remain, including the need for robust data standardization, validation of findings in diverse patient cohorts, and seamless integration with clinical workflows. By addressing these challenges, metabolomics has the potential to revolutionize TNBC management, offering tools for early detection, precision therapy, and improved patient outcomes. This review underscores the importance of interdisciplinary collaboration to translate metabolomic insights into actionable clinical applications.