Integrating multi-omics technologies with traditional Chinese medicine to enhance cancer research and treatment

作者：Xiaohui Wen, Yaran Wang, Chao Su, Yanyi You, Ziqing Jiang, Daoqi Zhu, Qin Fan · 发表于：QJM · 年份：2025 · DOI：10.1093/qjmed/hcaf103 · 被引用次数：18 · 研究领域：Bioinformatics and Genomic Networks、Cancer Genomics and Diagnostics、Metabolomics and Mass Spectrometry Studies

Cancer remains a formidable global health challenge owing to its complexity, including tumor heterogeneity and intricate regulatory networks. Traditional Chinese medicine (TCM) offers unique multi-targeted therapeutic approaches with demonstrated benefits such as improved prognosis, reduced side effects, and long-term tumor stabilization. This review explores the convergence of multi-omics technologies-genomics, transcriptomics, proteomics, metabolomics, and epigenomics-with TCM to elucidate the molecular mechanisms underlying its anti-cancer effects. By integrating omics data, researchers can uncover regulatory networks, identify therapeutic targets, and validate the efficacy of TCM. Advances in single-cell omics, spatial omics, and machine learning are creating new opportunities for personalized TCM-based therapies. However, translating these findings into clinical applications remains challenging. This review highlights the potential of omics-integrated TCM in addressing cancer complexity and proposes actionable strategies for overcoming research and application barriers, thereby facilitating the development of innovative and effective treatment options.