Gao Tingting, Yang Liuxin, Zhang Yali, Bajinka Ousman, Yuan Xingxing
Department of Gastroenterology, Heilongjiang Academy of Traditional Chinese Medicine, Harbin, China.
First Clinical Medical College, Heilongjiang University of Chinese Medicine, Harbin, China.
Front Pharmacol. 2024 Oct 17;15:1450441. doi: 10.3389/fphar.2024.1450441. eCollection 2024.
Despite the advanced technologies and global attention on cancer treatment strategies, cancer continues to claim lives and adversely affects socio-economic development. Although combination therapies were anticipated to eradicate this disease, the resilient and restorative nature of cancers allows them to proliferate at the expense of host immune cells energetically. This proliferation is driven by metabolic profiles specific to the cancer type and the patient. An emerging field is exploring the metabolic reprogramming (MR) of cancers to predict effective treatments. This mini-review discusses the recent advancements in cancer MR that have contributed to predictive, preventive, and precision medicine. Current perspectives on the mechanisms of various cancer types and prospects for MR and personalized cancer medicine are essential for optimizing metabolic outputs necessary for personalized treatments.
尽管在癌症治疗策略方面有先进技术且受到全球关注，但癌症仍在继续夺走生命，并对社会经济发展产生不利影响。尽管人们期望联合疗法能根除这种疾病，但癌症具有的韧性和恢复能力使其能够以大量消耗宿主免疫细胞为代价进行增殖。这种增殖由特定癌症类型和患者的代谢特征驱动。一个新兴领域正在探索癌症的代谢重编程（MR）以预测有效治疗方法。本综述讨论了癌症MR领域的最新进展，这些进展有助于推动预测性、预防性和精准医学的发展。目前对各种癌症类型的机制以及MR和个性化癌症医学前景的看法，对于优化个性化治疗所需的代谢输出至关重要。
