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癌症与衰老中的代谢重编程。

Metabolic reprogramming in cancer and senescence.

作者信息

Zhang Yuzhu, Tang Jiaxi, Jiang Can, Yi Hanxi, Guang Shu, Yin Gang, Wang Maonan

机构信息

Department of Pathology Xiangya Hospital School of Basic Medical Sciences Central South University Changsha China.

National Clinical Research Center for Geriatric Disorders Xiangya Hospital Central South University Changsha China.

出版信息

MedComm (2020). 2025 Mar 4;6(3):e70055. doi: 10.1002/mco2.70055. eCollection 2025 Mar.

DOI:10.1002/mco2.70055
PMID:40046406
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11879902/
Abstract

The rising trend in global cancer incidence has caused widespread concern, one of the main reasons being the aging of the global population. Statistical data show that cancer incidence and mortality rates show a clear upward trend with age. Although there is a commonality between dysregulated nutrient sensing, which is one of the main features of aging, and metabolic reprogramming of tumor cells, the specific regulatory relationship is not clear. This manuscript intends to comprehensively analyze the relationship between senescence and tumor metabolic reprogramming; as well as reveal the impact of key factors leading to cellular senescence on tumorigenesis. In addition, this review summarizes the current intervention strategies targeting nutrient sensing pathways, as well as the clinical cases of treating tumors targeting the characteristics of senescence with the existing nanodelivery research strategies. Finally, it also suggests sensible dietary habits for those who wish to combat aging. In conclusion, this review attempts to sort out the link between aging and metabolism and provide new ideas for cancer treatment.

摘要

全球癌症发病率的上升趋势已引起广泛关注,主要原因之一是全球人口老龄化。统计数据表明,癌症发病率和死亡率随年龄呈现明显上升趋势。尽管衰老的主要特征之一——营养感知失调与肿瘤细胞的代谢重编程之间存在共性,但具体的调控关系尚不清楚。本手稿旨在全面分析衰老与肿瘤代谢重编程之间的关系;以及揭示导致细胞衰老的关键因素对肿瘤发生的影响。此外,本综述总结了目前针对营养感知途径的干预策略,以及利用现有纳米递送研究策略针对衰老特征治疗肿瘤的临床案例。最后,它还为那些希望对抗衰老的人提出了合理的饮食习惯建议。总之,本综述试图梳理衰老与代谢之间的联系,并为癌症治疗提供新思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/7263f827aca7/MCO2-6-e70055-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/68fdf18fe0ce/MCO2-6-e70055-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/841558ffc85c/MCO2-6-e70055-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/758176ad1877/MCO2-6-e70055-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/ce9d09b43b34/MCO2-6-e70055-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/8528653860cf/MCO2-6-e70055-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/0d053100f4c6/MCO2-6-e70055-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/7263f827aca7/MCO2-6-e70055-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/68fdf18fe0ce/MCO2-6-e70055-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/841558ffc85c/MCO2-6-e70055-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/758176ad1877/MCO2-6-e70055-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/ce9d09b43b34/MCO2-6-e70055-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/8528653860cf/MCO2-6-e70055-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/0d053100f4c6/MCO2-6-e70055-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a2/11879902/7263f827aca7/MCO2-6-e70055-g006.jpg

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