Metabolic Regulation by p53: Implications for Cancer Therapy.

IF 3.7 3区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Molecules and Cells Pub Date : 2025-02-20 DOI:10.1016/j.mocell.2025.100198
Ki Yeon Koo, Kwanho Moon, Hwa Seob Song, Min-Sik Lee
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Abstract

The tumor suppressor p53, long known for its roles in maintaining genomic integrity and suppressing tumorigenesis, has recently been recognized as a key regulator of cellular metabolism. Here, we review p53's emerging metabolic functions, highlighting its ability to orchestrate glucose, amino acid, and lipid metabolism. By promoting oxidative phosphorylation while inhibiting glycolysis and anabolic pathways, wild-type p53 counters metabolic reprogramming characteristic of cancer cells, such as the Warburg effect, and protects cells from mild cellular stresses. In contrast, mutant p53 disrupts these processes, fostering metabolic adaptations that support tumor progression. These findings pave the way for therapeutic approaches targeting p53-driven metabolic vulnerabilities in cancer.

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长期以来,肿瘤抑制因子 p53 因其在维持基因组完整性和抑制肿瘤发生方面的作用而闻名,最近它又被认为是细胞新陈代谢的关键调节因子。在这里,我们回顾了 p53 新出现的代谢功能,强调了它协调葡萄糖、氨基酸和脂质代谢的能力。通过促进氧化磷酸化同时抑制糖酵解和合成代谢途径,野生型 p53 可对抗癌细胞特有的代谢重编程(如沃伯格效应),并保护细胞免受轻微的细胞压力。相反,突变型 p53 会破坏这些过程,促进支持肿瘤进展的代谢适应。这些发现为针对 p53 驱动的癌症代谢脆弱性的治疗方法铺平了道路。
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来源期刊
Molecules and Cells
Molecules and Cells 生物-生化与分子生物学
CiteScore
6.60
自引率
10.50%
发文量
83
审稿时长
2.3 months
期刊介绍: Molecules and Cells is an international on-line open-access journal devoted to the advancement and dissemination of fundamental knowledge in molecular and cellular biology. It was launched in 1990 and ISO abbreviation is "Mol. Cells". Reports on a broad range of topics of general interest to molecular and cell biologists are published. It is published on the last day of each month by the Korean Society for Molecular and Cellular Biology.
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Cover and caption Editorial Board Members/Copyright Metabolic Regulation by p53: Implications for Cancer Therapy. Current advances and future directions in targeting histone demethylases for cancer therapy Recent Advances and Future Challenges in Predictive Modelling of Metalloproteins by Artificial Intelligence.
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