Research advances of lactylation modification in breast cancer.

IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM
Pu Shen, Meng Yang
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引用次数: 0

Abstract

Breast cancer (BC), a leading cause of cancer mortality in women, involves complex molecular mechanisms including post-translational modifications (PTMs). While common PTMs are well-studied, lactylation-a novel PTM linking metabolism to epigenetics-has emerged as a critical regulator in BC pathogenesis. The high concentration of lactate caused by the Warburg effect makes lactylation in tumor tissue possible. Machine learning enhances the discovery and analysis of lactylation sites by processing large datasets, revealing patterns that influence tumor behavior and patient outcomes. This review offers a comprehensive analysis of the role of lactylation in breast cancer development and progression. It focuses on the impact on the proliferation, migration, and invasion of breast cancer cells and their association with chemotherapeutic resistance. This review provides valuable insights for the development of targeted therapeutic strategies that may enhance early diagnosis, treatment, and prognostic evaluation of breast cancer. The findings presented here open new avenues for future research and clinical practice.

乳腺癌中乳酸化修饰的研究进展。
乳腺癌(BC)是女性癌症死亡的主要原因,涉及包括翻译后修饰(PTMs)在内的复杂分子机制。虽然常见的PTM已被充分研究,但乳酸化-一种将代谢与表观遗传学联系起来的新型PTM -已成为BC发病机制的关键调节因子。由Warburg效应引起的高浓度乳酸使肿瘤组织中的乳酸化成为可能。机器学习通过处理大型数据集来增强对乳酸化位点的发现和分析,揭示影响肿瘤行为和患者预后的模式。这篇综述提供了一个全面的分析作用的乳酸化在乳腺癌的发展和进展。它的重点是对乳腺癌细胞的增殖、迁移和侵袭的影响及其与化疗耐药的关系。本综述为开发靶向治疗策略提供了有价值的见解,这些策略可能会增强乳腺癌的早期诊断、治疗和预后评估。这里提出的研究结果为未来的研究和临床实践开辟了新的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Discover. Oncology
Discover. Oncology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
2.40
自引率
9.10%
发文量
122
审稿时长
5 weeks
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