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乳腺癌中的代谢组学:从生物标志物发现到个性化医疗

Metabolomics in Breast Cancer: From Biomarker Discovery to Personalized Medicine.

作者信息

Perestrelo Rosa, Luís Catarina

机构信息

CQM-Centro de Química da Madeira, Universidade da Madeira, Campus da Penteada, 9020-105 Funchal, Portugal.

Faculdade de Ciências da Vida, Universidade da Madeira, Campus da Penteada, 9020-105 Funchal, Portugal.

出版信息

Metabolites. 2025 Jun 23;15(7):428. doi: 10.3390/metabo15070428.

Abstract

Breast cancer (BC) is a highly heterogeneous disease with distinct molecular subtypes, each exhibiting unique metabolic adaptations that drive tumor progression and therapy resistance. Metabolomics has emerged as a powerful tool for understanding cancer metabolism and identifying clinically relevant biomarkers guiding personalized therapeutic strategies. Advances in analytical techniques such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have enabled the identification of metabolic alterations associated with BC initiation, progression, and treatment response (dysregulated glycolysis, lipid metabolism, amino acid utilization, and redox homeostasis). This review aims to provide a comprehensive overview of the role of metabolomics in BC research, focusing on its applications in identifying metabolic biomarkers for early diagnosis, prognosis, and treatment response. It underscores how metabolomic profiling can unravel the metabolic adaptations of different BC subtypes, offering insights into tumor biology and mechanisms of therapy resistance. Ultimately, it highlights the promise of metabolomics in driving biomarker-guided diagnostics and the development of metabolically informed, personalized therapeutic strategies in the era of precision medicine.

摘要

乳腺癌(BC)是一种高度异质性疾病,具有不同的分子亚型,每种亚型都表现出独特的代谢适应性,这些适应性驱动肿瘤进展和治疗耐药性。代谢组学已成为理解癌症代谢和识别指导个性化治疗策略的临床相关生物标志物的有力工具。诸如质谱(MS)和核磁共振(NMR)光谱等分析技术的进步,使得能够识别与BC的发生、进展和治疗反应相关的代谢改变(糖酵解失调、脂质代谢、氨基酸利用和氧化还原稳态)。本综述旨在全面概述代谢组学在BC研究中的作用,重点关注其在识别早期诊断、预后和治疗反应的代谢生物标志物方面的应用。它强调了代谢组学分析如何能够揭示不同BC亚型的代谢适应性,为肿瘤生物学和治疗耐药机制提供见解。最终,它突出了代谢组学在推动生物标志物指导的诊断以及在精准医学时代开发基于代谢信息的个性化治疗策略方面的前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d3f/12298204/b7d0d50ce0bb/metabolites-15-00428-g001.jpg

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