癌症中的脂质代谢:探索磷脂作为潜在的生物标志物

IF 6.9 2区 医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
Dominique Delmas , Aurélie Mialhe , Alexia K. Cotte , Jean-Louis Connat , Florence Bouyer , François Hermetet , Virginie Aires
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引用次数: 0

摘要

异常脂质代谢越来越被认为是癌症的一个标志,有助于肿瘤生长、转移性传播和对治疗的抵抗。癌细胞重新编程关键的代谢途径,包括新生脂肪生成、脂质摄取和磷脂重塑,以维持恶性进展并适应微环境需求。这篇综述总结了目前对脂质代谢重编程在肿瘤发生中的作用的见解,并强调了脂质组学的最新进展,这些进展揭示了具有诊断和预后相关性的癌症类型和阶段特异性脂质特征。我们强调脂质代谢途径的双重潜力,特别是那些涉及磷脂的途径,作为临床相关生物标志物和治疗靶点的来源。参与这些途径的酶和转运体已成为诊断应用和药理学干预的有希望的候选者。我们还研究了阻碍基于脂质方法临床转化的持续挑战,包括分析可变性、生物学验证不足以及缺乏标准化整合到临床工作流程中。此外,本文还探讨了克服这些障碍的策略,强调了在先进的计算工具和人工智能驱动的分析支持下,将脂质组学纳入多组学框架的重要性,以破译肿瘤相关代谢网络的复杂性。我们讨论了这种综合方法如何促进可操作的代谢靶点的识别,提高基于脂质生物标志物的特异性和稳健性,并在精确肿瘤学的背景下加强患者分层。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lipid metabolism in cancer: Exploring phospholipids as potential biomarkers
Aberrant lipid metabolism is increasingly recognized as a hallmark of cancer, contributing to tumor growth, metastatic dissemination, and resistance to therapy. Cancer cells reprogram key metabolic pathways—including de novo lipogenesis, lipid uptake, and phospholipid remodeling—to sustain malignant progression and adapt to microenvironmental demands. This review summarizes current insights into the role of lipid metabolic reprogramming in oncogenesis and highlights recent advances in lipidomics that have revealed cancer type– and stage–specific lipid signatures with diagnostic and prognostic relevance. We emphasize the dual potential of lipid metabolic pathways—particularly those involving phospholipids—as sources of clinically relevant biomarkers and therapeutic targets. Enzymes and transporters involved in these pathways have emerged as promising candidates for both diagnostic applications and pharmacological intervention. We also examine persistent challenges hindering the clinical translation of lipid-based approaches, including analytical variability, insufficient biological validation, and the lack of standardized integration into clinical workflows. Furthermore, the review explores strategies to overcome these barriers, highlighting the importance of incorporating lipidomics into multi-omics frameworks, supported by advanced computational tools and AI-driven analytics, to decipher the complexity of tumor-associated metabolic networks. We discuss how such integrative approaches can facilitate the identification of actionable metabolic targets, improve the specificity and robustness of lipid-based biomarkers, and enhance patient stratification in the context of precision oncology.
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来源期刊
CiteScore
11.90
自引率
2.70%
发文量
1621
审稿时长
48 days
期刊介绍: Biomedicine & Pharmacotherapy stands as a multidisciplinary journal, presenting a spectrum of original research reports, reviews, and communications in the realms of clinical and basic medicine, as well as pharmacology. The journal spans various fields, including Cancer, Nutriceutics, Neurodegenerative, Cardiac, and Infectious Diseases.
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