Lipid metabolism in cancer: Exploring phospholipids as potential biomarkers.

Fiche publication

Date publication

avril 2025

Journal

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie

Auteurs

Membres identifiés du Cancéropôle Est :
Pr DELMAS Dominique , Dr HERMETET François , Dr AIRES Virginie

Tous les auteurs :
Delmas D, Mialhe A, Cotte AK, Connat JL, Bouyer F, Hermetet F, Aires V

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/40311223

Résumé

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.