The impact of de novo lipogenesis on predicting survival and clinical therapy: an exploration based on a multigene prognostic model in hepatocellular carcinoma

PMCID: PMC12178006

PMID: 40533802

DOI: 10.1186/s12967-025-06704-y

Journal: Journal of translational medicine

Publication Date: 2025-6-18

Authors: Zhou X, Cui G, Hu E, Wang X, Tang D, et al.

Key Points

• A six-gene DNL signature effectively stratifies HCC patients into distinct prognostic risk groups
• Predictive model shows high accuracy with AUC range of 0.78–0.82
• Immune microenvironment variations between risk groups suggest personalized therapeutic approaches based on DNL-related gene profiles

Summary

This comprehensive study investigated the role of de novo lipogenesis (DNL) in hepatocellular carcinoma (HCC) progression by developing a novel six-gene prognostic signature. Utilizing multiple genomic datasets and a cohort of 106 HCC patients, researchers identified G6PD, LCAT, SERPINE1, SOAT2, CYP2C9, and UGT1A10 as key genes in predicting HCC outcomes and immune microenvironment characteristics.

The prognostic model demonstrated excellent predictive performance (AUC: 0.78–0.82) and revealed critical differences in immune infiltration between high-risk and low-risk patient groups. High-risk patients exhibited immunosuppressive features with increased regulatory T-cell infiltration, while low-risk patients maintained a more immunologically active microenvironment with enhanced natural killer (NK) cell retention. Notably, high-risk scores correlated with poorer immunotherapy response but increased sensitivity to targeted therapies, highlighting the complex interplay between DNL pathways and cancer immune dynamics.