Identification and dissection of prostate cancer grounded on fatty acid metabolism-correlative features for predicting prognosis and assisting immunotherapy

Background

Fatty acid metabolism (FAM) plays a critical role in tumor progression and therapeutic resistance by enhancing lipid biosynthesis, storage, and catabolism. Dysregulated FAM is a hallmark of prostate cancer (PCa), enabling cancer cells to adapt to extracellular signals and metabolic changes, with the tumor microenvironment (TME) playing a key role. However, the prognostic significance of FAM in PCa remains unexplored.

Methods

We analyzed 309 FAM-related genes to develop a prognostic model using least absolute shrinkage and selection operator (LASSO) regression based on The Cancer Genome Atlas (TCGA) database. This model stratified PCa patients into high- and low-risk groups and was validated using the Gene Expression Omnibus (GEO) database. We constructed a nomogram incorporating risk score, clinical variables (T and N stage, Gleason score, age), and assessed its performance with calibration curves. The associations between risk score, tumor mutation burden (TMB), immune checkpoint inhibitors (ICIs), and TME features were also examined. Finally, a hub gene was identified via protein-protein interaction (PPI) networks and validated.

Results

The risk score was an independent prognostic factor for PCa. High-risk patients showed worse survival outcomes but were more responsive to immunotherapy, chemotherapy, and targeted therapies. A core gene with high expression correlated with poor prognosis, unfavorable clinicopathological features, and immune cell infiltration.

Conclusion

These findings reveal the prognostic importance of FAM in PCa, providing novel insights into prognosis and potential therapeutic targets for PCa management.