Palmitoylation-related gene signature for immune subtyping, prognostic stratification, and immunotherapy guidance in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) remains a significant global health burden, with high mortality rates due to late diagnosis and limited therapeutic options. Palmitoylation, a reversible post-translational modification, has emerged as a critical regulator of cancer progression, yet its role in HCC remains underexplored. This study aims to investigate the diagnostic and prognostic value of palmitoylation-related genes (acyltransferase and acylthioesterase) in HCC, focusing on their potential as biomarkers and therapeutic targets.

Methods: Transcriptomic and clinicopathologic data from 377 HCC patients in The Cancer Genome Atlas (TCGA) cohort and 231 HCC patients in the International Cancer Genome Consortium (ICGC) cohort were analyzed. Differential gene expression analysis identified palmitoylation-related genes significantly associated with HCC. Univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were employed to construct a predictive model based on these genes. The model’s performance was validated using the ICGC dataset. Functional enrichment, immune microenvironment analysis, and machine learning approaches were further applied to explore the biological roles and clinical relevance of the identified genes.

Results: We identified 20 differentially expressed palmitoylation-related genes in HCC, of which eight were significantly associated with overall survival (OS). A predictive model incorporating ZDHHC18, ZDHHC23, and PPT1 was developed, stratifying patients into high- and low-risk groups with distinct survival outcomes. The model demonstrated robust predictive performance, with area under the curve (AUC) values of 0.700 (1 year), 0.653 (2 years), and 0.634 (3 years) in the TCGA cohort, and 0.773 (1 year), 0.705 (2 years), and 0.703 (3 years) in the ICGC cohort. Functional enrichment analysis revealed significant differences in immune-related pathways between risk groups, highlighting the model’s potential in guiding immunotherapy strategies.

Conclusions: This study establishes a novel predictive model based on palmitoylation-related genes, offering valuable insights into HCC prognosis and potential therapeutic targets. The model’s ability to stratify patients by risk and its association with immune microenvironment characteristics underscores its clinical relevance, paving the way for personalized treatment strategies in HCC.