Post-translational acylation modulates immunosuppression and immunotherapy efficacy in hepatocellular carcinoma.

Acylation modification plays a crucial role in modulating hepatocellular carcinoma (HCC) progression, and their specific prognostic implications in HCC have not been thoroughly investigated. Eleven acylation modifications (crotonylation, lactylation, succinylation, benzoylation, butyrylation, malonylation, glutarylation, 2-hydroxyisobutyrylation, β-hydroxybutyrylation, palmitoylation, myristoylation, and prenylation) were generated consensus cluster. Then, WGCNA was utilized to identify module genes. Finally, machine learning approach was employed to create acylation modification related genes.score (AMRG.score). This analysis revealed two distinct subtypes of AMRG, each characterized by unique molecular signatures. Through the combination of DEGs, DEGs associated with prognosis, and WGCNA, a total of 21 key genes were identified, leading to the creation of AMRG.score. AMRG.score was rigorously validated across independent external cohorts (TCGA-LIHC, LIRI-JP, GSE10143, GSE14520, GSE27150, GSE36376, and GSE76427) and an in-house cohort, demonstrating its reliability and potential applicability. The AMRG.score serves a dual purpose in its application, as it encapsulates essential the clinical context and offers valuable insights regarding the immunotherapy. In particular, patients categorized with a high AMRG.score displayed an active TME and sensitive to immunotherapy. This novel acylation modification-related prognostic signature could effectively assess the prognosis and therapeutic responses of HCC patients, providing new perspectives for individualized treatment for the patient population.