Prognostic and immunological implications of sialylation-associated gene signatures in hepatocellular carcinoma

OBJECTIVE: The absence of effective biomarkers continues to limit early diagnostic accuracy and prognostic evaluation in patients with hepatocellular carcinoma (HCC). Aberrant sialylation (SI) has been demonstrated to contribute to therapeutic resistance and tumor progression. The aim of this investigation was to identify a sialylation-related gene (SRG) signature, evaluate its prognostic significance, and investigate associated immunological characteristics in HCC. METHODS: Transcriptomic profiles and corresponding clinical data for patients with HCC were obtained from UCSC Xena, the International Cancer Genome Consortium (ICGC), and the Molecular Signatures Database (MsigDB). Differential expression analysis, Cox regression analysis modeling, and least absolute shrinkage and selection operator (LASSO) regression analysis were applied to identify independent prognostic markers and develop predictive models. The tumor immune microenvironment and its relationship with the identified SRGs were assessed by evaluating immune infiltration patterns. A gene co-expression network for the prognostic SRGs was constructed using GeneMANIA to identify potentially targetable signaling pathways. RESULTS: ) were significantly associated with the prognosis of patients with HCC. Prognostic models constructed using these genes demonstrated strong predictive performance. Notable differences were observed in immune cell populations and immune checkpoint expression between the high-risk and low-risk groups. Additionally, the half-maximal inhibitory concentration values for 101 therapeutic compounds varied between these groups. Lipopolysaccharide and sphingolipid metabolism were identified as key biological processes linked to tumor progression and modulation of the immune microenvironment. CONCLUSION: The four identified SRGs were significantly associated with clinical outcomes and immunological features in HCC. These findings provide a foundation for advancing early diagnostic strategies, refining prognostic assessments, and guiding personalized therapeutic approaches for patients with HCC.