Background: The heterogeneous tumor microenvironment (TME) contributes to poor prognosis of hepatocellular carcinoma (HCC). However, determining the modulation of TME during HCC progression remains a challenge.
Methods: Herein, the stromal score and immune score of HCC samples from The Cancer Genome Atlas database were calculated using the ESTIMATE algorithm and differentially expressed genes (DEGs) were obtained. Key DEGs were identified based on a protein-protein interaction network and survival analysis. Immunohistochemistry was carried out using primary samples to evaluate key DEGs expression. The CIBERSORT algorithm was applied to evaluate immune components. Gene Set Enrichment Analysis (GSEA) and correlation analysis were carried out to determine the relationship between key DEGs and tumor-infiltrating immune cells (TICs).
Results: The stromal score, immune score and estimate score correlated significantly with 1-year recurrence-free survival of patients with HCC. Interleukin-2 inducible T-cell kinase (ITK) was identified as the most prognostic DEG for patients with HCC. GSEA revealed that genes in the high ITK subgroup were enriched in inflammatory-immunological terms. CIBERSORT analysis identified nine TIC subsets that correlated with ITK expression.
Conclusion: We identified ITK as a novel indicator for early post-surgery tumor recurrence and microenvironment remodeling in HCC, providing a potential therapeutic target to treat HCC.
Keywords: CIBERSORT; ESTIMATE algorithm; HCC; ITK; tumor microenvironment.