Identification of SOX9-related prognostic DEGs and a prediction model for hepatitis C-induced early-stage fibrosis.

Abstract

Background: Hepatitis C virus (HCV) infection induces liver inflammation, activating hepatic stellate cells (HSC) and advancing fibrosis. Studies have indicated that SOX9 overexpression is closely linked to HSC activation. The study aims to identify genes associated with SOX9 and search for potential targets for detecting and treating liver fibrosis.

Method: The dataset GSE15654, containing 216 biopsy samples from HCV-induced early-stage cirrhosis patients, was obtained from the GEO database. Prognostic genes were identified through differential gene analysis, LASSO, and Cox regression analyses. CIBERSORT analysis quantified infiltration levels across 22 immune cell types. Constructing a prognostic prediction model using screened genes and conducting preliminary validation using qRT PCR and RNA sequencing techniques.

Results: Elevated SOX9 expression correlates with unfavorable outcomes in patients with early-stage liver fibrosis induced by HCV. We identified nine SOX9-related prognostic DEGs in our study. ADAMTS2, ARHGEF5, CCT8, ERG, LBH, FRMD6, INMT, and RASGRF2 were considered risk factors in the disease progression, while DHRS4 was considered a protective factor. SOX9 expression showed a positive correlation with mast cell infiltration, whereas ARHGEF5 and FRMD6 expressions were positively associated with M0 macrophage infiltration. Our combined model surpasses the commonly used APRI and FIB4 indicators in predicting patient prognosis. The testing of clinical samples also preliminarily validated our research results.

Conclusion: The prognostic model based on nine SOX9-related DEGs provides an effective tool for forecasting the progression and outcomes of liver fibrosis. This study introduces a new strategy for advancing liver fibrosis prediction and treatment.