Abstract:Objective The weighted gene co-expression network (WGCNA) and LASSO algorithm were used to investigate the prognostic value of transcription factor SOX12 in the occurrence and development of hepatocellular carcinoma (HCC). Method Using gene expression data (GEO) and tumor genome atlas (TCGA) corresponding information, Kaplan-Meier (K-M) survival curve and single factor, multivariate Cox regression were used to analyze the clinical value of SOX12 gene expression in HCC. Using ESTIMATE and CIBERSORT algorithms to study the correlation between SOX12 gene expression and tumor immune microenvironment. The WGCNA and LASSO algorithms were used to establish a risk prognosis model to further evaluate the effect of SOX12 gene expression in the high and low risk groups on the mutations of HCC genes. Result In HCC tumor tissues, the expression of SOX12 is significantly increased, which is related to age, gender, tumor grade, disease stage, and is significantly related to the survival and prognosis of patients. In the risk prognosis model of immune-related genes (IRGs) showed that the overall survival rate of the high-risk group was worse than that of the low-risk group. The risk prognosis model has a significant prognostic prediction effect, and its 1-year, 3-year and 5-year AUCs are 0.823, 0.811 and 0.824, respectively. The proportion of TP53 gene mutations in the high SOX12 expression group (40%) was significantly higher than that in the low SOX12 expression group (25%). The results indicated that the high and low SOX12 expression in the high and low risk groups affects the frequency of HCC genetic mutations. Conclusion The expression of SOX12 is associated with HCC immune infiltration and disease gene mutations, suggesting that it may become a potential target for prognostic evaluation of HCC patients.