A novel prognostic signature for hepatocellular carcinoma based on SUMOylation-related genes

SUMOylation (SUMO modification) has been confirmed to play an essential role in the progression of various malignancies. As the value of SUMOylation-related genes (SRGs) in prognosis prediction of hepatocellular carcinoma (HCC) has not been explored, we aim to construct an HCC SRGs signature. RNA sequencing was utilized to identify differentially expressed SRGs. The 87 identified genes were used in Univariate Cox regression analysis and the Least Absolute Shrinkage and Selection Operator (LASSO) analysis to build a signature. The accuracy of the model was validated by the ICGC and GEO datasets. The GSEA revealed that the risk score was associated with common cancer-related pathways. The ssGSEA showed that NK cells in the high-risk group were significantly reduced. The sensitivities of anti-cancer drugs confirmed the sensitivity of the high-risk group to sorafenib was lower. Further, our cohort showed that risk scores were correlated with advanced grade and vascular invasion (VI). Finally, the results of H & E staining and immunohistochemistry of Ki67 showed that higher-risk patients are more malignant.

Automated summary

SUMOylation has a significant role in the progression of malignancies. This study aims to construct a signature for hepatocellular carcinoma (HCC) using SUMOylation-related genes (SRGs). Differentially expressed SRGs were identified through RNA sequencing and used to build a signature using Univariate Cox regression and LASSO analysis. The accuracy of the model was validated using ICGC and GEO datasets, and the risk score was found to be associated with cancer-related pathways.