Copper-binding proteins genes set predicting the overall survival and immune infiltration in hepatocellular carcinoma by bioinformatic analysis

Abstract

Abnormal Copper (Cu) accumulation shared a close association with hepatocellular carcinoma (HCC), but the regulatory role of Copper-binding proteins in HCC remains largely unknown. The aim of study was to identify the potential regulatory role of Cu-binding proteins, including copper homeostasis maintainer and the downstream effectors of Cu, in the progression of HCC. We conducted a comprehensive bioinformatic analysis of Cu-binding proteins in HCC using data from TCGA and ICGC database. Univariate cox regression analysis was conducted, and four prognostic Cu-binding proteins was identified to be differentially expressed between the normal liver tissues and HCC tissues. In addition, the Cu-binding proteins-based predictive signature (CuPscore) model was generated using the least absolute shrinkage and selection operator (LASSO) cox regression model. Here, we identified the crucial prognostic value of CuPscore in HCC. The pathological stage and CuPscore were independent risk factors for the prognosis of HCC patients. Pathological stage and CuPscore-based nomogram model exhibited great performance in predicting the prognosis of HCC patients. We also observed that the CuPscore shared a close association with several immunomodulatory molecules and the proportion of several tumor infiltrating immune cells, suggesting a potential value of CuPscore in predicting the response to immunotherapy in HCC. Our results demonstrated the prognostic value of Cu-binding proteins and its correlation with immune microenvironment in HCC, providing a therapeutic basis for the precision medicine strategy through targeting Cu-binding proteins in HCC.