Integrating bulk-RNA and single-cell analysis reveals heterogeneous expression of cuproptosis-related sorafenib-resistant genes in hepatocellular carcinoma

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Abstract Objectives Cuproptosis represents the copper-dependent novel cell death pattern. However, the effects of cuproptosis-related sorafenib-resistant genes on prognosis, treatment response, and sorafenib resistance in hepatocellular carcinoma (HCC) patients are still unclear. The present work aims to develop a cuproptosis-related signature for predicting HCC prognosis. Methods Cuproptosis-related sorafenib-resistant differentially expressed genes (CRSRDEGs) were identified by correlation analysis between cuproptosis genes and sorafenib-resistant genes using electronic databases TCGA and GEO. Besides, the cuproptosis-related sorafenib-resistant risk score model (CRSRRSM) was established through LASSO and univariate Cox regression analyses. Later, this model was adopted for analyzing HCC patient prognosis. Certain potential drugs and treatment sensitivity were also analyzed in HCC patients receiving sorafenib or transarterial chemoembolization (TACE) treatment. Results The CRSRRSM achieved excellent efficiency in predicting the prognosis and sorafenib or TACE treatment response of HCC patients. As revealed by somatic mutational analyses, CRSRRSM was associated with tumor mutational burden (TMB), especially for TP53, CSMD3, and OBSCN mutations. According to functional enrichment analysis, CRSRRSM was closely correlated with tumor-related pathways, cuproptosis-related tricarboxylic acid (TCA) cycle, and drug resistance. Notably, potential drugs such as sepantronium bromide, AZD8055, and RO-3306, the promising alternatives for treating HCC patients with sorafenib resistance, were also proposed based on CRSRRSM. Furthermore, single-cell transcriptomic analysis revealed that high-risk malignant cells demonstrated an increased capacity of proliferation and immune evasion. Conclusions A model, designated CRSRRSM, was constructed that can effectively predict the prognosis, sorafenib treatment response, and potential drugs for sorafenib resistance in HCC patients. This model provides potential implications for clinical management of HCC patients with sorafenib resistance.