Construction of a cuproptosis genes prognostic model and associated competing endogenous RNA network in thyroid carcinoma

Abstract

Background:The present study aimed to investigate the association between cuproptosis genes (CGs) and the prognosis of thyroid carcinoma (TC), and to construct a prognosis model of TC and its regulatory network based on CGs. Methods:The association between CGs and TC prognosis was analyzed. A prognostic model of TC related to CGs was constructed by the LASSO algorithm and multivariate Cox regression analysis. The starBase database was used to predict the upstream long non-coding RNA (lncRNA) and microRNA (miRNA). Results:The results of the LASSO algorithm and multivariate Cox regression analysis on these 6 genes showed that ATP7B, DLD and PDHA1 could constitute the prognostic model of TC (P=0.015, C-index=0.76). Univariate (P<0.001) and multivariate (P<0.05) Cox analysis demonstrated that the risk score could independently predict the prognosis of patients with TC. Furthermore, the upstream lncRNA/miRNA regulatory network of model genes was predicted. Conclusion:The cuproptosis-related TC prognosis model helped to predict the survival of patients with TC. In addition, regulating the upstream ceRNA network of model genes may aid to guide the clinical treatment of TC.