Abstract
BACKGROUND: The role of copper-induced cell death, termed cuproptosis, has been demonstrated recently. Nonetheless, the potential biological function of cuproptosis regulators in thyroid cancer (THCA) remains unknown. METHOD: We analyzed the expression levels and prognostic values of cuproptosis regulators in THCA. We used weighted gene co-expression network analysis (WGCNA) and single-sample gene set enrichment analysis (ssGSEA) to perform biological function analysis. We used a sliding windows sequential forward feature selection (SWSFS) method to construct a cuproptosis-related score (RS) to predict progression- and disease-free survival probability. We validated the expression level of cuproptosis-related genes and explored the biological function of FDX1. RESULTS: FDX1 was a protective factor for THCA and possessed a higher expression level in thyroid cancer. WGCNA and ssGSEA analysis showed that several pathways, such as protein secretion, oxidative phosphorylation, MYC, MTORC1, DNA repair, and adipogenesis, were highly positively correlated with cuproptosis regulators. In contrast, some immune-related pathways, such as interferon response and inflammatory pathways, were negatively correlated. We selected intersection genes by correlation analysis between the expression level of FDX1 and the prediction inhibitory concentration (IC50). Stratified analysis and nomogram were also employed to verify the validity and accessibility of the signature. Correlation analysis suggested that FDX1 expression was associated with immune cell infiltration patterns in THCA based on in silico estimations. Using qRT-PCR, we found that the expression level of MAP1LC3A and RBPMS2 were higher in normal thyroid tissues, and the GINM1 was higher in THCA. Colony forming and Cell Counting kit-8 assays verified that FDX1 might not affect cell growth. And by down-regulating FDX1, we found that the expression level of genes involved in cuproptosis RS might be affected by FDX1 in THCA. CONCLUSION: Overall, our study identified a novel cuproptosis-based predictive model, and we demonstrated that cuproptosis is a promising therapeutic method for THCA, which enhances our understanding of the cuproptosis-related genes and provides valuable insights into the clinical treatment and molecular mechanisms of THCA.