Ferroptosis-related gene model to predict overall survival of papillary thyroid carcinoma

Abstract

Background: Ferroptosis is a form of programmed cell death that is closely associated with the development of various tumors. However, the correlation between ferroptosis and papillary thyroid carcinoma (PTC) is unclear. This study was performed to investigate the expression and prognostic value of ferroptosis-related genes (FRG) in PTC.

Methods: mRNA expression profiles and corresponding clinical data of patients with PTC were analyzed to identify factors affecting prognosis. Independent risk factors were used to establish a predictive receiver operating characteristic model. Single-sample gene set enrichment analysis (ssGSEA) was used to evaluate the correlation between ferroptosis and immune cells.

Results: Most genes related to FRG (78.8%) were differentially expressed between the tumor and adjacent normal tissues. In univariate Cox regression analysis, 12 differentially expressed genes were associated with prognostic survival. We constructed a prognostic model of eight FRG, including DPP4, GPX4, GSS, ISCU, MIOX, PGD, TF, and TFRC, and divided patients into two groups: high and low risk. The high-risk group exhibited a significantly reduced overall survival rate. In multivariate Cox regression analysis, the risk score was used as an independent prognostic factor. ssGSEA showed that immune cell types and their expression in the high- and low-risk groups were significant.

Conclusion: This study constructed a prognostic model of ferroptosis-related genes and determined its usefulness as an independent prognostic factor, providing a reference for the treatment and prognosis of patients with PTC.

Keywords: Ferroptosis; Gene expression; Papillary thyroid carcinoma; Prognostic model; Single-sample gene set enrichment analysis.