Prognostic Role and Potential Mechanisms of the Ferroptosis-Related Metabolic Gene Signature in Hepatocellular Carcinoma

Tianxing Dai; Jing Li; Xu Lu; Linsen Ye; Haoyuan Yu; Lele Zhang; Mingbin Deng; Shuguang Zhu; Wei Liu; Guoying Wang; Yang Yang

doi:10.2147/PGPM.S319524

Prognostic Role and Potential Mechanisms of the Ferroptosis-Related Metabolic Gene Signature in Hepatocellular Carcinoma

Pharmgenomics Pers Med. 2021 Aug 3:14:927-945. doi: 10.2147/PGPM.S319524. eCollection 2021.

Authors

Tianxing Dai^#¹, Jing Li^#², Xu Lu^#³, Linsen Ye¹, Haoyuan Yu¹, Lele Zhang¹, Mingbin Deng¹, Shuguang Zhu¹, Wei Liu³, Guoying Wang⁴, Yang Yang¹

Affiliations

¹ Department of Hepatic Surgery and Liver Transplant Program, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, People's Republic of China.
² Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
³ Guangdong Key Laboratory of Liver Disease Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, People's Republic of China.
⁴ Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People's Republic of China.

^# Contributed equally.

Abstract

Purpose: Ferroptosis, as a novel regulated cell death form, has a close interaction with metabolism, which is largely unknown in cancer. In the present study, we conducted a comprehensive analysis of ferroptosis-related metabolic genes to delineate the metabolic signatures induced by ferroptosis and evaluate its prognostic significance in hepatocellular carcinoma (HCC).

Methods: The ferroptosis-related metabolic genes (Fer-MRGs) were identified by correlation analyses with transcriptome data from The Cancer Genome Atlas and Gene Expression Omnibus. Then, univariate and the least absolute shrinkage and selection operator Cox regression analysis was used to establish a novel risk score model. Univariate and multivariate COX analyses were used to identify independent prognostic factors for overall survival (OS) of HCC, and a nomogram was developed. The Fer-MRGs' expression was further evaluated by quantitative real-time polymerase chain reaction in HCC.

Results: A total of 77 metabolic genes were identified as Fer-MRGs, and 26 were found with prognostic values for OS of HCC. Then, a novel nine-gene (AKR1C3, ATIC, G6PD, GMPS, GNPDA1, IMPDH1, PRIM1, RRM2, and TXNRD1) risk score model was constructed. Survival analyses showed worse OS in high-risk patients both in the training and validation groups. The model was also identified as an independent prognostic factor for HCC, and a prognostic nomogram for OS was further established with superior discriminative capacity and prediction accuracy. Notably, close correlations were also identified between the risk score and the expression of immune checkpoint genes, immune subtypes of tumor, and susceptibility of HCC to chemotherapeutic agents. Finally, elevated expression of eight Fer-MRGs (except for IMPDH1) was further verified in 16 pairs of HCC tumor and adjacent tissues.

Conclusion: These results indicated the intense interaction between ferroptosis and metabolism, the significant role of ferroptosis-related MRGs, and the great potential of the novel risk score model for prognosis prediction in HCC.

Keywords: ferroptosis; gene signature; hepatocellular carcinoma; metabolism; prognosis.

Grants and funding

This work was supported by the Guangdong Natural Science Foundation (No. 2015A030313038, 2015A030312013).