Construction and validation of a prognostic model for hepatocellular carcinoma: Inflammatory ferroptosis and mitochondrial metabolism indicate a poor prognosis

Fang Han; Dan Cao; Xin Zhu; Lianqiang Shen; Jia Wu; Yizhen Chen; Youyao Xu; Linwei Xu; Xiangdong Cheng; Yuhua Zhang

doi:10.3389/fonc.2022.972434

Construction and validation of a prognostic model for hepatocellular carcinoma: Inflammatory ferroptosis and mitochondrial metabolism indicate a poor prognosis

Front Oncol. 2023 Jan 5:12:972434. doi: 10.3389/fonc.2022.972434. eCollection 2022.

Authors

Fang Han¹, Dan Cao^{1

2}, Xin Zhu³, Lianqiang Shen⁴, Jia Wu¹, Yizhen Chen^{1

5}, Youyao Xu^{1

5}, Linwei Xu¹, Xiangdong Cheng¹, Yuhua Zhang^{1

5}

Affiliations

¹ Hepatobiliary and Pancreatic Surgery Department, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer(IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang, China.
² College of Food and Pharmacy, Zhejiang Ocean University, Zhoushan, Zhejiang, China.
³ Hepatobiliary and Pancreatic Surgery Department, Shaoxing Peoples's Hospital, Shaoxing, Zhejiang, China.
⁴ Department of General Surgery, The First People's Hospital of Linping District, Hangzhou, Hangzhou, Zhejiang, China.
⁵ Clincal Dept. Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.

Abstract

Background: An increasing number of innovations have been discovered for treating hepatocellular carcinoma (HCC or commonly called HCC) therapy, Ferroptosis and mitochondrial metabolism are essential mechanisms of cell death. These pathways may act as functional molecular biomarkers that could have important clinical significance for determining individual differences and the prognosis of HCC. The aim of this study was to construct a stable and reliable comprehensive model of genetic features and clinical factors associated with HCC prognosis.

Methods: In this study, we used RNA-sequencing (fragments per kilobase of exon model per million reads mapped value) data from the Cancer Genome Atlas (TCGA) database to establish a prognostic model. We enrolled 104 patients for further validation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analyses (KEGG) analysis were used for the functional study of differentially expressed genes. Pan-cancer analysis was performed to evaluate the function of the Differentially Expressed Genes (DEGs). Thirteen genes were identified by univariate and least absolute contraction and selection operation (LASSO) Cox regression analysis. The prognostic model was visualized using a nomogram.

Results: We found that eight genes, namely EZH2, GRPEL2, PIGU, PPM1G, SF3B4, TUBG1, TXNRD1 and NDRG1, were hub genes for HCC and differentially expressed in most types of cancer. EZH2, GRPEL2 and NDRG1 may indicate a poor prognosis of HCC as verified by tissue samples. Furthermore, a gene set variation analysis algorithm was created to analyze the relationship between these eight genes and oxidative phosphorylation, mitophagy, and FeS-containing proteins, and it showed that ferroptosis might affect inflammatory-related pathways in HCC.

Conclusion: EZH2, GRPEL2, NDRG1, and the clinical factor of tumor size, were included in a nomogram for visualizing a prognostic model of HCC. This nomogram based on a functional study and verification by clinical samples, shows a reliable performance of patients with HCC.

Keywords: bioinformatics; ferroptosis; hepatocellular carcinoma; inflammation; mitochondrial metabolism; prognostic model; survival analysis.