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. 2022;39(1):24-31.
doi: 10.1159/000520893. Epub 2021 Nov 17.

Identification and Validation of Hub Genes Predicting Prognosis of Hepatocellular Carcinoma

Ziyan Chen  1   2 , Haitao Yu  3   4 , Lijun Wu  3   4 , Sina Zhang  3 , Zhihui Lin  3 , Tuo Deng  3   4 , Bangjie He  3   4 , Zhengping Yu  3   4 , Gang Chen  3   4 , Fang Wu  3
Affiliations

Identification and Validation of Hub Genes Predicting Prognosis of Hepatocellular Carcinoma

Ziyan Chen et al. Dig Surg. 2022.

Abstract

Introduction: The aim of this study is selecting the hub genes associated with hepatocellular carcinoma (HCC) to construct a Cox regression model for predicting prognosis in HCC patients.

Methods: Using HCC patient data from the ICGC and TCGA databases, screened for 40 core genes highly correlated with histological grade of HCC. Univariate and multivariate Cox regression analyses were performed on the genes highly associated with HCC prognosis, and the model was established. The expression of those genes was measured by immunohistochemistry in 110 HCC patients who underwent the surgery in the First Affiliated Hospital of Wenzhou Medical University. The survival of HCC patients was analyzed by the Kaplan-Meier method.

Results: Eight genes (CDC45, CENPA, MCM10, MELK, CDC20, ASF1B, FANCD2, and NCAPH) were correlated with prognosis, and the same result was observed in 110 HCC patients. Using the regression model, the HCC patients in the training set were classified as high- and low-risk groups. The overall survival of patients in the high-risk group was shorter than that in the low-risk group, and the same results were obtained in the verification set.

Conclusion: This study found that the risk model according to these 8 genes can be used as a predictor of prognosis in HCC. These genes may become alternative biomarkers and therapeutic targets and provide new therapeutic strategies for HCC.

Keywords: Cox regression model; Hepatocellular carcinoma; Hub gene; Prognosis.

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