Basic Study
Copyright ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Apr 14, 2019; 25(14): 1715-1728
Published online Apr 14, 2019. doi: 10.3748/wjg.v25.i14.1715
Seven-senescence-associated gene signature predicts overall survival for Asian patients with hepatocellular carcinoma
Xiao-Hong Xiang, Li Yang, Xing Zhang, Xiao-Hua Ma, Run-Chen Miao, Jing-Xian Gu, Yu-Nong Fu, Qing Yao, Jing-Yao Zhang, Chang Liu, Ting Lin, Kai Qu
Xiao-Hong Xiang, Xing Zhang, Xiao-Hua Ma, Run-Chen Miao, Jing-Xian Gu, Yu-Nong Fu, Qing Yao, Jing-Yao Zhang, Chang Liu, Ting Lin, Kai Qu, Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, Shaanxi Province, China
Li Yang, Department of Clinical Laboratory, Liaocheng People’s Hospital, Taishan Medical College, Liaocheng 252000, Shandong Province, China
Author contributions: Qu K, Lin T, Liu C, and Xiang XH designed the research; Yang L, Zhang X, Ma XH, Miao RC, and Gu JX collected and analyzed the data; Qu K, Xiang XH, Fu YN, and Yao Q prepared the figures; Zhang JY, Lin T, Qu K, and Liu C drafted and revised the manuscript.
Supported by the National Natural Science Foundation of China, No. 81773128 and No. 81871998; the Natural Science Basic Research Plan in Shaanxi Province of China, No. 2018JM7013 and No. 2017JM8039; the Research Fund for Young Star of Science and Technology in Shaanxi Province, No. 2018KJXX-022; and China Postdoctoral Science Foundation, No. 2018M641000.
Institutional review board statement: The study was reviewed and approved by the First Affiliated Hospital of Xi’an Jiaotong University Institutional Review Board.
Conflict-of-interest statement: None.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Kai Qu, MD, PhD, Professor, Research Assistant Professor, Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xi’an Jiaotong University, 277 West Yanta Road, Xi’an 710061, Shaanxi Province, China. qukai@xjtu.edu.cn
Telephone: +86-29-85323900 Fax: +86-29-85324695
Received: January 6, 2019
Peer-review started: January 7, 2019
First decision: February 13, 2019
Revised: March 6, 2019
Accepted: March 15, 2019
Article in press: March 16, 2019
Published online: April 14, 2019
Processing time: 96 Days and 23.7 Hours
ARTICLE HIGHLIGHTS
Research background

Hepatocellular carcinoma (HCC) is a common malignancy that remains a serious cause of death worldwide. Recently, molecular markers and prognostic models have been used to improve the diagnosis and treatment of HCC, but few can be applied clinically. Currently, bioinformatics technology has been used for data mining in large public databases. The abundant sample size in the public database can make up for the shortcomings of small samples in real hospitals and help to seek for a more accurate and applicable prognostic model for HCC.

Research motivation

Researchers have been making efforts to find molecular markers or prognostic models that can effectively predict the prognosis of HCC. Senescence is a cell cycle arrest caused by stress in cells, but the cells are still alive. Studies have shown that the proportion of senescent cells in tissues of patients with cirrhosis increases, but a considerable number of patients with cirrhosis can develop liver cancer, and its specific molecular mechanism has rarely been reported.

Research objectives

By analyzing the database of two cellular senescence models from Gene Expression Omnibus, we screened for senescence-associated genes and validated these genes in the liver cancer databases (GSE14520 and TCGA-LIHC). Then, we constructed an HCC prognostic model and evaluate its prognostic accuracy.

Research methods

Senescence-associated genes (SAGs) were identified using R package “limma”. The latest statistical algorithm-the least absolute shrinkage and selection operator (LASSO) was applied to create our prognostic model. Time-dependent receiver operating characteristic (ROC) curves were used to compare the prognostic accuracy between the seven-SAG signature and serum α-fetoprotein.

Research results

The prognostic model for predicting the overall survival (OS) of HCC was constructed by LASSO, consisting of the seven senescence-associated genes (SAGs) (KIF18B, CEP55, CIT, MCM7, CDC45, EZH2, and MCM5). All seven SAGs were highly expressed in HCC and proliferating cells, while lowly expressed in normal tissues and senescent cells. Survival analysis showed that our seven-SAG characteristics are closely related to OS, especially in Asian populations, both in the discovery and validation cohorts. In addition, the time-dependent ROC curve analysis indicated that the seven-gene marker is better than serum alpha-fetoprotein in predicting 1-, 3-, and 5-year OS of HCC patients.

Research conclusions

The seven-SAG signature was more applicable to evaluate OS of Asian HCC patients, which may provide new clinical evidence for the diagnosis and treatment of HCC transformed from cirrhosis.

Research perspectives

The current study provides clues that the expression changes of senescence-associated gene are the molecular basis for the progression of cirrhosis to liver cancer. Finding effective senescence-associated molecular biomarkers and predictive features of HCC prognosis is necessary.