Published online Apr 14, 2019. doi: 10.3748/wjg.v25.i14.1715
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
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.
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.
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.
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.
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.
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.
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.