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
Cellular senescence is a recognized barrier for progression of chronic liver diseases to hepatocellular carcinoma (HCC). The expression of a cluster of genes is altered in response to environmental factors during senescence. However, it is questionable whether these genes could serve as biomarkers for HCC patients.
To develop a signature of senescence-associated genes (SAGs) that predicts patients’ overall survival (OS) to improve prognosis prediction of HCC.
SAGs were identified using two senescent cell models. Univariate COX regression analysis was performed to screen the candidate genes significantly associated with OS of HCC in a discovery cohort (GSE14520) for the least absolute shrinkage and selection operator modelling. Prognostic value of this seven-gene signature was evaluated using two independent cohorts retrieved from the GEO (GSE14520) and the Cancer Genome Atlas datasets, respectively. Time-dependent receiver operating characteristic (ROC) curve analysis was conducted to compare the predictive accuracy of the seven-SAG signature and serum α-fetoprotein (AFP).
A total of 42 SAGs were screened and seven of them, including KIF18B, CEP55, CIT, MCM7, CDC45, EZH2, and MCM5, were used to construct a prognostic formula. All seven genes were significantly downregulated in senescent cells and upregulated in HCC tissues. Survival analysis indicated that our seven-SAG signature was strongly associated with OS, especially in Asian populations, both in discovery and validation cohorts. Moreover, time-dependent ROC curve analysis suggested the seven-gene signature had a better predictive accuracy than serum AFP in predicting HCC patients’ 1-, 3-, and 5-year OS.
We developed a seven-SAG signature, which could predict OS of Asian HCC patients. This risk model provides new clinical evidence for the accurate diagnosis and targeted treatment of HCC.
Core tip: In the present study, we identified a total of 42 senescence-associated genes (SAGs) and found seven of them were significantly downregulated in senescent cells and upregulated in HCC tissues. By using the least absolute shrinkage and selection operator, we constructed a seven-SAG signature that could predict the overall survival (OS) of hepatocellular carcinoma. This seven-SAG signature was further validated and developed in another independent dataset from The Cancer Genome Atlas project. Moreover, our risk score system showed better utility in predicting the OS than classic serum biomarker α-fetoprotein.