These authors contributed equally to this work.
Sixty-five gene-based risk score classifier predicts overall survival in hepatocellular carcinoma†
Article first published online: 18 MAR 2012
Copyright © 2011 American Association for the Study of Liver Diseases
Volume 55, Issue 5, pages 1443–1452, May 2012
How to Cite
Kim, S. M., Leem, S.-H., Chu, I.-S., Park, Y.-Y., Kim, S. C., Kim, S.-B., Park, E. S., Lim, J. Y., Heo, J., Kim, Y. J., Kim, D.-G., Kaseb, A., Park, Y. N., Wang, X. W., Thorgeirsson, S. S. and Lee, J.-S. (2012), Sixty-five gene-based risk score classifier predicts overall survival in hepatocellular carcinoma. Hepatology, 55: 1443–1452. doi: 10.1002/hep.24813
Potential conflict of interest: Nothing to report.
- Issue published online: 19 APR 2012
- Article first published online: 18 MAR 2012
- Accepted manuscript online: 22 NOV 2011 06:31AM EST
- Manuscript Accepted: 3 NOV 2011
- Manuscript Received: 20 JUL 2011
- intramural faculty fund of the University of Texas MD Anderson Cancer Center to J-S Lee; MD Anderson Cancer Center
- NCI CCSG. Grant Number: CA106672 Microarray data: GSE1898, GSE4024, GSE9843, GSE14520, GSE16757, and E-TABM-36
Clinical application of the prognostic gene expression signature has been delayed due to the large number of genes and complexity of prediction algorithms. In the current study we aimed to develop an easy-to-use risk score with a limited number of genes that can robustly predict prognosis of patients with hepatocellular carcinoma (HCC). The risk score was developed using Cox coefficient values of 65 genes in the training set (n = 139) and its robustness was validated in test sets (n = 292). The risk score was a highly significant predictor of overall survival (OS) in the first test cohort (P = 5.6 × 10−5, n = 100) and the second test cohort (P = 5.0 × 10−5, n = 192). In multivariate analysis, the risk score was a significant risk factor among clinical variables examined together (hazard ratio [HR], 1.36; 95% confidence interval [CI], 1.13-1.64; P = 0.001 for OS). Conclusion: The risk score classifier we have developed can identify two clinically distinct HCC subtypes at early and late stages of the disease in a simple and highly reproducible manner across multiple datasets. (HEPATOLOGY 2011)