Prognostic Biomarker Identification Through Integrating the Gene Signatures of Hepatocellular Carcinoma Properties
Many molecular classification and prognostic gene signatures for hepatocellular carcinoma (HCC) patients have been established based on genome-wide gene expression profiling; however, their generalizability is unclear. Herein, we systematically assessed the prognostic effects of these gene signature...
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doaj-05801d8d81ab4fe98bfe9611c41766a22020-11-25T01:22:13ZengElsevierEBioMedicine2352-39642017-05-0119C183010.1016/j.ebiom.2017.04.014Prognostic Biomarker Identification Through Integrating the Gene Signatures of Hepatocellular Carcinoma PropertiesJialin Cai0Bin Li1Yan Zhu2Xuqian Fang3Mingyu Zhu4Mingjie Wang5Shupeng Liu6Xiaoqing Jiang7Jianming Zheng8XinXin Zhang9Peizhan Chen10Translational Medicine Research Center, Ruijin Hospital North, Shanghai Jiao Tong University School of Medicine, Shanghai 201821, PR ChinaBiliary Tract Surgery Department I, Eastern Hepatobiliary Surgery Hospital, Secondary Military Medical University, Shanghai 200433, PR ChinaDepartment of Pathology, Changhai Hospital, Secondary Military Medical University, Shanghai 200433, PR ChinaTranslational Medicine Research Center, Ruijin Hospital North, Shanghai Jiao Tong University School of Medicine, Shanghai 201821, PR ChinaDepartment of Infectious Diseases, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, PR ChinaDepartment of Infectious Diseases, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, PR ChinaDepartment of Pathology, Changhai Hospital, Secondary Military Medical University, Shanghai 200433, PR ChinaBiliary Tract Surgery Department I, Eastern Hepatobiliary Surgery Hospital, Secondary Military Medical University, Shanghai 200433, PR ChinaDepartment of Pathology, Changhai Hospital, Secondary Military Medical University, Shanghai 200433, PR ChinaTranslational Medicine Research Center, Ruijin Hospital North, Shanghai Jiao Tong University School of Medicine, Shanghai 201821, PR ChinaTranslational Medicine Research Center, Ruijin Hospital North, Shanghai Jiao Tong University School of Medicine, Shanghai 201821, PR ChinaMany molecular classification and prognostic gene signatures for hepatocellular carcinoma (HCC) patients have been established based on genome-wide gene expression profiling; however, their generalizability is unclear. Herein, we systematically assessed the prognostic effects of these gene signatures and identified valuable prognostic biomarkers by integrating these gene signatures. With two independent HCC datasets (GSE14520, N = 242 and GSE54236, N = 78), 30 published gene signatures were evaluated, and 11 were significantly associated with the overall survival (OS) of postoperative HCC patients in both datasets. The random survival forest models suggested that the gene signatures were superior to clinical characteristics for predicting the prognosis of the patients. Based on the 11 gene signatures, a functional protein-protein interaction (PPI) network with 1406 nodes and 10,135 edges was established. With tissue microarrays of HCC patients (N = 60), we determined the prognostic values of the core genes in the network and found that RAD21, CDK1, and HDAC2 expression levels were negatively associated with OS for HCC patients. The multivariate Cox regression analyses suggested that CDK1 was an independent prognostic factor, which was validated in an independent case cohort (N = 78). In cellular models, inhibition of CDK1 by siRNA or a specific inhibitor, RO-3306, reduced cellular proliferation and viability for HCC cells. These results suggest that the prognostic predictive capacities of these gene signatures are reproducible and that CDK1 is a potential prognostic biomarker or therapeutic target for HCC patients.http://www.sciencedirect.com/science/article/pii/S2352396417301573Hepatocellular carcinomaOverall survivalBiomarkerNetworkGene signature |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jialin Cai Bin Li Yan Zhu Xuqian Fang Mingyu Zhu Mingjie Wang Shupeng Liu Xiaoqing Jiang Jianming Zheng XinXin Zhang Peizhan Chen |
spellingShingle |
Jialin Cai Bin Li Yan Zhu Xuqian Fang Mingyu Zhu Mingjie Wang Shupeng Liu Xiaoqing Jiang Jianming Zheng XinXin Zhang Peizhan Chen Prognostic Biomarker Identification Through Integrating the Gene Signatures of Hepatocellular Carcinoma Properties EBioMedicine Hepatocellular carcinoma Overall survival Biomarker Network Gene signature |
author_facet |
Jialin Cai Bin Li Yan Zhu Xuqian Fang Mingyu Zhu Mingjie Wang Shupeng Liu Xiaoqing Jiang Jianming Zheng XinXin Zhang Peizhan Chen |
author_sort |
Jialin Cai |
title |
Prognostic Biomarker Identification Through Integrating the Gene Signatures of Hepatocellular Carcinoma Properties |
title_short |
Prognostic Biomarker Identification Through Integrating the Gene Signatures of Hepatocellular Carcinoma Properties |
title_full |
Prognostic Biomarker Identification Through Integrating the Gene Signatures of Hepatocellular Carcinoma Properties |
title_fullStr |
Prognostic Biomarker Identification Through Integrating the Gene Signatures of Hepatocellular Carcinoma Properties |
title_full_unstemmed |
Prognostic Biomarker Identification Through Integrating the Gene Signatures of Hepatocellular Carcinoma Properties |
title_sort |
prognostic biomarker identification through integrating the gene signatures of hepatocellular carcinoma properties |
publisher |
Elsevier |
series |
EBioMedicine |
issn |
2352-3964 |
publishDate |
2017-05-01 |
description |
Many molecular classification and prognostic gene signatures for hepatocellular carcinoma (HCC) patients have been established based on genome-wide gene expression profiling; however, their generalizability is unclear. Herein, we systematically assessed the prognostic effects of these gene signatures and identified valuable prognostic biomarkers by integrating these gene signatures. With two independent HCC datasets (GSE14520, N = 242 and GSE54236, N = 78), 30 published gene signatures were evaluated, and 11 were significantly associated with the overall survival (OS) of postoperative HCC patients in both datasets. The random survival forest models suggested that the gene signatures were superior to clinical characteristics for predicting the prognosis of the patients. Based on the 11 gene signatures, a functional protein-protein interaction (PPI) network with 1406 nodes and 10,135 edges was established. With tissue microarrays of HCC patients (N = 60), we determined the prognostic values of the core genes in the network and found that RAD21, CDK1, and HDAC2 expression levels were negatively associated with OS for HCC patients. The multivariate Cox regression analyses suggested that CDK1 was an independent prognostic factor, which was validated in an independent case cohort (N = 78). In cellular models, inhibition of CDK1 by siRNA or a specific inhibitor, RO-3306, reduced cellular proliferation and viability for HCC cells. These results suggest that the prognostic predictive capacities of these gene signatures are reproducible and that CDK1 is a potential prognostic biomarker or therapeutic target for HCC patients. |
topic |
Hepatocellular carcinoma Overall survival Biomarker Network Gene signature |
url |
http://www.sciencedirect.com/science/article/pii/S2352396417301573 |
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