Kunlun Chen1, Pengfei Zhu1, Yuan Liao1, Lei Yan2, Ruo Feng3, Wenlong Zhai1. 1. Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China. 2. Department of Emergency Surgery, Henan Oilfield General Hospital, Nanyang, Henan, 473000, People's Republic of China. 3. Department of Histology and Embryology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou, Henan, 450052, People's Republic of China.
Abstract
BACKGROUND: Hepatocellular carcinoma (HCC) is a major public health burden worldwide owing to high incidence and poor prognosis. Although numerous apoptotic genes were disclosed in HCC, the prognostic value and clinical utility of the genes remained unclear. METHODS: The differentially expressed genes (DEGs) were identified in the microarray and RNA sequencing data from public databases. The apoptosis-related differentially expressed genes (AR-DEGs) were selected to construct a Lasso-penalized Cox regression model. The signature including five apoptotic genes was used to calculate risk score. Then, the receiver operating characteristic (ROC) and survival analysis were conducted based on the signature. A nomogram containing the signature and clinical characteristics was plotted to visualized the prognosis prediction. Finally, the enrichment analysis was performed in the Gene Ontology (GO) to investigate the potential mechanism. RESULTS: Patients with high risk scores were related to worse overall survival than those with low risk. The 3-year and 5-year area under curve (AUC) values of the signature were above 0.7 in databases. And the nomogram presented reliable net benefits for the survival prediction. The nomogram was also tested by probability calibration curves and Decision Curve Analysis (DCA). Furthermore, the five differentially expressed genes were verified again in the HCC clinical specimens with real-time PCR and Western Blot. CONCLUSION: Collectively, the present study formed a novel signature based on five apoptotic genes, and this possibly predicted prognosis and strengthened the communication with HCC patients about the likely treatment.
BACKGROUND: Hepatocellular carcinoma (HCC) is a major public health burden worldwide owing to high incidence and poor prognosis. Although numerous apoptotic genes were disclosed in HCC, the prognostic value and clinical utility of the genes remained unclear. METHODS: The differentially expressed genes (DEGs) were identified in the microarray and RNA sequencing data from public databases. The apoptosis-related differentially expressed genes (AR-DEGs) were selected to construct a Lasso-penalized Cox regression model. The signature including five apoptotic genes was used to calculate risk score. Then, the receiver operating characteristic (ROC) and survival analysis were conducted based on the signature. A nomogram containing the signature and clinical characteristics was plotted to visualized the prognosis prediction. Finally, the enrichment analysis was performed in the Gene Ontology (GO) to investigate the potential mechanism. RESULTS: Patients with high risk scores were related to worse overall survival than those with low risk. The 3-year and 5-year area under curve (AUC) values of the signature were above 0.7 in databases. And the nomogram presented reliable net benefits for the survival prediction. The nomogram was also tested by probability calibration curves and Decision Curve Analysis (DCA). Furthermore, the five differentially expressed genes were verified again in the HCC clinical specimens with real-time PCR and Western Blot. CONCLUSION: Collectively, the present study formed a novel signature based on five apoptotic genes, and this possibly predicted prognosis and strengthened the communication with HCC patients about the likely treatment.
Authors: Alexandra Aronin; Shira Amsili; Tatyana B Prigozhina; Kobi Tzdaka; Jacob Rachmilewitz; Noam Shani; Mark L Tykocinski; Michal Dranitzki Elhalel Journal: PLoS One Date: 2013-10-10 Impact factor: 3.240