D-H Liu1, S-L Wang, Y Hua, G-D Shi, J-H Qiao, H Wei. 1. Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, China. weihong@cancerhosp-ln-cmu.com.
Abstract
OBJECTIVE: The competing endogenous RNA (ceRNA) presents a comprehensive regulatory network among lncRNAs, miRNAs and mRNA. The ceRNA provides significant information in understanding the pathology of cancer. This study aimed to explore a lncRNA-associated ceRNA network for predicting the overall survival of patients with hepatocellular carcinoma (HCC). MATERIALS AND METHODS: In this study, RNA-sequencing data of HCC were downloaded from The Cancer Genomes Atlas (TCGA) database. The module-trait relationship was analyzed with Weighted gene co-expression network analysis (WGCNA). The key module associated with tumor was identified, as well as the involved lncRNAs, mRNAs and miRNAs. The preliminary ceRNA network was constructed with Cytoscape. The survival analysis was further performed to screen survival-relevant lncRNAs, mRNAs and miRNAs, and then the survival-associated ceRNA network was reconstructed. RESULTS: Eventually, 5 lncRNAs, 10 miRNAs, and 25 mRNAs were included in the reconstructed ceRNA network. CONCLUSIONS: The identified lncRNAs were promising candidate biomarkers in HCC diagnosis and therapeutics. This analysis process was effective to construct ceRNA network. The result will be conductive to explore the significant lncRNAs and regulatory mechanism.
OBJECTIVE: The competing endogenous RNA (ceRNA) presents a comprehensive regulatory network among lncRNAs, miRNAs and mRNA. The ceRNA provides significant information in understanding the pathology of cancer. This study aimed to explore a lncRNA-associated ceRNA network for predicting the overall survival of patients with hepatocellular carcinoma (HCC). MATERIALS AND METHODS: In this study, RNA-sequencing data of HCC were downloaded from The Cancer Genomes Atlas (TCGA) database. The module-trait relationship was analyzed with Weighted gene co-expression network analysis (WGCNA). The key module associated with tumor was identified, as well as the involved lncRNAs, mRNAs and miRNAs. The preliminary ceRNA network was constructed with Cytoscape. The survival analysis was further performed to screen survival-relevant lncRNAs, mRNAs and miRNAs, and then the survival-associated ceRNA network was reconstructed. RESULTS: Eventually, 5 lncRNAs, 10 miRNAs, and 25 mRNAs were included in the reconstructed ceRNA network. CONCLUSIONS: The identified lncRNAs were promising candidate biomarkers in HCC diagnosis and therapeutics. This analysis process was effective to construct ceRNA network. The result will be conductive to explore the significant lncRNAs and regulatory mechanism.