Construction of a ceRNA network and a genomic-clinicopathologic nomogram to predict survival for HBV-related HCC

AbstractSome lncRNA-associated competing endogenous RNAs (ceRNAs) are considered as potential biomarkers for targeted therapies and prognosis in human cancer. In our present study, we aimed to construct a ceRNA network and establish a genomic-clinicopathologic nomogram to provide insights into the molecular mechanisms and predict survival for HBV-related HCC. The Cancer Genome Atlas (TCGA) database was applied to collect the data of LIHC RNA-seq dataset and miRNA-seq dataset as well as the clinicopathological information. Identification of differentially expressed RNAs (mRNAs, lncRNAs, and miRNAs) between HBV-related HCC samples and normal samples was conducted using Limma package in R. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for performing the functional enrichment analysis of differentially expressed mRNAs. The ceRNA network was carried out using Cytoscape. The LASSO-penalized Cox regression analysis was implemented to identify HCC-related lncRNAs, and the multivariate Cox regression analysis was conducted for the establishment of a genomic-clinicopathology nomogram. A total of 1859 DEmRNAs, 113 DElncRNAs, and 89 DEmiRNAs were screened out etween HBV-related HCC samples and normal samples. A ceRNA network including 44 DEmRNAs, 7 DElncRNAs, and 20 DEmiRNAs was constructed. 7 DElncRNAs (PVT1, LINC01138, LINC02499, AL355488.2, FGF14-AS2, MAFG-AS1 and LINC00261) were finally identified as prognostic indicators. The area under the cu...
Source: Human Cell - Category: Cytology Source Type: research