Integrative analysis of ceRNA network and DNA methylation associated with gene expression in malignant pheochromocytomas: a study based on The Cancer Genome Atlas

BACKGROUND: Competitive endogenous RNAs (ceRNAs) have revealed a new mechanism of interaction between RNAs. Epigenetic regulation in the gene expression dynamics has become increasingly important in malignant pheochromocytomas (PCCs). We performed an integrative analysis of ceRNA networks and DNA methylation to identify key biomarkers and contribute to the understanding of the molecular biological mechanisms of malignant PCCs. METHODS: Differentially expressed genes in malignant PCCs and controls were identified from The Cancer Genome Atlas database by using the Limma package in R (v3.4.4). An abnormal lncRNA-miRNA-mRNA ceRNA network was constructed for malignant PCCs, and function enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery. For DNA methylation datasets, the methylation analysis package was used in identifying differential methylation genes, and potential prognostic genes were identified by Kaplan-Meier survival analysis. RESULTS: A total of 447 lncRNAs, 26 miRNAs, and 1,607 mRNAs were found to be differentially expressed in malignant PCCs as compared with those in normal samples. We then constructed an abnormal lncRNA-miRNA-mRNA ceRNA network for malignant PCCs. The network consisted of 12 lncRNAs, 6 miRNAs, and 220 mRNAs. Functional enrichment analysis showed that differentially expressed mRNAs were particularly enriched in the biological process, cellular component, and molecular function. Furthermore, four differentially expressed mRNAs from ceRNAs were identified through the cross-analysis of gene expression and DNA methylation profiles. LncRNA C9orf147 and 6 out of 220 mRNAs were indicated as prognostic biomarkers for patients with malignant PCCs (P<0.05). CONCLUSIONS: Our research increases the understanding of the pathogenesis of malignant PCCs and offers potential genes as underlying therapeutic targets or prognostic biomarkers.