Screening candidate microRNA-mRNA network for predicting the response to chemoresistance in osteosarcoma by bioinformatics analysis.

The search for biomarkers is important for providing more targeted treatments for osteosarcoma patients with chemoresistance. In this study, differentially expressed microRNAs (miRNAs) were identified from miRNA expression profiles. And the target messenger RNAs (mRNAs) of miRNA were obtained from two websites in public domains. Analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway by these miRNA targets suggests that they may have potential links to osteosarcoma chemoresistance. In the protein-protein interaction (PPI) network, we screened three subnetworks and 10 hub RNAs, and analyzed through KEGG pathway and searched the PubMed database, indicating that they were significantly associated with drug resistance. Then we found 12 key mRNAs by analyzing the mRNA expression profile. Survival analyses showed that most of the 10 hub mRNAs and 12 key mRNAs had a significant influence on the prognosis of patients with chemoresistance osteosarcoma. A miRNA-mRNA network is constructed by integrating mRNAs and miRNAs information. The network biomarkers in this study have an advantage over traditional single-molecule biomarkers in terms of predictive power. And the mRNAs in this network biomarkers are supported by survival analysis or by existing theories. These results will contribute to the choice of chemotherapy before treatment and the prediction of patient prognosis.