Bioinformatics Identification of miRNA-mRNA Regulatory Network Contributing Primary Lung Cancer

Abstract

Introduction: In clinical practice, distinguishing invasive lung tumors from primary tumors remains a challenge. With recent advances in understanding biological alterations of tumorigenesis and molecular analytic technologies, using these molecular alterations can be sensitive and tumor-specific as biomarker for the stratification of patients. In this study, the molecular network of miRNA-mRNA contributing to primary lung cancer has been assessed by bioinformatics approaches.
 Methods: In this analytical-observational study gene expression profiles of patients with primary lung cancer were collected from the RNASeq data of the Cancer Genome Atlas (TCGA) database by TCGAbiolinks package. With edgeR and limma packages in R, non-specific expression genes were filtered and the significant differentially expressed mRNAs and miRNAs between tumor tissues and normal tissues were saved and their targets were predicted by 2 databases; miRWalk, and Targetscan. Subsequently, the interaction regulatory network of miRNA-mRNA was visualized using Cytoscape software.
 Results: By miRNA-mRNA network analysis revealed that, 7 miRNAs included; hsa-miR-373-3p, hsa-let-7a-5p, hsa-miR-23b-3p, hsa-miR-152-3p, hsa-miR -216a-3p, hsa-miR-106-5p, hsa-let-7i-5p and 6 miRNAs including; has-miR-107, has-miR-17-5p, has-185-5p, has-miR-34a- 5p, has-miR-130a-5p and has-96-5p, mediated regulation of up-regulated and down-regulated mRNAs in primary lung cancer patients, respectively.
 Conclusion: This bioinformatics study proposes a miRNA–mRNA network associated with primary lung cancer, which may help to screening and new therapeutic targets for primary lung cancer as prognostic marker.