Bioinformatics Analysis of Dysregulated MicroRNA-Messenger RNA Networks in Small Cell Lung Cancer

Abstract

The present study aimed to identify a key module of differentially expressed miRNAs (DE-miRNAs) together with the corresponding differentially expressed mRNAs (DE-mRNAs) within small cell lung cancer (SCLC). Linear models were applied to ascertain the DE-miRNAs and DE-mRNAs in SCLC versus matched non-carcinoma samples obtained from the RNA expression datasets of GSE19945, GSE74190 and GSE6044. The common DE-miRNAs were identified using the Venn plot. Then, 3 databases were used to retrieve the DE-miRNAs target genes, and the intersection was taken for validating the shared target genes. Besides, Cytoscape was utilized for constructing the miRNAmRNA network for SCLC. Finally, a key module of five DE-miRNAs and four hub genes was determined based on the degree. In addition, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted for exploring those hub genes in terms of their functions along with the involved signal transduction pathways. Altogether 106 shared DE-miRNAs were identified, which were used to predict 63 common target genes. In addition, a key module of five DE-miRNAs (hsa-miR-17-5p, hsa-miR-20a-5p, hsa-miR-20b-5p, hsa-miR-93-5p and hsa-miR- 106b-5p) and four hub genes (SOX4, DPYSL2, TGFBR2 and F3) were extracted from the miRNAmRNA network according to their degree. Finally, the hub genes were subjected to GO as well as KEGG analysis, which revealed that cell cycle G1/S phase transition, the extracellular matrix, and cellular senescence signaling pathways exerted vial parts during SCLC progression. A key module of five DE-miRNAs and four hub genes may be potentially used as clinical biomarkers to predict SCLC.