Integrated bioinformatics analysis of microarray data from non-small cell lung cancer

Non-small cell lung cancer (NSCLC), with its high mortality rate, lack of early diagnostic markers and prevention of distant metastases are the main challenges in treatment. To identify potential miRNAs and key genes in NSCLC to find new biomarkers and target gene therapies. The GSE102286, GSE56036, GSE25508, GSE53882, GSE29248 and GSE101929 datasets were obtained from the Gene Expression Omnibus (GEO) database and screened for differentially co-expressed miRNAs (DE-miRNAs) and lncRNAs (DElncRs) by GEO2R and R software package. Pathway enrichment analysis of DE-miRNAs-target genes was performed by String and Funrich database to construct protein-protein interaction (PPI) and competing endogenous RNA (ceRNA) network and visualized with Cytoscape software. Nineteen co-expressed DE-miRNAs were scree-ned from five datasets. The 7683 predicted up-and down-regulated DE-miRNAs-target genes were significantly concentrated in cancer-related pathways. The top 10 hub nodes in the PPI were identified as hub genes, such as MYC, EGFR, HSP90AA1 and TP53, MYC, and ACTB. By constructing miRNA-hub gene networks, hsa-miR-21, hsa-miR-141, hsa-miR-200b and hsa-miR-30a, hsa-miR-30d, hsa-miR-145 may regulate most hub genes and hsa-miR-141, hsa-miR-200, hsa-miR-145 had higher levels in the miRNA and ceRNA regulatory networks, respectively. In conclusion, the identification of hsa-miR-21, hsa-miR-141, hsa-miR-200b hsa-miR-30a, hsa-miR-30d and hsa-miR-145 provides a new theoretical basis for understanding the development of NSCLC.