A panel of five-miRNA signature as a potential biomarker for predicting lung cancer

Lung cancer is one of the leading malignant tumors and the common cause of cancer-related deaths. In this study, in order to explore the pathogenesis of lung cancer, differentially expressed miRNAs (DEMs) were screened using high throughput data of lung cancer, combining with the function of the target genes and pathways. miRNA high-throughput data was download from The Cancer Genome Atlas (TCGA) to screen miRNAs between lung cancer and normal tissues, the DEMs were subjected to perform principal component analysis and ROC curves of the important miRNAs were analyzed so as to judge the accuracy of cancer diagnosis by miRNA. Then target genes were predicted by Targetscan software, and the up and down-regulated target genes were performed function enrichment analysis by DAVID respectively. After that, pathways annotations were executed on the target genes of DEMs through KEGG database, and the genes involved in significantly related pathways were further researched. Finally, survival analysis was accomplished between DEMs and the patient's survival time, and the miRNAs with prediction potentials were obtained. A total of 140 DEMs were screened, 58 DEMs were up-regulated including hsa-mir-519a-2, hsa-mir-522 and hsa-mir-520a; while 8 were down-regulated including hsa-mir-202, hsa-mir-675 and hsa-mir-323b. 5 miRNAs with diagnostic and preventive abilities were significantly associated with survival time. The selected important molecular targets may provide great clinical application value for the diagnostic and prognostic markers and targeted therapy, and it was expected to provide new ideas for the treatment of lung cancer.