Abstract
Background: Non-small cell lung cancer (NSCLC) accounts for about 85% of lung cancers. This study aimed to discover the potential miRNA biomarkers for early detection of NSCLC. Methods: Total circulating miRNAs were extracted from six patients and six volunteers and run on the miRNA chip. The differentially expressed miRNAs acquired by data mining were intersected with chip results, and qRT-PCR were carried out. Then the differentially miRNAs were validated by using a validation cohort (120 participants). ROC curves were established to evaluate the diagnostic efficacy of the differentially circulating miRNAs. The target genes of the differential miRNAs were identified using the miRTarBase database, and follow-up GO and KEGG enrichment analysis were conducted. Results: We identified 577 miRNA which screened according to the criteria (fold change > 2 and p value < 0.05). Among them, seven circulating miRNAs passed additional filtering based on data mining. These miRNAs were further validated in the training and validation cohort. miR-492, miR-590-3p, and miR-631 were differentially expressed in the patients' serum, and the area under the ROC curve (AUC) values of these miRNAs were 0.789, 0.792, and 0.711, respectively. When using them as a combination to discriminate healthy volunteers from patients, the AUC reached 0.828 (95% CI, 0.750-0.905, p = 0.000) with a sensitivity of 86.7% and specificity of 71.7%. The follow-up enrichment analysis showed that target genes of three miRNA were associated with tumorigenesis and progression, such as cell cycle and P53 signaling pathway. Conclusions: The combination of miR-492, miR-590-3p, and miR-631 can be utilized to distinguish healthy individuals and early-stage NSCLC patients. Impact: The combination of miR-492, miR-590-3p, and miR-631 might be a promising serum biomarker in patients for the early diagnosis of NSCLC.