Identification of a serum microRNA expression signature for detection of lung cancer, involving miR-23b, miR-221, miR-148b and miR-423-3p

Objectives: Serum mircoRNAs (miRNAs), with their noticeable stability and unique expression pattern in patients with various diseases, are powerful novel non-invasive biomarkers for cancer detection. The objective of this study was to identify specific serum miRNAs as potential diagnostic markers for detection of lung cancer. Materials and methods: The expression of serum miRNA from treatment-naive lung cancer patients (LC), benign pulmonary disease patients (PD) and healthy controls (HC) were examined by PCR array. The study was divided into two phases: the biomarker-screening phase and the biomarker-validation phase. Logistic regression and receiver operating characteristics curve analyses were used to identify differentially expressed miRNA signatures that could distinguish LC from PD and HC. In addition, target genes of miRNAs were predicted using bioinformatic assays. Results: Ten miRNAs (let-7f, miR-126-3p, miR-148b, miR-151-5p, miR-199a-3p, miR-221, miR-23b, miR-26a, miR-27b, and miR-423-3p) in LC were significantly increased compared to those in PD and HC in biomarker-validation phase (P< 0.05). Bioinformatic analyses showed that predicted targets of these miRNAs might have a correlation with formation and development of cancer. Furthermore, we have developed classifiers including 4 miRNAs (miR-23b, miR-221, miR-148b and miR-423-3p) that can be demonstrated as a signature for LC detection, yielding a receiver operating characteristic curve area of 0.885. Conclusion: our findings define a distinct miRNA expression profile in LC cases. These 4-miRNA signatures (miR-23b, miR-221, miR-148b and miR-423-3p) may be considered as novel, non-invasive biomarker for LC diagnosis.