A 5-MicroRNA Signature for Lung Squamous Cell Carcinoma Diagnosis and hsa-miR-31 for Prognosis

Abstract

PURPOSE: Recent studies have suggested that microRNA biomarkers could be useful for stratifying lung cancer subtypes, but microRNA signatures varied between different populations. Squamous cell carcinoma (SCC) is one major subtype of lung cancer that urgently needs biomarkers to aid patient management. Here, we undertook the first comprehensive investigation on microRNA in Chinese SCC patients. EXPERIMENTAL DESIGN: MicroRNA expression was measured in cancerous and noncancerous tissue pairs strictly collected from Chinese SCC patients (stages I-III), who had not been treated with chemotherapy or radiotherapy prior to surgery. The molecular targets of proposed microRNA were further examined. RESULTS: We identified a 5-microRNA classifier (hsa-miR-210, hsa-miR-182, hsa-miR-486-5p, hsa-miR-30a, and hsa-miR-140-3p) that could distinguish SCC from normal lung tissues. The classifier had an accuracy of 94.1% in a training cohort (34 patients) and 96.2% in a test cohort (26 patients). We also showed that high expression of hsa-miR-31 was associated with poor survival in these 60 SCC patients by Kaplan-Meier analysis (P = 0.007), by univariate Cox analysis (P = 0.011), and by multivariate Cox analysis (P = 0.011). This association was independently validated in a separate cohort of 88 SCC patients (P = 0.008, 0.011, and 0.003 in Kaplan-Meier analysis, univariate Cox analysis, and multivariate Cox analysis, respectively). We then determined that the tumor suppressor DICER1 is a target of hsa-miR-31. Expression of hsa-miR-31 in a human lung cancer cell line repressed DICER1 activity but not PPP2R2A or LATS2. CONCLUSIONS: Our results identified a new diagnostic microRNA classifier for SCC among Chinese patients and a new prognostic biomarker, hsa-miR-31.