Serum expression of selected miRNAs in patients with laryngeal squamous cell carcinoma (LSCC)

Abstract

Background: The aim of the present study was to identify specific serum miRNAs (preoperative serum samples compared to healthy controls) as potential diagnostic markers for detection in laryngeal squamous cell carcinoma (LSCC). Serum samples obtained from 66 patients with LSCC were compared with 100 healthy control subjects. Additionally, miRNA levels were evaluated to identify possible correlations with clinicopathological features. Methods: The expression of 377 miRNAs (screening set) was evaluated by microarray screening. The most differentially expressed miRNAs were validated by high-throughput real-time quantitative polymerase chain reaction (RT-qPCR) in the group of LSCC patients and healthy controls. Receiver-operator characteristic (ROC) curve analysis was conducted to evaluate the diagnostic accuracy of the highly and significantly identified deregulated miRNA(s) as potential candidate biomarker(s). Results: According to the array analysis, eleven miRNAs revealed an altered expression profile. The levels of serum expression of miR-31, miR-141, miR-149a, miR-182, LET-7a, miR-4853p, miR-122 and miR-33 were up-regulated, and those of miR-145, miR-223 and miR-133a down-regulated, in the LSCC group compared to healthy controls. ROC curve analyses revealed an AUC (area under the ROC curve) of 1.00 (95%Cl: 0.999-1.00; P < 0.001) for miR-31 and LET-7a, 1.00 (95%Cl: 1.00-1.00; P < 0.001) for miR-33 respectively, indicating that these three miRNAs had an additive effect regarding diagnostic value. No statistically significant differences were found between the serum levels of these eleven miRNAs and the tested clinicopathological features. Conclusion: Our findings outline a distinct miRNA expression profile in laryngeal cancer (LC) cases which can be used to diagnose LSCC patients with high sensitivity and specificity. Particular miRNA signatures (miR-31, LET-7a and miR-33) may be considered as novel, non-invasive biomarkers for LC diagnosis.