Identification of predictive biomarkers for early diagnosis of larynx carcinoma based on microRNA expression data

Abstract

The abnormal expression of microRNAs (miRNAs) plays a key role in tumorigenesis. In order to identify potential miRNA biomarkers for early diagnosis of larynx carcinoma, we employed a miRNA microarray technique and applied bioinformatic algorithms to characterize miRNA classifiers in early larynx carcinoma and normal esophageal mucosa tissue samples from 69 patients who were selected retrospectively for this study. We identified 47 miRNAs that were significantly differentially expressed in primary larynx tumor tissues compared to normal tissues using a SAM algorithm. Of these, 30 were up-regulated and 17 down-regulated in early larynx cancer, including hsa-miR-657, which was overexpressed, and hsa-miR-1287, which was underexpressed. These two candidate miRNA biomarkers were combined as a single classifier to recognize the biological characteristics in early larynx carcinoma. Real-time quantitative reverse-transcription PCR validated the microarray results in both trial and test samples. The hsa-miR-657-hsa-miR-1287 classifier displayed high sensitivity and specificity for discriminating between early larynx carcinoma and normal mucosa tissues, suggesting they may be suitable as potential predictive biomarkers for the early diagnosis of larynx carcinoma.

Keywords: Larynx carcinoma; biomarkers; early diagnosis; microRNA.