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MicroRNA Expression Profiling of Thyroid Tumors: Biological Significance and Diagnostic Utility

Department of Pathology (M.N.N., Y.E.N.), University of Pittsburgh Medical Center, and Department of Biostatistics (G.C.T.), University of Pittsburgh, Pittsburgh, Pennsylvania 15261; Department of Otolaryngology-Head and Neck Surgery (D.S.), University of Cincinnati College of Medicine, Cincinnati, Ohio 45267; and Department of Pathology (D.D.), Cincinnati Children’s Hospital, Cincinnati, Ohio 45229

Address all correspondence and requests for reprints to: Dr. Marina Nikiforova, Department of Pathology, University of Pittsburgh, 3550 Terrace Street, Pittsburgh, Pennsylvania 15261. E-mail: nikiforovamn{at}upmc.edu.

Objective: MicroRNA (miRNA) expression is deregulated in many types of human cancers. We sought to investigate the expression patterns of miRNA in all major types of thyroid tumors, including tumors carrying distinct oncogenic mutations, and to explore the utility of miRNA profiling for the preoperative diagnosis of thyroid nodules.

Design: miRNA expression levels were detected in 60 surgically removed thyroid neoplastic and nonneoplastic samples and in 62 fine-needle aspiration (FNA) samples by RT-PCR using TaqMan MicroRNA Panel or individual miRNA sequence-specific primers. miRNA expression levels were calculated relative to normal thyroid tissue. All tumors were genotyped for most common mutations.

Results: Various histopathological types of thyroid tumors, including those deriving from the same cell type, showed significantly different profiles of miRNA expression. Oncocytic tumors, conventional follicular tumors, papillary carcinomas, and medullary carcinomas formed distinct clusters on the unsupervised hierarchical clustering analysis. Significant correlation between miRNA expression patterns and somatic mutations was observed in papillary carcinomas. A set of seven miRNAs (miR-187, miR-221, miR-222, miR-146b, miR-155, miR-224, and miR-197) that were most differentially overexpressed in thyroid tumors vs. hyperplastic nodules in the surgical samples was validated in the FNA samples, showing high accuracy of thyroid cancer detection.

Conclusions: In this study, we demonstrate that various histopathological types of thyroid tumors have distinct miRNA profiles, which further differ within the same tumor type, reflecting specific oncogenic mutations. A limited set of miRNAs can be used diagnostically with high accuracy to detect thyroid cancer in the surgical and preoperative FNA samples.

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