Detection of metabolites discriminating subtypes of thyroid cancer: Molecular profiling of FFPE samples using the GC/MS approach.

One of the critical issues in thyroid cancer diagnostic is differentiation between follicular adenoma, follicular carcinoma and the follicular variant of papillary carcinoma, which in some cases is not possible based on histopathological features only. In this paper we performed molecular profiling of thyroid tissue aiming to identify metabolites characteristic for different types of thyroid cancer. FFPE tissue specimens were analysed from 5 different types of thyroid malignancies (follicular, papillary/classical variant, papillary/follicular variant, medullary and anaplastic cancers), benign follicular adenoma and normal thyroid. Extracted metabolites were identified and semi-quantified using the GC/MS approach. There were 28 metabolites identified, whose abundances were significantly different among different types of thyroid tumours, including lipids, carboxylic acids, and saccharides. We concluded, that multi-component metabolome signature could be used for classification of different subtypes of follicular thyroid lesions. Moreover, potential applicability of the GC/MS-based analysis of FFPE tissue samples in diagnostics of thyroid cancer has been proved.