The increased frequency of thyroid nodules is paralleled by the rise of thyroid cancer diagnosis. To define the nature of most thyroid nodules, fine needle aspiration (FNA) followed by cyto- logical evaluation is considered the method of choice. About 20 % of FNA biopsies on thyroid nodules, however, show inde- terminate cytological features and may require diagnostic surgery. Several immunocytochemical and molecular markers have been proposed to improve classification of thyroid nod - ules, but these tests require adequate cell amount and cyto- logical paraffin inclusion. Polymeric matrices were recently proposed for the collection of cells for diagnostic purposes. In this study, we evaluated the diagnostic use of a new matrix (CytoMatrix). Morphological, molecular and immunohisto- chemical investigations were carried out on 23 FNA samples included in CytoMatrix and compared with data obtained from the definitive histology of surgical samples. Our results showed that CytoMatrix is suitable to capture and preserve the cellu- larity of the samples harvested by FNA and that its paraffin sections mimic the morphology of those obtained from real histological tissue. Immunohistochemistry on CytoMatrix sam- ples was consistent with the immunophenotypical profile of the corresponding histological surgical specimens. Mutational analysis of the BRAF (V600E) gene performed on CytoMatrix inclusions and paired surgical tissue matched in all but one cases while matrix immunohistochemistry identified 91.6 % of BRAF mutated samples. In conclusion, we suggest that CytoMa- trix could be a reliable tool to overcome the current limits of traditional collection methods for the study of thyroid cytolo- gy, thereby improving their reliability for a conclusive diagnos- tic interpretation
Morphological and Molecular Assessment in Thyroid Cytology Using Cell-Capturing Scaffolds / Scarpino, S; Taccogna, S; Pepe, G; Papini, E; D’Angelo, M; Cascone, F; Nicoletti, D; Guglielmi, R; Palermo, A; Trombetta, M; Rainer, A; Taffon, C; Crescenzi, A. - In: HORMONE AND METABOLIC RESEARCH. - ISSN 0018-5043. - 52:11(2020), pp. 803-808. [10.1055/a-1157-6419]
Morphological and Molecular Assessment in Thyroid Cytology Using Cell-Capturing Scaffolds
Crescenzi A
2020
Abstract
The increased frequency of thyroid nodules is paralleled by the rise of thyroid cancer diagnosis. To define the nature of most thyroid nodules, fine needle aspiration (FNA) followed by cyto- logical evaluation is considered the method of choice. About 20 % of FNA biopsies on thyroid nodules, however, show inde- terminate cytological features and may require diagnostic surgery. Several immunocytochemical and molecular markers have been proposed to improve classification of thyroid nod - ules, but these tests require adequate cell amount and cyto- logical paraffin inclusion. Polymeric matrices were recently proposed for the collection of cells for diagnostic purposes. In this study, we evaluated the diagnostic use of a new matrix (CytoMatrix). Morphological, molecular and immunohisto- chemical investigations were carried out on 23 FNA samples included in CytoMatrix and compared with data obtained from the definitive histology of surgical samples. Our results showed that CytoMatrix is suitable to capture and preserve the cellu- larity of the samples harvested by FNA and that its paraffin sections mimic the morphology of those obtained from real histological tissue. Immunohistochemistry on CytoMatrix sam- ples was consistent with the immunophenotypical profile of the corresponding histological surgical specimens. Mutational analysis of the BRAF (V600E) gene performed on CytoMatrix inclusions and paired surgical tissue matched in all but one cases while matrix immunohistochemistry identified 91.6 % of BRAF mutated samples. In conclusion, we suggest that CytoMa- trix could be a reliable tool to overcome the current limits of traditional collection methods for the study of thyroid cytolo- gy, thereby improving their reliability for a conclusive diagnos- tic interpretation| File | Dimensione | Formato | |
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