Morphological and Molecular Assessment in Thyroid Cytology Using Cell-Capturing Scaffolds.


Journal

Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme
ISSN: 1439-4286
Titre abrégé: Horm Metab Res
Pays: Germany
ID NLM: 0177722

Informations de publication

Date de publication:
11 May 2020
Historique:
entrez: 12 5 2020
pubmed: 12 5 2020
medline: 12 5 2020
Statut: aheadofprint

Résumé

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 cytological evaluation is considered the method of choice. About 20% of FNA biopsies on thyroid nodules, however, show indeterminate cytological features and may require diagnostic surgery. Several immunocytochemical and molecular markers have been proposed to improve classification of thyroid nodules, but these tests require adequate cell amount and cytological 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 immunohistochemical 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 cellularity of the samples harvested by FNA and that its paraffin sections mimic the morphology of those obtained from real histological tissue. Immunohistochemistry on CytoMatrix samples 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 CytoMatrix could be a reliable tool to overcome the current limits of traditional collection methods for the study of thyroid cytology, thereby improving their reliability for a conclusive diagnostic interpretation.

Identifiants

pubmed: 32392586
doi: 10.1055/a-1157-6419
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© Georg Thieme Verlag KG Stuttgart · New York.

Déclaration de conflit d'intérêts

The authors declare that they have no conflict of interest. Anna Crescenzi, Marcella Trombetta, Alberto Raine and Chiara Taffon are co-authors of the Cytomatrix patent.

Auteurs

Stefania Scarpino (S)

Department of Clinical and Molecular Medicine, Pathology Unit, Sant'Andrea Hospital, Sapienza University of Rome, Albano Laziale (RM), Italy.

Silvia Taccogna (S)

Pathology Unit, Regina Apostolorum Hospital, Albano Laziale (RM), Italy.

Giuseppina Pepe (G)

Department of Clinical and Molecular Medicine, Pathology Unit, Sant'Andrea Hospital, Sapienza University of Rome, Albano Laziale (RM), Italy.

Enrico Papini (E)

Endocrinology and Metabolism Unit, Regina Apostolorum Hospital, Albano Laziale (RM), Italy.

Martina D'Angelo (M)

Pathology Unit, Regina Apostolorum Hospital, Albano Laziale (RM), Italy.

Federica Cascone (F)

Pathology Unit, University Hospital Campus Bio-Medico of Rome, Rome, Italy.

Daniele Nicoletti (D)

Pathology Unit, University Hospital Campus Bio-Medico of Rome, Rome, Italy.

Rinaldo Guglielmi (R)

Endocrinology and Metabolism Unit, Regina Apostolorum Hospital, Albano Laziale (RM), Italy.

Andrea Palermo (A)

Unit of Endocrinology and Diabetes, University Hospital Campus Bio-Medico of Rome, Rome, Italy.

Marcella Trombetta (M)

Department of Engineering, University Campus Bio-Medico of Rome, Rome, Italy.

Alberto Rainer (A)

Department of Engineering, University Campus Bio-Medico of Rome, Rome, Italy.

Chiara Taffon (C)

Pathology Unit, University Hospital Campus Bio-Medico of Rome, Rome, Italy.

Anna Crescenzi (A)

Pathology Unit, University Hospital Campus Bio-Medico of Rome, Rome, Italy.

Classifications MeSH