Analysis of Hashimoto's thyroiditis on fine needle aspiration samples by MALDI-Imaging.


Journal

Biochimica et biophysica acta. Proteins and proteomics
ISSN: 1878-1454
Titre abrégé: Biochim Biophys Acta Proteins Proteom
Pays: Netherlands
ID NLM: 101731734

Informations de publication

Date de publication:
11 2020
Historique:
received: 29 02 2020
revised: 04 06 2020
accepted: 27 06 2020
pubmed: 10 7 2020
medline: 15 12 2020
entrez: 10 7 2020
Statut: ppublish

Résumé

Matrix-Assisted Laser Desorption/Ionization (MALDI)-Mass Spectrometry imaging (MSI) has been applied in various diseases aimed to biomarkers discovery. In this study diagnosis and prognosis of Hashimoto Thyroiditis (HT) in cytopathology by MALDI-MSI has been investigated. Specimens from a routine series of subjects who underwent UltraSound-guided thyroid Fine Needle Aspirations (FNAs) were used. The molecular classifier trained in a previous study was modified to include HT as a separate entity in the group of benign lesions, in the diagnostic proteomic triage of thyroid nodules. The statistical analysis confirmed the existence of signals that HT shares with hyperplastic lesions and others that are specific and characterize this subgroup. Statistically relevant HT-related peaks were included in the model. Then, the discriminatory capability of the classifier was tested in a second validation phase, showing a good agreement with cytological diagnoses. The possibility to overlap the molecular signatures of both the lymphocytes and epithelial cells components (ROIs or pixel-by-pixel analysis) confirmed the composite proteomic background of HT. These results open the way to their possible translation as alternative serum biomarkers of this autoimmune condition.

Identifiants

pubmed: 32645440
pii: S1570-9639(20)30128-X
doi: 10.1016/j.bbapap.2020.140481
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

140481

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Giulia Capitoli (G)

Bicocca Bioinformatics Biostatistics and Bioimaging B4 Center, School of Medicine and Surgery, University of Milano - Bicocca, Monza, Italy.

Isabella Piga (I)

Proteomics and Metabolomics, School of Medicine and Surgery, University of Milano-Bicocca, Vedano al Lambro, Italy.

Francesca Clerici (F)

Proteomics and Metabolomics, School of Medicine and Surgery, University of Milano-Bicocca, Vedano al Lambro, Italy.

Virginia Brambilla (V)

Pathology, Department of Medicine and Surgery, University of Milano-Bicocca, San Gerardo Hospital, ASST, Monza, Italy.

Allia Mahajneh (A)

Proteomics and Metabolomics, School of Medicine and Surgery, University of Milano-Bicocca, Vedano al Lambro, Italy.

Davide Leni (D)

Department of radiology, San Gerardo Hospital, ASST, Monza, Italy.

Mattia Garancini (M)

Department of Surgery, San Gerardo Hospital, ASST, Monza, Italy.

Angela Ida Pincelli (AI)

Department of Endocrinology, San Gerardo Hospital, ASST, Monza, Italy.

Vincenzo L'Imperio (V)

Pathology, Department of Medicine and Surgery, University of Milano-Bicocca, San Gerardo Hospital, ASST, Monza, Italy.

Stefania Galimberti (S)

Bicocca Bioinformatics Biostatistics and Bioimaging B4 Center, School of Medicine and Surgery, University of Milano - Bicocca, Monza, Italy.

Fulvio Magni (F)

Proteomics and Metabolomics, School of Medicine and Surgery, University of Milano-Bicocca, Vedano al Lambro, Italy. Electronic address: fulvio.magni@unimib.it.

Fabio Pagni (F)

Pathology, Department of Medicine and Surgery, University of Milano-Bicocca, San Gerardo Hospital, ASST, Monza, Italy. Electronic address: fabio.pagni@unimib.it.

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