Spatial proteomics to overcome challenges in the diagnosis of follicular-patterned thyroid neoplasms entities: preliminary results

Lucrezia Principi;Giulia Capitoli;Davide Seminati;Vincenzo L’Imperio;Gabriele Casati;Stefania Galimberti;Fulvio Magni;Fabio Pagni;Isabella Piga

Last

2022-01-01

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Abstract

Introduction Noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTP) are low-risk thyroid lesions most often characterized by RAS-type mutations [1]. The current histological diagnostic criteria are still debated and even immunohistochemistry (IHC) and molecular approaches have not yet provided reliable diagnostic targets. The aim of this study is to characterize NIFTP lesions by Matrix-Assisted Laser Desorption/Ionization (MALDI)-Mass Spectrometry Imaging (MSI) in order to highlight proteomic signatures capable of overcoming the histological headaches. Materials and Methods Archived FFPE samples from ten NIFTP (n=5 RAS-mutated and n=5 RAS-wild type), one goiter and one papillary thyroid carcinoma (PTC) samples were trypsin digested and analyzed by MALDI-MSI proteomics using a rapifleX MALDI TissuetyperTM (Bruker Daltonik GmbH, Bremen, Germany) MALDI-TOF/TOF MS equipped with a Smartbeam 3D laser operating at 2kHz frequency. Mass spectra were acquired in reflectron-positive mode within the m/z 750 to 3000 mass range. Images of FFPE NIFTPs tissues were acquired with spatial resolution of 50 μm. After the analysis, CHCA matrix was removed and digested peptides were identified by nLC-ESI-MS/MS. Results Twelve FFPE specimens from RAS-mutated and RAS-wild-type NIFTPs, goiter and PTC were analyzed by MALDI-MSI in order to evaluate the technical feasibility of MALDI-MSI to characterize NIFTP lesions. Considering the proteome of the entire tissue sections, unsupervised segmentation analysis was able to highlight i) the presence of the nodular lesions that arose in the context of normal thyroid parenchyma, with the spectra deriving from the nodule and the parenchyma being clustered under separate nodes, ii) under the nodule node, a further separation enlightened the presence of both NIFTP nodular lesions and hyperplastic lesions, with the spectra deriving from the NIFTP nodules and the hyperplastic nodules being clustered under separate nodes. The high complexity of the proteomic data was investigated and unsupervised principal component analysis (PCA) was performed, highlighting specific patterns of the two NIFTP entities. Receiver Operative Characteristics (ROC) analysis was performed, with an AUC (Area Under the Curve) of ≥0.75 being required for a peak to be considered as statistically significant, and highlighted that five ions were able to discriminate the NIFTP RAS-mutated from the NIFTP RAS-wild type nodules. Conclusions These results underlined the unique capability of spatial proteomics to detect the proteomic signatures of RAS-mutated and RAS-wild-type NIFTP lesions highlighting proteomic alterations even within regions that are indistinguishable at the microscopic level, and the potential role of MALDI-MSI technology to support traditional pathology. Hence, spatial-proteomics is an outstanding approach to differentiate NIFTPs from other follicular-patterned features and to characterize classic and atypical cases. References 1 Esther Diana Rossi, W.C. Faquin, Z. Baloch, G. Fadda, L. Thompson, L. M. Larocca, L. Pantanowitz, Endocrine Pathology 2019 Jun; 30(2): 155–162. Acknowledgement This research was funded by Regione Lombardia: Programma degli interventi per la ripresa economica: sviluppo di nuovi accordi di collaborazione con le università per la ricerca, l’innovazione e il trasferimento tecnologico: NephropaThy and Ricerca Finalizzata GR-2019 12368592.