Molecular Pathological Diagnosis of Thyroid Tumors Using Spatially Resolved Metabolomics

• Published in: Molecules (Basel, Switzerland) Vol. 27; no. 4; p. 1390
• Main Authors: Huang, Luojiao, Mao, Xinxin, Sun, Chenglong, Li, Tiegang, Song, Xiaowei, Li, Jiangshuo, Gao, Shanshan, Zhang, Ruiping, Chen, Jie, He, Jiuming, Abliz, Zeper
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 18.02.2022; MDPI
• Subjects: Adenoma; Air flow; Biomarkers; Biomarkers, Tumor; Diagnosis; Diagnostic systems; Fluorescent Antibody Technique; Heterogeneity; Humans; Immunohistochemistry; in situ pathology diagnosis; Ionization; Mass spectrometry; mass spectrometry imaging; Mass spectroscopy; Metabolites; Metabolome; Metabolomics; Metabolomics - methods; Model accuracy; molecular diagnosis model; Molecular Diagnostic Techniques; Nodules; Prognosis; ROC Curve; Spatial distribution; Spectrometry, Mass, Electrospray Ionization; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; Thyroid cancer; Thyroid carcinoma; Thyroid Neoplasms - diagnosis; Thyroid Neoplasms - etiology; Thyroid Neoplasms - metabolism; tumor heterogeneity; tumor metabolism; Tumors; Visual discrimination; in situ pathology diagnosis; mass spectrometry imaging; molecular diagnosis model; tumor metabolism; tumor heterogeneity
• ISSN: 1420-3049; 1420-3049
• DOI: 10.3390/molecules27041390

The pathological diagnosis of benign and malignant follicular thyroid tumors remains a major challenge using the current histopathological technique. To improve diagnosis accuracy, spatially resolved metabolomics analysis based on air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) technique was used to establish a molecular diagnostic strategy for discriminating four pathological types of thyroid tumor. Without any specific labels, numerous metabolite features with their spatial distribution information can be acquired by AFADESI-MSI. The underlying metabolic heterogeneity can be visualized in line with the cellular heterogeneity in native tumor tissue. Through micro-regional feature extraction and in situ metabolomics analysis, three sets of metabolic biomarkers for the visual discrimination of benign follicular adenoma and differentiated thyroid carcinomas were discovered. Additionally, the automated prediction of tumor foci was supported by a diagnostic model based on the metabolic profile of 65 thyroid nodules. The model prediction accuracy was 83.3% when a test set of 12 independent samples was used. This diagnostic strategy presents a new way of performing in situ pathological examinations using small molecular biomarkers and provides a model diagnosis for clinically indeterminate thyroid tumor cases.