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Molecular classification of thyroid lesions by combined testing for miRNA gene expression and somatic gene alterations

Multiple molecular markers contribute to the pathogenesis of thyroid cancer and can provide valuable information to improve disease diagnosis and patient management. We performed a comprehensive evaluation of miRNA gene expression in diverse thyroid lesions (n = 534) and developed predictive models...

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Autores principales: Wylie, Dennis, Beaudenon‐Huibregtse, Sylvie, Haynes, Brian C., Giordano, Thomas J., Labourier, Emmanuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4907059/
https://www.ncbi.nlm.nih.gov/pubmed/27499919
http://dx.doi.org/10.1002/cjp2.38
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author Wylie, Dennis
Beaudenon‐Huibregtse, Sylvie
Haynes, Brian C.
Giordano, Thomas J.
Labourier, Emmanuel
author_facet Wylie, Dennis
Beaudenon‐Huibregtse, Sylvie
Haynes, Brian C.
Giordano, Thomas J.
Labourier, Emmanuel
author_sort Wylie, Dennis
collection PubMed
description Multiple molecular markers contribute to the pathogenesis of thyroid cancer and can provide valuable information to improve disease diagnosis and patient management. We performed a comprehensive evaluation of miRNA gene expression in diverse thyroid lesions (n = 534) and developed predictive models for the classification of thyroid nodules, alone or in combination with genotyping. Expression profiling by reverse transcription‐quantitative polymerase chain reaction in surgical specimens (n = 257) identified specific miRNAs differentially expressed in 17 histopathological categories. Eight supervised machine learning algorithms were trained to discriminate benign from malignant lesions and evaluated for accuracy and robustness. The selected models showed invariant area under the receiver operating characteristic curve (AUC) in cross‐validation (0.89), optimal AUC (0.94) in an independent set of preoperative thyroid nodule aspirates (n = 235), and classified 92% of benign lesions as low risk/negative and 92% of malignant lesions as high risk/positive. Surgical and preoperative specimens were further tested for the presence of 17 validated oncogenic gene alterations in the BRAF, RAS, RET or PAX8 genes. The miRNA‐based classifiers complemented and significantly improved the diagnostic performance of the 17‐mutation panel (p < 0.001 for McNemar's tests). In a subset of resected tissues (n = 54) and in an independent set of thyroid nodules with indeterminate cytology (n = 42), the optimized ThyraMIR Thyroid miRNA Classifier increased diagnostic sensitivity by 30–39% and correctly classified 100% of benign nodules negative by the 17‐mutation panel. In contrast, testing with broad targeted next‐generation sequencing panels decreased diagnostic specificity by detecting additional mutations of unknown clinical significance in 19–39% of benign lesions. Our results demonstrate that, independent of mutational status, miRNA expression profiles are strongly associated with altered molecular pathways underlying thyroid tumorigenesis. Combined testing for miRNA gene expression and well‐established somatic gene alterations is a novel diagnostic strategy that can improve the preoperative diagnosis and surgical management of patients with indeterminate thyroid nodules.
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spelling pubmed-49070592016-08-05 Molecular classification of thyroid lesions by combined testing for miRNA gene expression and somatic gene alterations Wylie, Dennis Beaudenon‐Huibregtse, Sylvie Haynes, Brian C. Giordano, Thomas J. Labourier, Emmanuel J Pathol Clin Res Original Articles Multiple molecular markers contribute to the pathogenesis of thyroid cancer and can provide valuable information to improve disease diagnosis and patient management. We performed a comprehensive evaluation of miRNA gene expression in diverse thyroid lesions (n = 534) and developed predictive models for the classification of thyroid nodules, alone or in combination with genotyping. Expression profiling by reverse transcription‐quantitative polymerase chain reaction in surgical specimens (n = 257) identified specific miRNAs differentially expressed in 17 histopathological categories. Eight supervised machine learning algorithms were trained to discriminate benign from malignant lesions and evaluated for accuracy and robustness. The selected models showed invariant area under the receiver operating characteristic curve (AUC) in cross‐validation (0.89), optimal AUC (0.94) in an independent set of preoperative thyroid nodule aspirates (n = 235), and classified 92% of benign lesions as low risk/negative and 92% of malignant lesions as high risk/positive. Surgical and preoperative specimens were further tested for the presence of 17 validated oncogenic gene alterations in the BRAF, RAS, RET or PAX8 genes. The miRNA‐based classifiers complemented and significantly improved the diagnostic performance of the 17‐mutation panel (p < 0.001 for McNemar's tests). In a subset of resected tissues (n = 54) and in an independent set of thyroid nodules with indeterminate cytology (n = 42), the optimized ThyraMIR Thyroid miRNA Classifier increased diagnostic sensitivity by 30–39% and correctly classified 100% of benign nodules negative by the 17‐mutation panel. In contrast, testing with broad targeted next‐generation sequencing panels decreased diagnostic specificity by detecting additional mutations of unknown clinical significance in 19–39% of benign lesions. Our results demonstrate that, independent of mutational status, miRNA expression profiles are strongly associated with altered molecular pathways underlying thyroid tumorigenesis. Combined testing for miRNA gene expression and well‐established somatic gene alterations is a novel diagnostic strategy that can improve the preoperative diagnosis and surgical management of patients with indeterminate thyroid nodules. John Wiley and Sons Inc. 2016-02-08 /pmc/articles/PMC4907059/ /pubmed/27499919 http://dx.doi.org/10.1002/cjp2.38 Text en © 2016 John Wiley and Sons Ltd and The Pathological Society of Great Britain and Ireland This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Wylie, Dennis
Beaudenon‐Huibregtse, Sylvie
Haynes, Brian C.
Giordano, Thomas J.
Labourier, Emmanuel
Molecular classification of thyroid lesions by combined testing for miRNA gene expression and somatic gene alterations
title Molecular classification of thyroid lesions by combined testing for miRNA gene expression and somatic gene alterations
title_full Molecular classification of thyroid lesions by combined testing for miRNA gene expression and somatic gene alterations
title_fullStr Molecular classification of thyroid lesions by combined testing for miRNA gene expression and somatic gene alterations
title_full_unstemmed Molecular classification of thyroid lesions by combined testing for miRNA gene expression and somatic gene alterations
title_short Molecular classification of thyroid lesions by combined testing for miRNA gene expression and somatic gene alterations
title_sort molecular classification of thyroid lesions by combined testing for mirna gene expression and somatic gene alterations
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4907059/
https://www.ncbi.nlm.nih.gov/pubmed/27499919
http://dx.doi.org/10.1002/cjp2.38
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