Information de reference pour ce titreAccession Number: | 00006372-201504000-00017.
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Author: | Heineman, Thomas E. 1; Joshi, Rohan MD 2; Cohen, Marc A. MD 2; Kuhel, William I. MD 2; Kutler, David I. MD 2
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Institution: | (1)Weill Cornell Medical College, New York, New York, USA (2)Department of Otolaryngology-Head and Neck Surgery, Weill Cornell Medical College/New York Presbyterian, New York, New York, USA
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Title: | |
Source: | Otolaryngology - Head & Neck Surgery. 152(4):650-654, April 2015.
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Abstract: | Objective: The American Thyroid Association (ATA) medullary thyroid cancer (MTC) guidelines group RET variants, in the setting of familial medullary thyroid cancer and multiple endocrine neoplasia type 2, into 4 classes of severity based on epidemiological data. The aim of this study was to determine if genotype correlates with phenotype in RET missense mutations.
Study Design: In silico mutational tolerance prediction.
Setting: Academic research hospital.
Subjects and Methods: We analyzed all RET variants currently listed in the ATA guidelines for the management of MTC using 2 computer-based (in silico) mutation tolerance prediction approaches: PolyPhen-2 HumVar and PolyPhen-2 HumDiv. Our analysis also included 27 different RET single-nucleotide polymorphisms resulting in missense variants.
Results: There was a statistically significant difference in the overall HumDiv score between ATA groups A and B (P = .025) and a statistically significant different HumVar score between benign polymorphisms and ATA group A (P = .023). Overall, RET variants associated with a less aggressive clinical phenotype generally had a lower Hum Div/Var score.
Conclusions: Polyphen-2 Hum Div/Var may provide additional clinical data to help distinguish benign from MEN2/familial medullary thyroid carcinoma-causing RET variants as well as less aggressive phenotypes (ATA A) from more aggressive ones (ATA B-C). In silico genetic analyses, with proper validation, may predict the phenotypic severity of RET variants, providing clinicians with a tool to aid clinical decision making in cases in which the RET variant is currently unknown or little epidemiological data are available.
(C)2015Sage Publications
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Author Keywords: | medullary thyroid cancer; multiple endocrine neoplasia; thyroidectomy; in silico analysis; RET gene.
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Language: | English.
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Document Type: | Endocrine Surgery.
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Journal Subset: | Clinical Medicine.
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ISSN: | 0194-5998
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NLM Journal Code: | 7909794, 8508176, on7, on8
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DOI Number: | https://dx.doi.org/10.1177/01945...- ouverture dans une nouvelle fenêtre
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