In Silico Analysis of RET Variants in Medullary Thyroid Cancer

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.