ArticleEuropean thyroid journal2016
How to Assess the Clinical Relevance of Novel RET Missense Variants in the Absence of Functional Studies?
Article in European thyroid journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Unexpected Pathogenic RET p.V804M Variant Leads to the Clinical Diagnosis and Management of Medullary Thyroid Carcinoma.The American journal of case reports · 2020Article
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5 authors.
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Abstract
INTRODUCTION AND
backgroundFamilial medullary thyroid cancer (FMTC) is caused by gain of function mutations in the proto-oncogene RET (rearranged during transfection). Missense mutations within exon 14 including p.Val804Met are known to cause FMTC and multiple endocrine neoplasia type 2a/b. The clinical significance of other novel missense variants within this hotspot region of exon 14 is not delineated. CASE DESCRIPTION: A three-generation pedigree of FMTC is presented with the co-occurrence of two missense variants within exon 14 of the RET gene, the known variant p.Val804Met and the novel variant p.Val826Met. The female index patient developed medullary thyroid cancer at the age of 42 years and was heterozygous for both missense variants. Her younger sister was also tested to be compound heterozygous for both mutations, and five further relatives were heterozygous for only one of both sequence variants. Prophylactic thyroidectomy was recommended for the two carriers of the RET mutation p.Val804Met, revealing a C-cell hyperplasia for one of them at the age of 19 years. Medical surveillance of 6 heterozygous carriers including repeated neck ultrasound examination as well as basal and calcium (pentagastrin)-stimulated calcitonin levels were recommended.
conclusionOur data emphasize the importance of an interdisciplinary approach to assess the functional and clinical significance of novel RET variants. In the absence of functional studies, the plausibility of the pathologic significance of a detected endocrine genetic variant can be estimated by in silico methods such as computational analysis of protein structure and biophysical differences or comparative database search for evolutionary conservation.
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