Identification of predisposing genes to development of Familial Non-Medullary Thryoid Cancer using whole exoma sequencing

Abstract

Familial thyroid cancer can originate from parafollicular cells and called medullary thyroid carcinoma (MTC) or from follicular cells and called familial non-medullary thyroid carcinoma (FNMTC). Hereditary MTC occurs associated with other endocrine neoplasms in Multiple Endocrine Neoplasm Type 2 (MEN 2) syndrome. FNMTC can occur in a syndromic or non-syndromic form. The syndromic form occurs in 5% of cases, the prevalence of thyroid carcinoma is variable, it occurs as a component of one of the familial cancer syndromes, and susceptibility genes have been identified. The non-syndromic form occurs in 95% of cases and thyroid cancer occurs as the only type of differentiated thyroid cancer and is the object of this study. According to the new World Health Organization (WHO) classification, the essential criteria for classification of non-syndromic FNMTC include: (1) presence of follicular cell-derived carcinomas in at least 3 first-degree relatives or (2) presence of PTC in at least 2 first-degree relatives and always, in both cases, absence of a history of radiation exposure and of cases of syndromic FNMTC. More than a hundred candidate genes and a few gene loci have been identified, but most of the genetic variants identified so far confer small increments in risk and explain only a small proportion of family clustering. Thus, genetic tests are not indicated for the non-syndromic FNMTC form. It is hoped that the clinical criteria established by the WHO will facilitate the investigation of the genetic basis of FNMTC. The present project aims to identify genetic variants of susceptibility to FNMTC. Ten families with at least 3 first-degree relatives with PTC were selected. The identification of candidate genes will be performed by Whole Exome Sequencing (WES) using the NextSeq2000 Sequencing Systems platform, Illlumina. Initially, the data will be evaluated for the presence of variants in 101 genes previously associated with FNMTC. In the absence of variants in these predisposition genes, the VCF files will be analyzed using the PhenoDB tool (phenodb.org). Variants will be annotated by ANNOVAR and filtered according to number of reads, quality, and frequency (<1%) in gnomAD (Genome Aggregation Database) and ABraOM (Online Archive of Brazilian Mutations). The prevalence of identified variants associated with FNMTC will be evaluated in approximately 500 sporadic PTC cases from The Cancer Genome Atlas (TCGA), the Cancer Somatic Mutations Catalog (COSMIC v92) and Integrative OncoGenomics (intOGen) database. The effect of amino acid substitution on the structure and function of the identified proteins will be analyzed using various plug-ins available through the Ensembl Variant Effect Predictor interface (ensembl.org/info/docs/tools/vep). We believe that this study will enable the identification of genes associated with non-syndromic FNMTC and the integration of these data with those reported in the literature will allow the development of a test aimed at early detection and individualized therapy of the disease in the Brazilian population, optimizing patient management. (AU)