Разработка таргетной панели для молекулярно-генетической диагностики рака щитовидной железы

Thyroid cancer is the most common endocrine malignancy. The key approach for thyroid cancer diagnosis is cytology of fine needle aspiration biopsy (FNA) samples. FNA specimens have indeterminate cytology in 20-30%. This results in wrong clinical diagnosis and impropriate treatment strategy. Currently known mutations describe vast majority of thyroid cancer cases. Detection of the driver mutations is supposed to improve diagnostic accuracy. The aim of the work is to develop next-generation sequencing based diagnostic panel for thyroid cancer. The analysis of the English-language literature, COSMIC database (DB), as well as results of the research project the Cancer Genome Atlas was performed. In total, 456 point somatic mutations in 25 genes, 23 genetic translocations, and 3 copy number variations (CNV) mutations were identified. Using AmpliSeq Designer, 2 Custom Panels were created - for the detection of point mutations, small indels and CNV (1) and for the detection of translocations (2). The custom Panel for the detection of point mutations, small indels and CNV contains 221 primer pairs in 2 pools, covering 99.59% selected targeted regions. The design also incorporated the regions of the RET gene for detection of germline mutations associated with hereditary medullary thyroid cancer. RNA Gene Fusion designs tool in AmpliSeq Designer was used to design the Panel for the detection of 23 translocations.