Analysis of mutations in CDC27, CTBP2, HYDIN and KMT5A genes in carotid paragangliomas

Abstract

Carotid paragangliomas (CPGLs) are rare neuroendocrine tumors that arise from paraganglionic tissue of the carotid body localizing at the bifurcation of carotid artery. These tumors are slowly growing, but occasionally they become aggressive and metastatic. Surgical treatment remains high-risk and extremely challenging; radiation and chemotherapy are poorly effective. The study of molecular pathogenesis of CPGLs will allow developing novel therapeutic approaches and revealing biomarkers. Previously, we performed the exome sequencing of 52 CPGLs and estimated mutational load (ML). Paired histologically normal tissues or blood were unavailable, so potentially germline mutations were excluded from the analysis with strong filtering conditions using 1000 Genomes Project and ExAC databases. In this work, ten genes (ZNF717, CDC27, FRG2C, FAM104B, CTBP2, HLA-DRB1, HYDIN, KMT5A, MUC3A, and PRSS3) characterized by the highest level of mutational load were analyzed. Using several prediction algorithms (SIFT, PolyPhen-2, MutationTaster, and LRT), potentially pathogenic mutations were identified in four genes (CDC27, CTBP2, HYDIN, and KMT5A). Many of these mutations occurred in the majority of cases, and their mutation type was checked using exome sequencing data of blood prepared with the same exome enrichment kit that was used for preparation of exome libraries from CPGLs. The majority of the mutations were germline that can apparently be associated with annotation errors in 1000 Genomes Pro ject and ExAC. However, part of the mutations identified in CDC27, CTBP2, HYDIN, and KMT5A remain potentially pathogenic, and there is a large body of data on the involvement of these genes in the formation and progression of other tumors. This allows considering CDC27, CTBP2, HYDIN, and KMT5A genes as potentially associated with CPGL pathogenesis and requires taking them into account in further investigations. Thus, there is a necessity to improve the methods for identification of cancer-asso ciated genes as well as pathogenic mutations.