Genetic Analysis and Clinical Characteristics of Hereditary Pheochromocytoma and Paraganglioma Syndrome in Korean Population

韩国人群遗传性嗜铬细胞瘤和副神经节瘤综合征的遗传分析和临床特征

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Abstract

BACKGROUND: Pheochromocytoma and paragangliomas (PPGL) are hereditary in approximately 30% to 40% cases. With the advancement of genetic analysis techniques, including next-generation sequencing (NGS), there were attempts to classify PPGL into molecular clusters. With NGS being applied to clinical settings recently, we aimed to review the results of genetic analysis, including NGS, and investigate the association with clinical characteristics in Korean PPGL patients. METHODS: We reviewed the medical records of PPGL patients who visited Severance hospital from 2006 to 2019. We documented the clinical phenotype of those who underwent targeted NGS or had known germline mutations of related genes. RESULTS: Among 57 PPGL patients, we found 28 pathogenic germline mutations of susceptibility genes. Before the targeted NGS was implemented, only obvious syndromic feature lead to the Sanger sequencing for the specific genes. Therefore, for the exact prevalence, only patients after the year 2017, when targeted NGS was added, were included (n=43). The positive germline mutations were found in 14 patients; thus, the incidence rate is 32.6%. Patients with germline mutations had a higher likelihood of family history. There were significant differences in the type of PPGLs, percentage of family history, metastasis rate, presence of other tumors, and biochemical profile among three molecular clusters: pseudohypoxic tricarboxylic acid cycle-related, pseudohypoxic von Hippel-Lindau (VHL)/endothelial PAS domain-containing protein 1-related, and kinase-signaling group. Germline mutations were identified in seven PPGL-related genes (SDHB, RET, VHL, NF1, MAX, SDHA, and SDHD). CONCLUSION: We report the expected prevalence of germline mutations in Korean PPGL patients. NGS is a useful and accessible tool for genetic analysis in patients with PPGLs, and further research on molecular classification is needed for precise management.

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