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Integrated Whole-Exome and Transcriptome Sequencing of Sporadic Parathyroid Adenoma

PURPOSE: Hyperparathyroidism is the third most common endocrine disease. Parathyroid adenoma (PA) accounts for approximately 85% of cases of primary hyperparathyroidism, but the molecular mechanism is not fully understood. Herein, we aimed to investigate the genetic and transcriptomic profiles of sp...

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Detalles Bibliográficos
Autores principales: Hu, Ya, Zhang, Xiang, Wang, Ou, Cui, Ming, Li, Xiaobin, Wang, Mengyi, Hua, Surong, Liao, Quan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163014/
https://www.ncbi.nlm.nih.gov/pubmed/34054720
http://dx.doi.org/10.3389/fendo.2021.631680
Descripción
Sumario:PURPOSE: Hyperparathyroidism is the third most common endocrine disease. Parathyroid adenoma (PA) accounts for approximately 85% of cases of primary hyperparathyroidism, but the molecular mechanism is not fully understood. Herein, we aimed to investigate the genetic and transcriptomic profiles of sporadic PA. METHODS: Whole-exome sequencing (WES) and transcriptome sequencing (RNA-seq) of 41 patients with PA and RNA-seq of 5 normal parathyroid tissues were performed. Gene mutations and characterized expression changes were identified. To elucidate the molecular mechanism underlying PA, unsupervised consensus clustering of RNA-seq data was performed. The correlations between the sequencing data and clinicopathological features of these patients were analyzed. RESULTS: Previously reported PA driver gene mutations, such as MEN1 (9/41), mTOR (4/41), ZFX (3/41), CASR (3/41), EZH2 (2/41) and FAT1 (2/41), were also identified in our cohort. Furthermore, somatic mutation of EZH1, which had not been reported in PA, was found in 4 samples. RNA-seq showed that the expression levels of 84 genes were upregulated and 646 were downregulated in PA samples compared with normal samples. Unsupervised clustering analysis of RNA-seq data clustered these patients into 10 subgroups related to mutation or abnormal expression of a group of potential pathogenic genes. CONCLUSION: MEN1, EZH2, CASR, EZH1, ZFX, mTOR and FAT1 mutations in PA were revealed. According to the RNA-seq data clustering analysis, cyclin D1, β-catenin, VDR, CASR and GCM2 may be important factors contributing to the PA gene expression profile.