Frontiers in endocrinology · 2021
Integrated Whole-Exome and Transcriptome Sequencing of Sporadic Parathyroid Adenoma.
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Hu Ya, Zhang Xiang, Wang Ou, Cui Ming, Li Xiaobin, Wang Mengyi, Hua Surong, Liao Quan
Аннотация
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.
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.
Предметные рубрики MeSH
AdenomaAdultAgedCadherinsCluster AnalysisEnhancer of Zeste Homolog 2 ProteinExomeFemaleGene Expression RegulationGenomicsHumansHyperparathyroidismKruppel-Like Transcription FactorsMaleMiddle AgedMutationParathyroid NeoplasmsPolycomb Repressive Complex 2Proto-Oncogene ProteinsRNA-SeqReceptors, Calcium-SensingTOR Serine-Threonine KinasesTissue BanksTranscriptome