甲状旁腺功能亢进是第三常见的内分泌疾病。甲状旁腺腺瘤(PA)约占原发性甲状旁腺功能亢进病例的85%,但是分子机制还不完全清楚。在这里,我们的目的是研究散发性PA的遗传和转录组特征。
对41例PA患者进行全外显子组测序(WES)和转录组测序(RNA-seq),对5例正常甲状旁腺组织进行RNA-seq测序。鉴定了基因突变和表征的表达变化。为了阐明PA的分子机制,进行RNA-seq数据的无监督一致聚类。分析这些患者的测序数据与临床病理特征之间的相关性。
先前报道的PA驱动基因突变,如MEN1(9/41),mTOR(4/41),ZFX(3/41),CASR(3/41),EZH2(2/41)和FAT1(2/41),在我们的队列中也被发现。此外,EZH1的体细胞突变,在PA中没有报道,在4个样本中发现。RNA-seq显示,与正常样品相比,PA样品中84个基因的表达水平上调,646个基因的表达水平下调。RNA-seq数据的无监督聚类分析将这些患者分为10个与一组潜在致病基因的突变或异常表达相关的亚组。
MEN1,EZH2,CASR,EZH1,ZFX,显示PA中mTOR和FAT1突变。根据RNA-seq数据聚类分析,细胞周期蛋白D1,β-连环蛋白,VDR,CASR和GCM2可能是导致PA基因表达谱的重要因素。
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.
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.
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.
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.