Li Qing, Li Yonghao, Sun Ximei, Zhang Xinlei, Zhang Mei
Department of General Surgery, The First Affiliated Hospital of Shandong First Medical University &Shandong Provincial Qianfoshan Hospital, No 16766 Jingshi Road, Jinan, Shandong, China.
Int J Endocrinol. 2022 Jul 16;2022:4995196. doi: 10.1155/2022/4995196. eCollection 2022.
Parathyroid tumors are common endocrine neoplasias associated with primary hyperparathyroidism. Although numerous studies have studied the subject, the predictive value of gene biomarkers nevertheless remains low.
In this study, we performed genomic analysis of abnormal DNA methylation in parathyroid tumors. After data preprocessing, differentially methylated genes were extracted from patients with parathyroid tumors by using -tests.
After refinement of the basic differential methylation, 28241 unique CpGs (634 genes) were identified to be methylated. The methylated genes were primarily involved in 7 GO terms, and the top 3 terms were associated with cyst morphogenesis, ion transport, and GTPase signal. Following pathway enrichment analyses, a total of 10 significant pathways were enriched; notably, the top 3 pathways were cholinergic synapses, glutamatergic synapses, and oxytocin signaling pathways. Based on PPIN and ego-net analysis, 67 ego genes were found which could completely separate the diseased group from the normal group. The 10 most prominent genes included POLA1, FAM155 B, AMMECR1, THOC2, CCND1, CLDN11, IDS, TST, RBPJ, and GNA11. SVM analysis confirmed that this grouping approach was precise.
This research provides useful data to further explore novel genes and pathways as therapeutic targets for parathyroid tumors.
甲状旁腺肿瘤是与原发性甲状旁腺功能亢进相关的常见内分泌肿瘤。尽管众多研究已对该主题进行了探讨，但基因生物标志物的预测价值仍然较低。
在本研究中，我们对甲状旁腺肿瘤中异常的DNA甲基化进行了基因组分析。经过数据预处理后，通过t检验从甲状旁腺肿瘤患者中提取差异甲基化基因。
在对基本差异甲基化进行优化后，共鉴定出28241个独特的甲基化CpG（634个基因）。甲基化基因主要涉及7个基因本体（GO）术语，其中前3个术语与囊肿形态发生、离子转运和GTPase信号相关。经过通路富集分析，共富集到10条显著通路；值得注意的是，前3条通路为胆碱能突触、谷氨酸能突触和催产素信号通路。基于蛋白质-蛋白质相互作用网络（PPIN）和自我网络分析，发现67个自我基因能够将患病组与正常组完全区分开。最突出的10个基因包括POLA1、FAM155B、AMMECR1、THOC2、CCND1、CLDN11、IDS、TST、RBPJ和GNA11。支持向量机（SVM）分析证实这种分组方法是精确的。
本研究提供了有用的数据，以进一步探索新的基因和通路作为甲状旁腺肿瘤的治疗靶点。
