Analysis of key candidate genes and pathways of endometriosis pathophysiology by a genomics-bioinformatics approach

Abstract

Endometriosis is a common disease in women, but the signaling pathways and driven genes involved remain unclear. This study integrated four datasets to elucidate potential key candidate genes and pathways in endometriosis. Four expression profile datasets including 29 endometriosis lesions and 37 normal tissues were integrated and analyzed. Differentially expressed genes (DEGs) were sorted, and the gene ontology, pathway enrichment, and protein–protein interaction network of candidate genes were then analyzed. A total of 94 shared DEGs were identified from the four datasets. The DEGs were clustered based on functions and signaling pathways through the analysis of significant enrichment. Among the DEG protein-protein interaction network complex, 87 nodes/DEGs were identified. Furthermore, 18 central node genes were identified, and most of the corresponding genes were involved in the angiotensin system, smooth muscle contraction, cell junction organization, and lipoxin pathways. Through integrated bioinformatic analysis, we identified candidate genes and pathways in endometriosis, which could improve our understanding of endometriosis.

摘要

子宫内膜异位症是一种常见的女性疾病, 但是其信号通路和致病基因尚不清楚。本研究整合了四个数据库来阐明子宫内膜异位症可能的主要候选基因和信号通路。四个表达谱数据库整合分析了29例子宫内膜异位症病变和37例正常组织。对差异表达基因（DEGs）进行排序, 分析候选基因的基因本体、通路多少和蛋白-蛋白相互作用。共从四个数据库中发现94个共享差异表达基因（DEGs）。通过显著性分析, 根据功能和信号通路对DEGs进行分类。在DEG蛋白-蛋白相互作用网络复合体中, 识别出87个节点/DEG。此外, 我们还发现了18个中央节点基因, 大部分相关基因参与了血管紧张素系统、平滑肌收缩、细胞连接组织和脂氧素通路。通过综合生物信息学分析, 我们发现了子宫内膜异位症的候选基因和信号通路, 这可以提高我们对子宫内膜异位症的认识。

The Chinese abstracts are translated by Prof. Dr. Xiangyan Ruan and her team: Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.

Keywords:

• Endometriosis
• bioinformatic analysis
• differentially expressed genes

Disclosure statement

There are no conflicts of interest to declare.