Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.
Department of Gynaecology and Obstetrics, Ningbo First Hospital, Ningbo, Zhejiang, China.
Front Immunol. 2023 Aug 18;14:1130738. doi: 10.3389/fimmu.2023.1130738. eCollection 2023.
Endometriosis is a worldwide gynacological diseases, affecting in 6-10% of women of reproductive age. The aim of this study was to investigate the gene network and potential signatures of immune infiltration in endometriosis.
The expression profiles of GSE51981, GSE6364, and GSE7305 were obtained from the Gene Expression Omnibus (GEO) database. Core modules and central genes related to immune characteristics were identified using a weighted gene coexpression network analysis. Bioinformatics analysis was performed to identify central genes in immune infiltration. Protein-protein interaction (PPI) network was used to identify the hub genes. We then constructed subtypes of endometriosis samples and calculated their correlation with hub genes. qRTPCR and Western blotting were used to verify our findings.
We identified 10 candidate hub genes (GZMB, PRF1, KIR2DL1, KIR2DL3, KIR3DL1, KIR2DL4, FGB, IGFBP1, RBP4, and PROK1) that were significantly correlated with immune infiltration. Our study established a detailed immune network and systematically elucidated the molecular mechanism underlying endometriosis from the aspect of immune infiltration.
Our study provides comprehensive insights into the immunology involved in endometriosis and might contribute to the development of immunotherapy for endometriosis. Furthermore, our study sheds light on the underlying molecular mechanism of endometriosis and might help improve the diagnosis and treatment of this condition.
子宫内膜异位症是一种全球性的妇科疾病,影响着 6-10%的育龄妇女。本研究旨在探讨子宫内膜异位症中的基因网络和潜在的免疫浸润特征。
从基因表达综合数据库(GEO)中获取 GSE51981、GSE6364 和 GSE7305 的表达谱。使用加权基因共表达网络分析(WGCNA)识别与免疫特征相关的核心模块和中心基因。进行生物信息学分析以识别免疫浸润中的核心基因。使用蛋白质-蛋白质相互作用(PPI)网络识别枢纽基因。然后构建子宫内膜异位症样本的亚型,并计算它们与枢纽基因的相关性。采用 qRTPCR 和 Western blot 验证我们的发现。
我们确定了 10 个候选的枢纽基因(GZMB、PRF1、KIR2DL1、KIR2DL3、KIR3DL1、KIR2DL4、FGB、IGFBP1、RBP4 和 PROK1),它们与免疫浸润显著相关。我们的研究从免疫浸润的角度建立了一个详细的免疫网络,并系统地阐明了子宫内膜异位症的分子机制。
我们的研究提供了对子宫内膜异位症中免疫相关的全面见解,可能有助于子宫内膜异位症的免疫治疗的发展。此外,我们的研究揭示了子宫内膜异位症的潜在分子机制,可能有助于改善该疾病的诊断和治疗。