Reproductive Medicine Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Department of Gynecology and Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Am J Reprod Immunol. 2022 Oct;88(4):e13607. doi: 10.1111/aji.13607. Epub 2022 Aug 15.
Recurrent implantation failure (RIF) refers to a challenging topic in assisted reproductive technology (ART), the etiology of which may be attributed to impaired endometrial receptivity; however, the precise pathogenesis of RIF has not been thoroughly elucidated.
Four RIF microarray datasets were obtained from the Gene Expression Omnibus database and integrated by the "sva" R package. The differentially expressed genes (DEGs) were analyzed using the "limma" package and then GO, KEGG, GSEA, and GSVA were applied to perform functional and pathway enrichment analysis. The immune cell infiltration in the RIF process was evaluated by the CIBERSORT algorithm. Finally, the hub genes were identified through the CytoHubba and subsequently verified using two items of external endometrial data.
236 genes were differentially expressed in the endometrium of the RIF group. Functional enrichment analysis demonstrated that the biological functions of DEGs were mainly correlated to the immune-related pathways, including immune response, TNF signaling pathway, complement and coagulation cascades. Among the immune cells, γδ T cells decreased significantly in the endometrium of RIF patients. In addition, the key DEGs such as PTGS2, FGB, MUC1, SST, VCAM1, MMP7, ERBB4, FOLR1, and C3 were screened and identified as the hub genes involved in the pathogenesis of RIF.
Abnormal immune response regulation of endometrium contributes to the occurrence of RIF, and γδ T cells may be the pivotal immune cells causing RIF. At the same time, the novel hub genes identified will provide effective targets for the prediction and therapy of RIF.
反复着床失败（RIF）是辅助生殖技术（ART）中的一个难题，其病因可能与子宫内膜容受性受损有关，但 RIF 的具体发病机制尚未完全阐明。
从基因表达综合数据库中获取了 4 个 RIF 微阵列数据集，并通过“sva”R 包进行整合。使用“limma”包分析差异表达基因（DEGs），然后进行 GO、KEGG、GSEA 和 GSVA 分析，以进行功能和通路富集分析。通过 CIBERSORT 算法评估 RIF 过程中的免疫细胞浸润。最后，通过 CytoHubba 识别枢纽基因，并使用两项外部子宫内膜数据进行验证。
在 RIF 组的子宫内膜中，有 236 个基因差异表达。功能富集分析表明，DEGs 的生物学功能主要与免疫相关通路相关，包括免疫反应、TNF 信号通路、补体和凝血级联。在免疫细胞中，RIF 患者的子宫内膜中 γδ T 细胞显著减少。此外，筛选并鉴定了关键的 DEGs，如 PTGS2、FGB、MUC1、SST、VCAM1、MMP7、ERBB4、FOLR1 和 C3，作为参与 RIF 发病机制的枢纽基因。
子宫内膜异常免疫反应调节导致 RIF 的发生，γδ T 细胞可能是导致 RIF 的关键免疫细胞。同时，新鉴定的枢纽基因将为 RIF 的预测和治疗提供有效的靶点。
