Department of Obstetrics and Gynaecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623, China.
Curr Med Chem. 2024;31(41):6871-6888. doi: 10.2174/0109298673283426231220100011.
To explore the diagnostic biomarkers for diagnosing endometriosis.
Endometriosis is a benign, progressive, estrogen-dependent gynecological disorder that has highly variant prevalence. Therefore, it is essential to develop reliable diagnostic biomarkers for endometriosis diagnosis.
To explore the diagnostic biomarkers for endometriosis diagnosis.
Based on transcriptome data from GSE145701, we identified potential therapeutic targets through the intersection of endometriosis-related genes from weighted gene correlation network analysis (WGCNA) and differential expression analysis. Aprotein-protein interaction (PPI) was constructed. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were employed for functional enrichment analysis. The intersection of hub genes from topological analysis and module genes from module-based network analysis were selected as core targets, which were used for diagnostic model construction. Its robustness was validated using GSE7305 and GSE134056. Associations of core targets with immune characteristics and pathways were further evaluated. Molecular docking was employed to evaluate the docking affinity between core targets and drugs. Additionally, western blot and quantitative real-time polymerase chain reaction were also carried out to validate molecular docking results.
A diagnostic model was constructed using 7 core targets, which had a high diagnostic ability for endometriosis. CTSK was positively correlated with immune scores, while CDH2 was negatively correlated with immune scores. CTSK, HGF, and EPCAM were positively correlated with energy metabolism and inflammation-related pathways, while RUNX2, FN1, NCAM1, and CDH2 were positively correlated with epithelial-to-mesenchymal transition (EMT) and unfolded protein response (UPR). Moreover, FN1 had good docking affinity with Elagolix, Esmya, and Proellex. NCAM1 might be a promising target modulated by Elagolix. In vitro experiment revealed that the expression of FN1 in human normal endometrial cell lines (hEEC) gradually decreased with the increase of Esmya concentration, indicating that FN1 was a target for Esmya.
These results may facilitate the in-depth understanding of the development of endometriosis, and guide early diagnostic as well as clinical treatments for patients with endometriosis.
探索用于诊断子宫内膜异位症的诊断生物标志物。
子宫内膜异位症是一种良性、进行性、雌激素依赖性妇科疾病，其发病率差异很大。因此，开发用于子宫内膜异位症诊断的可靠诊断生物标志物至关重要。
探索用于子宫内膜异位症诊断的诊断生物标志物。
基于 GSE145701 的转录组数据，我们通过加权基因相关网络分析 (WGCNA) 中与子宫内膜异位症相关基因的交集和差异表达分析，确定了潜在的治疗靶点。构建了蛋白质-蛋白质相互作用 (PPI)。采用基因本体论 (GO) 和京都基因与基因组百科全书 (KEGG) 进行功能富集分析。选择拓扑分析中的枢纽基因和基于模块的网络分析中的模块基因的交集作为核心靶点，用于构建诊断模型。使用 GSE7305 和 GSE134056 验证其稳健性。进一步评估核心靶点与免疫特征和途径的相关性。采用分子对接评估核心靶点与药物的对接亲和力。此外，还进行了 Western blot 和实时定量聚合酶链反应以验证分子对接结果。
使用 7 个核心靶标构建了诊断模型，该模型对子宫内膜异位症具有较高的诊断能力。CTSK 与免疫评分呈正相关，而 CDH2 与免疫评分呈负相关。CTSK、HGF 和 EPCAM 与能量代谢和炎症相关途径呈正相关，而 RUNX2、FN1、NCAM1 和 CDH2 与上皮-间充质转化 (EMT) 和未折叠蛋白反应 (UPR) 呈正相关。此外，FN1 与 Elagolix、Esmya 和 Proellex 具有良好的对接亲和力。NCAM1 可能是 Elagolix 调节的有前途的靶点。体外实验表明，FN1 在人正常子宫内膜细胞系 (hEEC) 中的表达随着 Esmya 浓度的增加而逐渐降低，表明 FN1 是 Esmya 的靶点。
这些结果可能有助于深入了解子宫内膜异位症的发生发展，并指导子宫内膜异位症患者的早期诊断和临床治疗。
