Abstract:
Gynecological diseases are triggered by aberrant molecular pathways that alter gene expression, hormonal balance, and cellular signaling pathways, which may lead to long-term physiological consequences. This study was able to identify highly preserved modules and key hub genes that are mainly associated with gynecological diseases, represented by endometriosis (EM), ovarian cancer (OC), cervical cancer (CC), and endometrial cancer (EC), through the weighted gene co-expression network analysis (WGCNA) of microarray datasets sourced from the Gene Expression Omnibus (GEO) database. Five highly preserved modules were observed across the EM (GSE51981), OC (GSE63885), CC (GSE63514), and EC (GSE17025) datasets. The functional annotation and pathway enrichment analysis revealed that the highly preserved modules were heavily involved in several inflammatory pathways that are associated with transcription dysregulation, such as NF-kB signaling, JAK-STAT signaling, MAPK-ERK signaling, and mTOR signaling pathways. Furthermore, the results also include pathways that are relevant in gynecological disease prognosis through viral infections. Mutations in the ESR1 gene that encodes for ERα, which were shown to also affect signaling pathways involved in inflammation, further indicate its importance in gynecological disease prognosis. Potential drugs were screened through the Drug Repurposing Encyclopedia (DRE) based on the up-and downregulated hub genes, wherein a bacterial ribosomal subunit inhibitor and a benzodiazepine receptor agonist were the top candidates. Other drug candidates include a dihydrofolate reductase inhibitor, glucocorticoid receptor agonists, cholinergic receptor agonists, selective serotonin reuptake inhibitors, sterol demethylase inhibitors, a bacterial antifolate, and serotonin receptor antagonist drugs which have known anti-inflammatory effects, demonstrating that the gene network highlights specific inflammatory pathways as a therapeutic avenue in designing drug candidates for gynecological diseases.
摘要:
妇科疾病是由改变基因表达的异常分子途径引发的,荷尔蒙平衡,和细胞信号通路,这可能会导致长期的生理后果。这项研究能够鉴定出高度保存的模块和主要与妇科疾病相关的关键枢纽基因,以子宫内膜异位症(EM)为代表,卵巢癌(OC),宫颈癌(CC),子宫内膜癌(EC),通过来自基因表达综合(GEO)数据库的微阵列数据集的加权基因共表达网络分析(WGCNA)。在EM中观察到五个高度保存的模块(GSE51981),OC(GSE63885),CC(GSE63514),和EC(GSE17025)数据集。功能注释和途径富集分析显示,高度保存的模块严重参与了与转录失调相关的几种炎症途径。如NF-kB信号,JAK-STAT信号,MAPK-ERK信号,和mTOR信号通路。此外,结果还包括通过病毒感染与妇科疾病预后相关的途径。编码ERα的ESR1基因突变,它们也被证明会影响炎症中涉及的信号通路,进一步表明其在妇科疾病预后中的重要性。潜在的药物通过药物再利用百科全书(DRE)筛选基于上调和下调的hub基因,其中细菌核糖体亚基抑制剂和苯二氮卓受体激动剂是首选。其他候选药物包括二氢叶酸还原酶抑制剂,糖皮质激素受体激动剂,胆碱能受体激动剂,选择性5-羟色胺再摄取抑制剂,甾醇去甲基酶抑制剂,一种细菌抗叶酸剂,和已知具有抗炎作用的5-羟色胺受体拮抗剂药物,证明了基因网络突出了特定的炎症途径,作为设计妇科疾病候选药物的治疗途径。