摘要
目的卵巢癌是妇产科恶性肿瘤死亡的主要原因之一,但其致病分子机制还未被清晰阐明。该研究通过整合生物信息学方法,旨在挖掘其潜在的关键基因分子及生物学功能,以便更全面地揭示其发病机制。方法从GEO(Gene Expression Omnibus)数据库下载miRNA和mRNA表达谱芯片集。通过R语言“limma”包筛选差异表达的miRNA和mRNA。通过FunRich软件对筛选的差异miRNA进行靶标预测,并与筛选的差异mRNA取交集得到共有差异基因。通过R语言“clusterProfiler”包对共有差异基因进行富集分析和通路注释以挖掘其生物学功能。运用string数据库和cytoscape软件进一步构建miRNA-靶基因调控网络,并鉴定分子网络中的关键基因分子。结果共筛选鉴定出167个共有差异基因。富集分析表明共有差异基因主要涉及细胞外组织、胚胎器官发育、突触后特化、胶原三聚体和DNA结合转录激活等生物过程;通路注释表明共有差异基因主要参与蛋白质的消化吸收和松弛素信号通路行为。分子网络分析筛选鉴定了10个候选关键基因,并发现miR-29c-3p,miR-1271-5p和miR-133b抑癌分子与共有差异基因存在最广泛的靶向关系,处于调控中枢核心地位。上述关键基因分子在卵巢癌发生发展中扮演了重要角色。结论该研究采用的系统整合方法学和鉴定的关键基因分子有助于揭示卵巢癌的潜在致病机制,也为卵巢癌的早期筛查提供新的候选标志物。
Objective Ovarian cancer is one of the leading causes of death in gynecological malignancies, of which molecular mechanism hasn’t been elucidated clearly yet. The research aims to reveal the potential key molecular and biological processes of ovarian cancer by means of integrated bioinformatics, in order to more fully clarify its pathogenesis. Methods The microarray sets of miRNA and mRNA expression profiles were downloaded from the GEO(Gene Expression Omnibus) database. The differentially expressed miRNAs and mRNAs were screened by the "limma" package of R language. The target prediction was performed on the differentially expressed miRNAs identified by the FunRich program and overlapped differentially expressed genes(DEGs) were obtained combined with miRNA and mRNA datasets. The overlapped DEGs in the network were analyzed to explore the biological processes involved by enrichment and pathway analysis by the "cluster Profiler" package of the R language. The regulatory network of miRNA-gene was further constructed by string database and cytoscape software, and the key molecular were identified in the molecular protein-protein interaction(PPI) network among DEGs. Results A total of 167 overlapped DEGs were identified. The enrichment showed that the overlapped DEGs were mainly involved in process named extracellular related organization, embryonic organ development, postsynaptic specialization, collagen trimer and DNA-binding transcription activator. The pathway analysis showed that these DEGs were involved in protein digestion and absorption and relaxin signaling pathway. The PPI molecular network identified 10 key genes, and found that miR-29 c-3 p, miR-1271-5 p and miR-133 b, existed the most extensive targeting relationship with overlapped DEGs, being three key miRNAs of the regulatory network, which played the role of tumor suppressor. These key molecules may play an important role in the occurrence and development of ovarian cancer. Conclusion The methodology used and identification of key molecules in this study contributed to understanding the pathogenesis of ovarian cancer and providing new candidate biomarkers for early screening of ovarian cancer.
作者
李超
朱晓丹
张玲华
杨兴坤
LI Chao;ZHU Xiao-dan;ZHANG Ling-hua;YANG Xing-kun(Foshan Women and Children Hospital,Guangdong Foshan 528000,China)
出处
《现代检验医学杂志》
CAS
2021年第5期38-42,共5页
Journal of Modern Laboratory Medicine
基金
佛山市遗传病精准诊断工程技术研究中心项目(NO.2020001003953),佛山市科学技术局审批。
