应用生物信息学分析正常女性不同乳腺密度差异表达基因
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南京医科大学第一附属医院

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[基金项目] 国家重点研发计划(No. 2016YFC0905900);国家自然科学基金(No. 81872365);江苏省社会发展“临床前沿技术”重点项目(No. BE2019731)


Exploring the differentially expressed genes in Healthy Women with Different Mammographic Density Using Bioinformatics Analysis
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the First Affiliated Hospital of Nanjing Medical University

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This research was supported by the National Key Research and Development Program of China (No. 2016YFC0905900), National Natural Science Foundation of China (No. 81872365) and Jiangsu Provincial Key Research Development Program (No. BE2019731).

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    摘要:

    目的:应用生物信息学技术筛选高乳腺密度和低乳腺密度的正常女性的差异基因并分析其富集通路,为致密型乳腺女性乳腺癌早期诊断,靶向治疗和预后评估提供理论依据。方法:从GEO数据库获取GSE38506数据集,使用GEO2R筛选差异表达基因。使用DAVID数据库进行GO、KEGG富集分析,并应用STRING及Cytoscape软件的 CytoHubba插件进行蛋白互作网络分析和筛选出hub基因。最后使用bcGenExMiner在线工具对这5个hub基因进行预后分析。结果:从GSE38506基因芯片共筛选出830个显著差异表达基因,其中上调基因442个,下调基因388个。富集分析显示差异表达基因主要涉及信号转导、GTP酶活性的正调控、固有免疫反应、细胞黏附、细胞质膜、细胞表面、细胞连接、ATP结合、肌动蛋白结合、转录因子结合等。共筛选出2个核心模块和5个hub基因,包括EGFR(epidermal growth factor receptor),JUN(Jun proto-oncogene),CDC42(cell division cycle 42),SRC(SRC proto-oncogene),RAC1(ras-related C3 botulinum toxin substrate 1),并且它们都与乳腺癌预后相关。结论:本研究通过生物信息学筛选出了正常女性乳腺密度相关的 5个核心基因,可能对乳腺癌的发生发展和预后存在一定影响,是潜在的致密型乳腺女性易患乳腺癌的分子学标志物和靶向治疗新位点。

    Abstract:

    Objective: Bioinformatics analysis was applied to explore the differentially expressed genes (DEGs) in normal women with high breast density and low breast density and analyze their enrichment pathways, so as to provide theoretical basis for early diagnosis, targeted therapy and prognosis assessment of breast cancer patients with dense breast. Methods: GSE38506 data set was obtained from the GEO database and DEGs were screened using GEO2R. Enrichment analysis of GO and KEGG was performed using DAVID database. CytoHubba plug-in of STRING and Cytoscape software was used for protein interaction network analysis and hub gene screening. Finally, the online tool bcGenExMiner was used to analyze the prognosis of these 5 hub genes. Results: A total of 830 significantly DEGs were screened from GSE38506 gene chip, among which 442 genes were up-regulated and 388 genes were down-regulated. Enrichment analysis showed that DEGs were mainly involved in signal transduction, positive regulation of GTPase activity, innate immune response, cell adhesion, cytoplasmic membrane, cell surface, cell connection, ATP binding, actin binding, transcription factor binding, et al. A total of 2 core modules and 5 hub genes were screened, including EGFR (epidermal growth factor receptor), JUN proto-Oncogene, CDC42 (cell division cycle 42), SRC proto-oncogene, RAC1 (RAS-related C3 botulinum toxin substrate 1), and they are all associated with breast cancer prognosis. Conclusion: In this study, 5 hub genes related to mammographic density in healthy women were screened through bioinformatics, which may have certain influence on the occurrence, development and prognosis of breast cancer, and are potential molecular markers and new targeted therapy sites for breast cancer patients with dense breast.

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  • 收稿日期:2020-07-15
  • 最后修改日期:2020-11-07
  • 录用日期:2021-12-23
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