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魏娜, 王丹, 何浪. 整合组学数据分析乳腺癌细胞与外周免疫系统的交互作用[J]. 肿瘤防治研究, 2017, 44(4): 243-247. DOI: 10.3971/j.issn.1000-8578.2017.04.001
引用本文: 魏娜, 王丹, 何浪. 整合组学数据分析乳腺癌细胞与外周免疫系统的交互作用[J]. 肿瘤防治研究, 2017, 44(4): 243-247. DOI: 10.3971/j.issn.1000-8578.2017.04.001
WEI Na, WANG Dan, HE Lang. Potential Molecular Crosstalk Between Breast Cancer Cells and Peripheral Immune System Based on Integrative Omics Strategy[J]. Cancer Research on Prevention and Treatment, 2017, 44(4): 243-247. DOI: 10.3971/j.issn.1000-8578.2017.04.001
Citation: WEI Na, WANG Dan, HE Lang. Potential Molecular Crosstalk Between Breast Cancer Cells and Peripheral Immune System Based on Integrative Omics Strategy[J]. Cancer Research on Prevention and Treatment, 2017, 44(4): 243-247. DOI: 10.3971/j.issn.1000-8578.2017.04.001

整合组学数据分析乳腺癌细胞与外周免疫系统的交互作用

Potential Molecular Crosstalk Between Breast Cancer Cells and Peripheral Immune System Based on Integrative Omics Strategy

  • 摘要:
    目的 探讨乳腺癌上皮细胞与外周血之间的交互作用。
    方法 从GEO数据库中获取乳腺癌上皮细胞及外周血单个核细胞(PBMCs)表达谱。GEO2R在线分析工具筛选差异表达基因,利用UniProt和STRING数据库对差异表达基因蛋白产物进行亚细胞定位,筛选乳腺癌细胞分泌蛋白及与其相互作用的PBMCs膜蛋白。Cytoscape软件构建互作网络。使用DAVID在线工具基因功能注释和KEGG通路富集方法对互作分子进行分析。
    结果 共筛选到101对相互作用分子,基因功能主要涉及细胞黏附、细胞迁移、白细胞激活、免疫反应等生物学过程,参与的信号通路主要有细胞外基质—受体相互作用,细胞因子—细胞因子受体相互作用,趋化因子信号通路等。其中FN1、ITGBI、FLT1、COMP、CXCL12为关键蛋白。
    结论 利用生物信息学方法,整合组学数据,能够有效获取信息,为乳腺癌的治疗及预后监测的研究开辟新思路。

     

    Abstract:
    Objective To investigate the molecular crosstalk between breast tumor tissues and peripheral blood mononuclear cells (PBMCs).
    Methods Two publicly available microarray datasets of breast tumor epithelium and PBMCs respectively were analyzed by bioinformatics approaches. Differentially expressed genes were identified by GEO2R online analysis tools. Then protein-protein interactions (PPIs), protein subcellular localization information from UniProt and STRING database were integrated to identify the genes that contribute to the dialogue. Function and pathways of that involved in the dialogue between the tumor cells and the peripheral circulation were annotated by the Database for Annotation, Visualization and Integrated Discovery (DAVID).
    Results A total of 101 interaction relationships were identified and visualized. Function and pathway analysis indicated that biology processes included cell adhesion, regulation of cell motion, leukocyte activation, and immune response. And the crossstalk molecules were enriched in ECM-receptor interaction, cytokine-cytokine receptor interaction, and chemokine signaling pathway. The genes such as FN1, ITGB1, FLT1, CXCR3, COPM, CXCL12 were the hub nodes of the crosstalk network and may play an important role in the response for tumor-derived chemoattractants.
    Conclusion Bioinformatic tools can extract the effective information through integrative analysis of multi-omics data. This study has the potential for development of new therapeutic and the prognosis monitoring strategies against breast cancer.

     

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