Zhang Ming, Gao Chang E, Li Wen Hui, Yang Yi, Chang Li, Dong Jian, Ren Yan Xin, Chen De Dian
Department of Radiation Oncology, The Third Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650118, P.R. China.
Department of Medical Oncology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650032, P.R. China.
Oncol Lett. 2017 Apr;13(4):2770-2776. doi: 10.3892/ol.2017.5776. Epub 2017 Feb 24.
Breast cancer is one of the most common malignant tumors with a high case-fatality rate among women. The present study aimed to investigate the effects of mesenchymal stem cells (MSCs) on breast cancer by exploring the potential underlying molecular mechanisms. The expression profile of GSE43306, which refers to MDA-MB-231 cells with or without a 1:1 ratio of MSCs, was downloaded from Gene Expression Omnibus database for differentially expressed gene (DEG) screening. The Database for Annotation, Visualization and Integrated Discovery was used for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs. The protein-protein interactional (PPI) network of DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins. The data was subsequently analyzed using molecular complex detection for sub-network mining of modules. Finally, DEGs in modules were analyzed using GO and KEGG pathway enrichment analyses. A total of 291 DEGs including 193 upregulated and 98 downregulated DEGs were obtained. Upregulated DEGs were primarily enriched in pathways including response to wounding (P=5.92×10), inflammatory response (P=5.92×10) and defense response (P=1.20×10), whereas downregulated DEGs were enriched in pathways including the cell cycle (P=7.13×10), mitotic cell cycle (P=6.81×10) and M phase (P=1.72 ×10). The PPI network, which contained 156 nodes and 289 edges, was constructed, and Fos was the hub node with the degree of 29. A total of 3 modules were mined from the PPI network. In total, 14 DEGs in module A were primarily enriched in GO terms, including response to wounding (P=4.77×10), wounding healing (P=6.25×10) and coagulation (P=1.13 ×10), and these DEGs were also enriched in 1 KEGG pathway (complement and coagulation cascades; P=0.0036). Therefore, MSCs were demonstrated to exhibit potentially beneficial effects for breast cancer therapy. In addition, the screened DEGs, particularly in PPI network modules, including FN1, CD44, NGF, SERPINE1 and CCNA2, may be the potential target genes of MSC therapy for breast cancer.
乳腺癌是女性中最常见且病死率较高的恶性肿瘤之一。本研究旨在通过探索潜在的分子机制来研究间充质干细胞(MSCs)对乳腺癌的影响。从基因表达综合数据库下载了GSE43306的表达谱,该表达谱涉及有或无1:1比例MSCs的MDA-MB-231细胞,用于差异表达基因(DEG)筛选。利用注释、可视化与整合发现数据库对DEGs进行基因本体(GO)和京都基因与基因组百科全书(KEGG)通路富集分析。使用检索相互作用基因/蛋白质的搜索工具构建DEGs的蛋白质-蛋白质相互作用(PPI)网络。随后使用分子复合物检测对数据进行分析,以挖掘模块的子网。最后,使用GO和KEGG通路富集分析对模块中的DEGs进行分析。共获得291个DEGs,其中193个上调,98个下调。上调的DEGs主要富集在包括伤口反应(P=5.92×10)、炎症反应(P=5.92×10)和防御反应(P=1.20×10)的通路中,而下调的DEGs则富集在包括细胞周期(P=7.13×10)、有丝分裂细胞周期(P=6.81×10)和M期(P=1.72×10)的通路中。构建了包含156个节点和289条边的PPI网络,Fos是度为29的枢纽节点。从PPI网络中挖掘出总共3个模块。模块A中共有14个DEGs主要富集在GO术语中,包括伤口反应(P=4.77×10)、伤口愈合(P=6.25×10)和凝血(P=1.13×10),并且这些DEGs也富集在1条KEGG通路(补体和凝血级联反应;P=0.0036)中。因此,证明MSCs对乳腺癌治疗可能具有有益作用。此外,筛选出的DEGs,特别是在PPI网络模块中的,包括FN1、CD44、NGF、SERPINE1和CCNA2,可能是MSCs治疗乳腺癌的潜在靶基因。