Identification of adriamycin resistance genes in breast cancer based on microarray data analysis.
Identification of adriamycin resistance genes in breast cancer based on microarray data analysis.
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基于微阵列数据分析的乳腺癌阿霉素耐药基因鉴定
DOI：
10.21037/tcr-19-2145
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发表时间：
2020-12
影响因子：
0.9
通讯作者：
Cui Z
中科院分区：
文献类型：
--
作者：
Chen Y;Lin Y;Cui Z
研究背景乳腺癌是一种常见的恶性肿瘤，在世界范围内发病率呈逐年上升趋势。本研究旨在探讨乳腺癌阿霉素耐药的分子机制。方法采用美国国家生物技术信息中心（NCBI）基因表达综合数据库（GEO）中的GSE 76540数据集进行分析。分别采用GEO 2 R在线工具对化疗敏感病例和化疗耐药病例的差异表达基因（DEG）进行鉴定。通过使用大卫在线工具进行DEG的基因本体（GO）分析和京都基因和基因组百科全书（KEGG）富集分析。蛋白质-蛋白质相互作用（PPI）网络使用检索相互作用基因的搜索工具（STRING）构建，并使用Cytoscape软件可视化。并对关键肿瘤基因对生存和预后的影响进行了阐述。结果共获得1,481个DEG，其中上调基因549个，下调基因932个。根据GO分析，DEG在细胞外基质组织、RNA聚合酶II启动子转录的正调控、肺发育、基因表达的正调控、轴突导向等方面显著富集。KEGG途径富集分析结果显示，DEG富集最多的可以在：在PPI网络分析中，CDH 1、ESR 1、SOX 2、AR、GATA 3、FOXA 1、KRT 19、CLDN 7、AGR 2、ESRP 1、RAB 25、检测CLDN 4、IGF 1 R、CLDN 3和IRS 1。最后筛选出与ADR耐药相关的枢纽基因。结论应用生物信息学技术筛选出与ADR耐药相关的Hub基因。本研究结果可能有助于乳腺癌靶向治疗的发展。
Background Breast cancer is a common malignant tumor with increasing incidence worldwide. This study aimed to investigate the molecular mechanisms of the adriamycin (ADR) resistance in breast cancer. Methods The GSE76540 dataset downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database was adopted for analysis. Differentially expressed genes (DEGs) in chemo-sensitive cases and chemo-resistant cases were identified using the GEO2R online tool respectively. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DEGs were carried out by using the DAVID online tool. The protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) and visualized with Cytoscape software. The impact of key tumor genes on the survival and prognosis were described. Results A total of 1,481 DEGs were excavated, including 549 up-regulated genes and 932 down-regulated genes. According to the GO analysis, the DEGs were significantly enriched in: extracellular matrix organization, positive regulation of transcription from RNA polymerase II promoter, lung development, positive regulation of gene expression, axon guidance and so on. The results of KEGG pathway enrichment analysis showed that the most enriched DEGs can be detected in: pathways in cancer, PI3K/AKT signaling pathway, focal adhesion, Ras signaling pathway and so on. In the PPI network analysis, hub genes of CDH1, ESR1, SOX2, AR, GATA3, FOXA1, KRT19, CLDN7, AGR2, ESRP1, RAB25, CLDN4, IGF1R, CLDN3 and IRS1 were detected. Finally, there is a correlation filter out these hub genes in resistance of ADR. Conclusions Hub genes associated with ADR resistance were identified using bioinformatic techniques. The results of this study may contribute to the development of targeted therapy for breast cancer.
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影响因子：
14.9
作者：
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影响因子：
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