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基于GEO数据库的近端与远端结肠癌特征基因生物信息学研究 被引量:6

Study on the differences gene between proximal and distal colon cancer based on GEO database by bioinformatics
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摘要 目的:通过分析近端与远端结直肠癌的差异基因集和其集中的关键通路,区分不同部位结肠癌的分子表达特征基因谱。方法:利用GEO数据库中高通量基因芯片数据筛选出具有结肠癌患者肿瘤部位近远端信息的芯片。采用GO基因功能注释和KEGG通路富集分析,筛选出可表征远端与近端结肠癌生物特性的特征基因簇和通路,并进行蛋白质相互作用网络可视化分析。结果:经差异基因分析后,发现不同部位结肠癌基因表达具有显著差异,且主要存在于一些重要的肿瘤相关信号通路,如Wnt信号通路,细胞外基质相关通路和免疫调控通路等。结论:本文利用生物信息学方法,从多种角度定义了近端和远端结肠癌的差异分子表达特征,为结肠癌的精准治疗提供理论依据。 AIM: To investigate the distinguish differences gene and its key pathways by analyzing the microarray data of the colon cancer patients with location information. METHODS: Gene expression profiles of the colon cancer with the information of location information in GEO database were selected. Then, using the GO gene functional annotation and KEGG pathway enrichment analysis, screening can represent different characteristics of location of colon cancer gene cluster & pathway, and visualization analysis for protein interaction network. RESULTS: After bioinformatics analysis, it was found that location affected the biological characteristics of colon carcinoma, and significantly altered some important tumor signaling pathways, such as Wnt signaling pathway, extracellular matrix related pathways and immuno-regulatory pathways. CONCLUSION: This study employed bioinformatics method from various perspectives to define the gene expression characteristics of different location in colon carcinoma. These results may provide theoretical basis for accurate treatment of colon cancer.
作者 张轶雯 楼倩雯 钟里科 潘宗富 方罗 黄萍 ZHANG Yiwen;LOU Qianwen;ZHONG Like;PAN Zongfu;FANG Luo;HUANG Ping(Department of Pharmacy, Zhejiang Cancer Hospital, Hangzhou 310022, Zhejiang , China;School of Pharmacy, Zhejiang University City College, Hangzhou 310001, Zhejiang, China)
出处 《中国临床药理学与治疗学》 CAS CSCD 2018年第4期422-427,共6页 Chinese Journal of Clinical Pharmacology and Therapeutics
基金 国家自然科学基金(81503165) 浙江省医药卫生科技计划项目(2017RC001) 浙江省中医药科技计划项目(2015ZA038)
关键词 近端结肠癌 远端结肠癌 差异基因 生物信息学分析 distal colon cancer proximal coloncancer differential gene expression bioinformatics
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