论文部分内容阅读
[目的]了解乳腺癌内分泌治疗敏感相关基因的研究现状,构建相关基因相互联系的网络模块。[方法]在Embase、Medline/Pubmed及BIOSIS Preview数据库中检索2001～2010年发表的有关乳腺癌内分泌治疗敏感相关基因的文献进行计量学分析,并对相关基因及其产物进行生物信息学分析。[结果]168篇文献纳入研究,共涉及267个基因。文献计量分析结果显示近3年来该领域的研究目前处于快速发展阶段;美国在该领域研究水平处于明显领先地位;Breast Cancer Research and Treatment与Clinical Cancer Research为载文量最多的期刊。生物信息学分析提示关键基因和瓶颈基因具体包括CCND1、AKT1、NFKB1、PIK3CA、TPX2、EGFR、Bcl-2、BRCA1、MYC、SRC、VEGFA、AR、ESR1、TNF、BIRC5、CDK1、TP53、Jun。[结论]通过对乳腺癌内分泌治疗敏感相关基因的文献计量学分析及生物信息学分析,我们可清楚了解目前该领域研究现状及基因网络模块对未来研究的预测作用,帮助研究人员作进一步研究打下基础。
[Objective] To understand the research status of the genes related to endocrine therapy in breast cancer and construct the network module of related genes. [Methods] We searched the literature about Embest, Medline / Pubmed and BIOSIS Preview retrieved from 2001 to 2010 for the genes related to endocrine therapy in breast cancer, and analyzed the related genes and their products by bioinformatics analysis. [Results] 168 articles were included in the study, involving a total of 267 genes. The results of bibliometric analysis show that the research in this field has been in a rapid development stage in recent 3 years. The United States has a clear leading research level in this field. Breast Cancer Research and Treatment and Clinical Cancer Research are the most frequently published journals. Bioinformatics analysis suggested that the key genes and bottleneck genes include CCND1, AKT1, NFKB1, PIK3CA, TPX2, EGFR, Bcl-2, BRCA1, MYC, SRC, VEGFA, AR, ESR1, TNF, BIRC5, CDK1, TP53, Jun. [Conclusion] Through the bibliometrics and bioinformatics analysis of the genes related to endocrine therapy in breast cancer, we can know the current situation in the field and predict the future research of gene network module, and help researchers to further study and lay down basis.