摘要
目的通过挖掘乳腺癌疾病力学-药物靶点,将力学与药物相结合,为乳腺癌新药的开发以及老药新用提供重要参考。方法基于乳腺癌多重表达谱数据及GO数据库注释文件,应用差异表达分析及富集分析等生物信息学方法挖掘与乳腺癌疾病力学-药物相关的作用靶点,并基于药物靶点数据库构建包含GO功能-基因-药物的三维网络图。结果通过整合数据识别出乳腺癌疾病中参与到力学-药学作用机制中的靶点87个,其中12个被证实为乳腺癌或癌症药物靶点并且发挥了力学相关功能,其余靶点可作为潜在乳腺癌药物靶点。结论通过数据挖掘找出87个参与到乳腺癌疾病力学-药学作用中的靶点,揭示了乳腺癌疾病中力学-药物作用的分子机制,为疾病药物治疗提供了指引。
Objective The combination of mechanics and drugs through the mining of mechanics-drug targets for breast cancer provide an important reference for the development of new drugs for breast cancer and repurposing old drugs. Methods Based on the multiple expression data of breast cancer and the annotation data in GO database,bioinformatics methods such as differential expression analysis and enrichment analysis were used to explore the targets involved in the mechanics-drug interaction in breast cancer,and constructed a threedimensional network of GO function-gene-drugs based on the drug target databases. Results Eighty-seven targets involved in the interaction between mechanics and pharmacology in breast cancer were identified through integrating the data,of which 12 targets were confirmed to be breast cancer or cancer drug targets and played a mechanical role,and the other genes could be used as potential targets for breast cancer drugs and served as reference for related studies. Conclusions Through data mining, we identified 87 targets involved in the mechanical-pharmaceutical interaction in breast cancer,and revealed the molecular mechanism of mechanicalpharmaceutical interaction in breast cancer, which provided guidelines for drug therapy.
出处
《北京生物医学工程》
2017年第6期558-563,625,共7页
Beijing Biomedical Engineering
基金
北京市教育委员会科技发展计划一般项目(KM201710025010)
首都医科大学基础临床合作项目(16JL58)
吉林大学符号计算与知识工程教育部重点实验室开放课题(93K172016K07)资助
关键词
乳腺癌
力学微环境
药物靶点
功能分析
数据挖掘
breast cancer
mechanical microenviro- nment
drug target
functional analysis
data mining
