基于细胞系-药物K近邻的抗癌药物敏感性预测  

Prediction of Anti-cancer Drug Sensitivity based on Cell Line-drug K Nearest Neighbors

作　　者：王波 魏东 李玉双[1] WANG Bo;WEI Dong;LI Yu-shuang(School of Science,Yanshan University,Qinhuangdao 066004,China;Hebei Dataport Technology Co.,Ltd,Qinhuangdao 066004,China)

机构地区：[1]燕山大学理学院,河北秦皇岛066004 [2]河北数港科技有限公司,河北秦皇岛066004

出　　处：《数学的实践与认识》2020年第4期295-300,共6页Mathematics in Practice and Theory

基　　金：国家自然科学基金(61807029).

摘　　要：抗癌药物敏感性数据的缺失会对后续癌症数据分析产生重要影响.高通量测序技术为构建计算模型,有效预测抗癌药物敏感性提供了可能.依据已有的合理性假设:相似的细胞系对于目标药物具有相似的反应;相似的药物对于目标细胞系具有相似的反应,本文综合考虑了细胞系的基因表达和基因突变特征,给出细胞系相似性新的定义形式,结合药物相似性度量方法,提出了"细胞系-药物K近邻"计算模型,并将其成功应用于癌症细胞系百科全书(CCLE),得到的抗癌药物敏感性预测结果明显优于已有的经典模型.Missing values in the anti-cancer drug sensitivity data might have impact on the downstream cancer data analyses.High-throughput sequencing technology provides us a big chance to build computational models for predicting the sensitivity of anti-cancer drugs.According to a reasonable hypothesis,"similar cell lines have similar response to a given drug,and similar drugs have similar response to a given cell line".Comprehensive consideration of gene expression and gene mutation information of cell lines,a new definition of cell line similarity is given.Combining the drug similarity,a computational model named cell line-drug K Nearest Neighbor is proposed,and then applied it on the Cancer Cell Line Encyclopedia.The prediction result is significantly superior to some popular methods.

关 键 词：抗癌药物敏感性 细胞系相似性 药物相似性 K近邻 

分 类 号：R965[医药卫生—药理学]