Using activation status of signaling pathways as mechanism-based biomarkers to predict drug sensitivity

被引:29
作者
Amadoz, Alicia [1 ]
Sebastian-Leon, Patricia [1 ]
Vidal, Enrique [1 ,2 ]
Salavert, Francisco [1 ,2 ]
Dopazo, Joaquin [1 ,2 ,3 ]
机构
[1] CIPF, Computat Genom Dept, Valencia, Spain
[2] CIBERER, Bioinformat Rare Dis BIER, Valencia, Spain
[3] INB CIPF, Funct Genom Node, Valencia, Spain
关键词
SQUAMOUS-CELL CARCINOMA; GENE-EXPRESSION; BREAST-CANCER; HEPATOCELLULAR-CARCINOMA; AZD6244; ARRY-142886; ANTITUMOR-ACTIVITY; CONNECTIVITY MAP; DOWN-REGULATION; LUNG-CANCER; RNA-SEQ;
D O I
10.1038/srep18494
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
070301 [无机化学]; 070403 [天体物理学]; 070507 [自然资源与国土空间规划学]; 090105 [作物生产系统与生态工程];
摘要
Many complex traits, as drug response, are associated with changes in biological pathways rather than being caused by single gene alterations. Here, a predictive framework is presented in which gene expression data are recoded into activity statuses of signal transduction circuits (sub-pathways within signaling pathways that connect receptor proteins to final effector proteins that trigger cell actions). Such activity values are used as features by a prediction algorithm which can efficiently predict a continuous variable such as the IC50 value. The main advantage of this prediction method is that the features selected by the predictor, the signaling circuits, are themselves rich-informative, mechanism-based biomarkers which provide insight into or drug molecular mechanisms of action (MoA).
引用
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页数:13
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