Using activation status of signaling pathways as mechanism-based biomarkers to predict drug sensitivity
Open Access
- 18 December 2015
- journal article
- research article
- Published by Springer Science and Business Media LLC in Scientific Reports
- Vol. 5 (1), 18494
- https://doi.org/10.1038/srep18494
Abstract
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).Keywords
This publication has 98 references indexed in Scilit:
- Systematic identification of genomic markers of drug sensitivity in cancer cellsNature, 2012
- The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivityNature, 2012
- Epidermal growth factor receptor (EGFR) and squamous cell carcinoma of the skin: Molecular bases for EGFR-targeted therapyPathology - Research and Practice, 2011
- Interactome Networks and Human DiseaseCell, 2011
- Systems biology and the future of medicineWires Systems Biology and Medicine, 2011
- The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive modelsNature Biotechnology, 2010
- A chemical and phosphoproteomic characterization of dasatinib action in lung cancerNature Chemical Biology, 2010
- Microtubule-mediated NF-κB activation in the TNF-α signaling pathwayExperimental Cell Research, 2009
- An integrative genomics approach to infer causal associations between gene expression and diseaseNature Genetics, 2005
- The evolution of molecular biology into systems biologyNature Biotechnology, 2004