Combinatorial high-throughput experimental and bioinformatic approach identifies molecular pathways linked with the sensitivity to anticancer target drugs

摘要: Effective choice of anticancer drugs is important problem modern medicine. We developed a method termed OncoFinder for the analysis new type biomarkers reflecting activation intracellular signaling and metabolic molecular pathways. These may be linked with sensitivity to drugs. In this study, we compared experimental data obtained in our laboratory Genomics Drug Sensitivity Cancer (GDS) project testing response transcriptomes various human cell lines. The microarray-based profiling was performed lines before addition medium, growth inhibition curves were built each drug, featuring characteristic IC50 values. assayed here four target - Pazopanib, Sorafenib, Sunitinib Temsirolimus, 238 different lines, which 11 profiled 227 GDS project. Using OncoFinder-processed transcriptomic on ~600 pathways, identified pathways showing significant correlation between pathway strength (PAS) values these Correlations reflect relationships drug features. intersected results found significantly correlated both assay For most generated models their interaction known target(s) respective first time, study uncovered mechanisms underlying cancer at high-throughput interactomic level.