Fig. 1

Schematic representation of experimental and computational approach to personalized combination targeted therapy predictions. Following tumor extraction and culture establishment, biological data is generated (e.g., chemical screening, transcriptome sequencing, exome sequencing, siRNA interference screening and phosphoproteomic analysis) and used as input for PTIM modeling. To briefly explain the graphical model representation, targets A and B denote two independent single points of failure. Targets C and D denote parallel targets, which independently are not predicted to be effective, but together will be synergistic and lead to significant cell growth inhibition. Targets A, B, and the C-D parallel block are in series and may target independent pathways. Series blocks, when inhibited together, may abrogate cancer resistance mechanisms by knockdown of independent pathways. Model sensitivity scores for gene target combinations are used to design and rank follow-up in vitro validation and in vivo validation experiments. The “Exome-Seq” representative images was adapted from an image on the Wikipedia Exome sequencing article originally created by user SarahKusala and available under Creative Commons 3.0 license. An unaltered portion of the image was used. The mouse image used is public domain and accessed through Bing image search at the following weblink: http://img.res.meizu.com/img/download/uc/27/83/20/60/00/2783206/w100h100