Application of network diffusion approaches to drug screenings: A perspective on multilayered networks derived from cell lines and drugs

Network diffusion approaches are frequently used for identifying the relevant disease genes and for prioritizing the genes for drug sensitivity predictions. Majority of these studies rely on networks representing a single type of information. However, using multiplex heterogeneous networks (networks with multiple interconnected layers) is much more informative and helps to understand the global topology. We built a multi-layered network that incorporates information on protein-protein interactions, drug-drug similarities, cell line-cell line similarities and co-expressed genes. We applied Random Walk with Restart algorithm to investigate the interactions between drugs, targets and cancer cell lines. Results of ANOVA models show that these prioritized genes are among the most significant ones that relate to drug response. Moreover, the predictive power of the drug response prediction models built using the gene expression data of only the top ranked genes is similar to the models built using all the available genes. Taken together, the results confirm that the multiplex heterogeneous network-based approach is efficient in identifying the most significant genes associated with drug response.