(306g) Invited Talk: Systems Biology Approaches to Drug Discovery and Repurposing

“Omics” technologies have enabled network-level measurements of genes, proteins, and metabolites from cellular models of disease. Systems biology attempts to synthesize these quantitative measurements into data-driven models to explain biological function. Here, I will discuss three different systems biology approaches using metabolomics, proteomics, and bioinformatics to discover or repurpose drugs for cancer and aging. First, using metabolomics, we designed a synergistic drug combination that mimics nutrient deprivation to kill cancer cells. Second, by integrating a proteomic signature of cellular senescence with large-scale drug screening databases, we predicted and then validated that EGFR inhibitors are toxic to a model of aging, specifically senescent human mammary epithelial cells. Finally, we developed a bioinformatic approach to integrate gene expression data with drug screening data from hundreds of cancer cell lines to identify clinically approved drugs whose efficacy depends on metabolic pathway activity. Taken together, these studies demonstrate how metabolomics, proteomics, and bioinformatics can all serve to identify drugs for cancer and aging.