Atorvastatin is a highly successful drug prescribed to lower cholesterol and prevent cardiovascular disease in millions of people. Though much of its effect comes from inhibiting a key enzyme in the cholesterol biosynthetic pathway, genes in this pathway interact with genes in other pathways, resulting in 15% of patients suffering painful muscular side effects and 50% having inadequate responses.
Many approved drugs are pleiotropic, for example statins, whose main cholesterol lowering activity is complemented by anticancer and pro-diabetogenic mechanisms involving poorly characterized genetic interaction networks. We investigated these using the Saccharomyces cerevisiae genetic model where most genetic interactions known are limited to the statin-sensitive S288C genetic background. We therefore broadened our approach by investigating gene interactions to include two statin-resistant UWOPS87-2421 and Y55 genetic backgrounds. Networks were functionally focused by selection of HMG1 and BTS1 mevalonate pathway genes for detecting genetic interactions. Networks, multi-layered by genetic background, were analysed for modifying key genes using network centrality (degree, betweenness, closeness), pathway enrichment, functional community modules and gene ontology. Statin treatment induces the unfolded protein response and we found modifying genes related to dysregulated endocytosis and autophagic cell death. To translate results to human cells, human orthologues were searched for other drugs targets, thus identifying candidates for synergistic anticancer bioactivity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.