Abstract
AbstractSpheroids formation during epithelial ovarian cancer progression correlates with peritoneal organ colonization, disease recurrence, and poor prognosis. Although cancer progression has been demonstrated to be associated with and driven by metabolic changes within transformed cells, possible associations between metabolic dynamics and metastatic morphological transitions remain unexplored. To address this problem, we performed quantitative proteomics to identify protein signatures associated with three distinct morphologies (2D monolayers and two geometrically individual three-dimensional spheroidal states) of the high-grade serous ovarian cancer line OVCAR-3. Integrating the protein states onto genome-scale metabolic models allowed us to construct context-specific metabolic models for each morphological stage of the OVCAR-3 cell line and systematically evaluate their metabolic functionalities. We obtained disease-driving metabolic reaction modules using these models and elucidated gene knockout strategies to reduce metabolic alterations associated with disease progression. We explored the DrugBank database to mine pharmacological agents and evaluated the effect of drugs in impairing cancer progression. Finally, we experimentally validated our predictions by confirming the ability of one of our predicted drugs: the neuraminidase inhibitor oseltamivir, to disrupt the metastatic spheroidal morphologies without any cytotoxic effect on untransformed stromal mesothelial monolayers.
Publisher
Cold Spring Harbor Laboratory