Ovarian Cancer Metabolism: Systems-Scale Dynamics As a Platform for Identifying Therapeutic Targets

While response to first-line treatment of ovarian cancer (the most deadly gynecological cancer) is high, most patients relapse, and five-year survival rates have remained constant for decades.  A significant cause of this relapse and resultant mortality is believed to be a class of cells referred to as “cancer initiating cells”, a chemoresistant subpopulation believed to be able to reconstitute the entire tumor.

Though metabolic dysfunction is becoming increasingly accepted as a hallmark of cancer, efforts to exploit and manipulate metabolism to fight cancer (analogous to metabolic engineering) are not yet pervasive. To move towards that goal, it is imperative to have a more comprehensive, systems-scale understanding of cancer metabolism than just (for example) aerobic glycolysis and glutaminolysis. To this end, we have performed system-wide metabolite profiling (metabolomics) of intracellular ovarian cancer metabolism along three important axes: bulk vs. cancer initiating cells, microenvironment-relevant perturbations (e.g., hypoxia, decreased glucose, chemotherapeutics), and temporal dynamics.

This work is the first-ever metabolic characterization of a cancer initiating cell line and its isogenic parental cell line, allowing for unique insight into the metabolic differences specific to cancer initiating cells that could be exploited in treatment. The cell types display significant, time-dependent differential responses to environmental perturbations. There are also more general differences between these cell types even in the absence of perturbations, including a pathway and two of its metabolites (proline and putrescine) that are typically accumulated in cancer, but are consistently lower in cancer initiating cells. These molecules also have documented roles in differentiation, suggesting a relationship between their levels and a delicate balance between proliferation and potency. We believe these differences (and others) can be leveraged to identify novel therapeutic targets, or perhaps even leads based on endogenous metabolites, that would actively target cancer initiating cells.