A Predictive Model for Selective Targeting of the Warburg Effect through GAPDH Inhibition with a Natural Product

In a recent Cell Metabolism paper, a study from Dr. Jason Locasale's group, led by PhD student Maria Liberti, identified differences in enzymes involved in the Warburg Effect (the abnormal process through which cancer cells metabolize glucose to produce energy). Importantly, these differences can be used to predict the therapeutic response to targeting glucose metabolism in cancer. Liberti et. al. further established a natural product produced by fungi, koningic acid (KA), to be a selective inhibitor of GAPDH, a rate-limiting enzyme that contributes to the breakdown of glucose. Targeting GAPDH with KA has therapeutic properties through its effects on glucose metabolism during the Warburg Effect.

Targeted cancer therapy is capable of differentiating normal cells from cancer cells based on their genetics, and exploits these differences during treatment. While these therapies have advanced precision medicine, strategies for targeting cancer metabolism remain elusive because the genetic differences from normal cell metabolism are not always clear. 

In this paper, Liberti et. al. explored the concept that specific properties of the metabolic network can allow a small change in enzyme activity in glucose metabolism to selectively target tumor cells. Using metabolic control analysis, they found pharmacological interventions that were able to specifically disrupt metabolic pathways important in tumor growth, but with limited adverse effect on normal cells, thereby providing the basis for a novel targeted therapy that selectively kills cancer cells based on their metabolic profile.