Cancers, Vol. 15, Pages 4356: Metabolic Reprogramming by Ribitol Expands the Therapeutic Window of BETi JQ1 against Breast Cancer

Cancers, Vol. 15, Pages 4356: Metabolic Reprogramming by Ribitol Expands the Therapeutic Window of BETi JQ1 against Breast Cancer

Cancers doi: 10.3390/cancers15174356

Authors: Ravi Doddapaneni Jason D. Tucker Pei J. Lu Qi L. Lu

Many cancer patients still lack effective treatments, and pre-existing or acquired resistance limits the clinical benefit of even the most advanced medicines. Recently, much attention has been given to the role of metabolism in cancer, expanding from the Warburg effect to highlight unique patterns that, in turn, may improve diagnostic and therapeutic approaches. Our recent metabolomics study revealed that ribitol can alter glycolysis in breast cancer cells. In the current study, we investigate the combinatorial effects of ribitol with several other anticancer drugs (chrysin, lonidamine, GSK2837808A, CB-839, JQ1, and shikonin) in various breast cancer cells (MDA-MB-231, MCF-7, and T-47D). The combination of ribitol with JQ1 synergistically inhibited the proliferation and migration of breast cancer cells cell-type dependently, only observed in the triple-negative MDA-MB-231 breast cancer cells. This synergy is associated with the differential effects of the 2 compounds on expression of the genes involved in cell survival and death, specifically downregulation in c-Myc and other anti-apoptotic proteins (Bcl-2, Bcl-xL, Mcl-1), but upregulation in p53 and cytochrome C levels. Glycolysis is differentially altered, with significant downregulation of glucose-6-phosphate and lactate by ribitol and JQ1, respectively. The overall effect of the combined treatment on metabolism and apoptosis-related genes results in significant synergy in the inhibition of cell growth and induction of apoptosis. Given the fact that ribitol is a metabolite with limited side effects, a combined therapy is highly desirable with relative ease to apply in the clinic for treating an appropriate cancer population. Our results also emphasize that, similar to traditional drug development, the therapeutic potential of targeting metabolism for cancer treatment may only be achieved in combination with other drugs and requires the identification of a specific cancer population. The desire to apply metabolomic intervention to a large scope of cancer types may be one of the reasons identification of this class of drugs in a clinical trial setting has been delayed.