Systems analysis of the "weights" of Bcl-2 and Mcl-1 in mitochondrial apoptosis pathwayestablishes a predictor for best drug combination ratio

Abstract

Background : Inhibitors of B-cell CLL/lymphoma 2 (Bcl-2) family proteins have shown hope as antitumor drugs. While the notion that it is ef fi cient to coordinate, balance, and neutralize both arms of the anti-apoptotic Bcl-2 family has been validated in many cancer cells, the weights of the two arms contributing to apoptosis inhibition have not been explored. This study analyzed the best combination ratio for different Bcl-2 selective inhibitors. Methods : We used a previously established mathematical model to study the weights of Bcl-2 (representing both Bcl-2 and Bcl-xL in this study) and myeloid cell leukemia-1 (Mcl-1). Correlation and single-parameter sensitivity analysis were used to fi nd the major molecular determinants for Bcl-2 and Mcl-1 dependency, as well as their weights. Biological experiments were used to verify the mathematical model. Results : Bcl-2 protein level and Mcl-1 protein level, production, and degradation rates were the major molecular determinants for Bcl-2 and Mcl-1 dependency. The model gained agreement with the experimental assays for ABT-737/A-1210477 and ABT-737/compound 5 combination effect in MCF-7 and MDA-MB-231. Two sets of equations composed of Bcl-2 and Mcl-1 levels were obtained to predict the best combination ratio for Bcl-2 inhibitors with Mcl-1 inhibitors that stabilize and downregulate Mcl-1, respectively. Conclusions : The two sets of equations can be used as tools to bypass time-consuming and laborious experimental screening to predict the best drug combination ratio for treatment. Author summary: We used a mathematical model combined with experimental veri fi cation to quantitatively examine the contribution of the two arms of anti-apoptotic Bcl-2 proteins to apoptosis by weight. The correlation analysis and single-parameter sensitivity analysis showed that Bcl-2 protein level and Mcl-1 protein level, production, and degradation rates were the major molecular determinants. We gained two sets of equations as tools to bypass the time-consuming and laborious experimental screening to predict the best drug combination ratio for treatment. Biological experiments have veri fi ed the ef fi ciency of the tools in MCF-7, MDA-MB-231, OCI-AML3, and HCT-116 cells.