• The molecular basis of synergism between carboplatin and ABT-737 therapy targeting ovarian carcinomas.

      Jain, Harsh Vardhan; Müller, A (2011-02-01)
      Resistance to standard chemotherapy (carboplatin + paclitaxel) is one of the leading causes of therapeutic failure in ovarian carcinomas. Emergence of chemoresistance has been shown to be mediated in part by members of the Bcl family of proteins including the antiapoptotic protein Bcl-x(L), whose expression is correlated with shorter disease-free intervals in recurrent disease. ABT-737 is an example of one of the first small-molecule inhibitors of Bcl-2/Bcl-x(L) that has been shown to increase the sensitivity of ovarian cancer cells to carboplatin. To exploit the therapeutic potential of these two drugs and predict optimal doses and dose scheduling, it is essential to understand the molecular basis of their synergistic action. Here, we build and calibrate a mathematical model of ABT-737 and carboplatin action on an ovarian cancer cell line (IGROV-1). The model suggests that carboplatin treatment primes cells for ABT-737 therapy because of an increased dependence of cells with DNA damage on Bcl-x(L) for survival. Numerical simulations predict the existence of a threshold of Bcl-x(L) below which these cells are unable to recover. Furthermore, co- plus posttreatment of ABT-737 with carboplatin is predicted to be the best strategy to maximize synergism between these two drugs. A critical challenge in chemotherapy is to strike a balance between maximizing cell-kill while minimizing patient drug load. We show that the model can be used to compute minimal doses required for any desired fraction of cell kill. These results underscore the potential of the modeling work presented here as a valuable quantitative tool to aid in the translation of novel drugs such as ABT-737 from the experimental to clinical setting and highlight the need for close collaboration between modelers and experimental scientists.
    • Therapeutic Potential of Bacteria against Solid Tumors.

      Hatzikirou, Haralampos; López Alfonso, Juan Carlos; Leschner, Sara; Weiss, Siegfried; Meyer-Hermann, Michael; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany. (2017-04-01)
      Intentional bacterial infections can produce efficacious antitumor responses in mice, rats, dogs, and humans. However, low overall success rates and intense side effects prevent such approaches from being employed clinically. In this work, we titered bacteria and/or the proinflammatory cytokine TNFα in a set of established murine models of cancer. To interpret the experiments conducted, we considered and calibrated a tumor-effector cell recruitment model under the influence of functional tumor-associated vasculature. In this model, bacterial infections and TNFα enhanced immune activity and altered vascularization in the tumor bed. Information to predict bacterial therapy outcomes was provided by pretreatment tumor size and the underlying immune recruitment dynamics. Notably, increasing bacterial loads did not necessarily produce better long-term tumor control, suggesting that tumor sizes affected optimal bacterial loads. Short-term treatment responses were favored by high concentrations of effector cells postinjection, such as induced by higher bacterial loads, but in the longer term did not correlate with an effective restoration of immune surveillance. Overall, our findings suggested that a combination of intermediate bacterial loads with low levels TNFα administration could enable more favorable outcomes elicited by bacterial infections in tumor-bearing subjects. Cancer Res; 77(7); 1553-63. ©2017 AACR.