| Abstract: |
| Resistance to the taxane docetaxel is a major obstacle in the treatment of solid tumors, particularly prostate and pancreatic cancer. The stress-response protein NUPR1 has been identified as an important molecular driver of docetaxel resistance, suggesting that pharmacologic inhibition of NUPR1 may restore treatment sensitivity. While the early NUPR1 inhibitor ZZW-115 demonstrated promising anti-tumor activity, concerns about cardiotoxicity motivated the development of next-generation NUPR1-targeting compounds such as AJO14 and related derivatives. \
In this work we develop mechanistic mathematical models to investigate tumor response to combined docetaxel and NUPR1-targeted therapy. The models are informed by preclinical data, including in vitro prostate cancer cell-line experiments and in vivo pancreatic cancer xenografts. Using these calibrated models, we quantify treatment effects, explore potential synergy between therapies, and extend the analysis to heterogeneous virtual populations to examine how variability in tumor growth and drug response influences outcomes. This framework provides a quantitative approach for evaluating strategies to overcome docetaxel resistance and for guiding the development of NUPR1-targeted combination therapies. |
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