Abstract
Hypoxia, a low level of oxygen in the tissue, is a feature of most solid tumors. It arises due to an imbalance between the oxygen supply from the abnormal vasculature and oxygen demand by the large number of tumor and stromal cells. Hypoxia has been implicated in the development of aggressive tumors and tumor resistance to various therapies. This makes hypoxia a negative marker of patients’ survival. However, recent advances in designing new hypoxia-activated pro-drugs and adoptive T cell therapies provide an opportunity for exploiting hypoxia in order to improve cancer treatment. We used novel mathematical models of micro-pharmacology and computational optimization techniques for determining the most effective treatment protocols that take advantage of heterogeneous and dynamically changing oxygenation in in vivo tumors. These models were applied to design schedules for a combination of three therapeutic compounds in pancreatic cancers and determine the most effective adoptive T cell therapy protocols in melanomas.
Footnotes
Research supported by NIH Physical Sciences Oncology Network Grant U01CA202229-04, NIH Physical Sciences Oncology Network Grant U54CA193489-04, and the Moffitt Team Science Award.
