Chemotherapeutic drugs are toxins for killing tumor cells, but their efficacy is often limited by the tolerance ceiling of normal tissues. A survey of systemic toxicity will provide valuable information on a new drug candidate for pharmaceutical development, and on the therapeutic regimen for existing drug combinations for each patient. The overall goal of this project is to develop and validate whole-body apoptosis imaging as a new approach for characterizing the systemic toxicity profile of anticancer drugs. Apoptosis is an important manifestation of toxicity-induced tissue injuries. A whole-body scan, which we call ToxScan, detects tissue injuries systemically, in terms of a toxicity profile in response to the drug. We use a radiopharmaceutical, 99mTc-Duramycin, which detects exposed phosphatidylethanolamine in dead and dying cells. The imaging agent has binding affinity/specificity like an antibody yet clearance kinetics of a peptide. It is thus uniquely suitd for whole-body imaging applications. Our central hypothesis is that a systemic toxicity profile reflects the individual susceptibility to anticancer treatment. The scan provides indices for drug tolerance, and a prognostic indicator for chronic adverse effects. In preliminary studies, we demonstrated the sensitivity of whole-body 99mTc-Duramycin scan by detecting cell death in multiple tissues after a single clinically relevant dose of Doxorubicin. Whole-body apoptosis scan also revealed individualized response to the same therapeutic regimen. Single-and multi-organ indices for tissue injury are being derived for diagnostic and prognostic purposes. The evaluation of toxicity in such fashion will significantly accelerate the development of new anticancer drugs and new combination treatments. Ultimately, this approach will benefit oncology patients by optimizing therapies on a personalized basis.
We propose to develop and validate a whole-body apoptosis imaging technique for assessing systemic toxicity induced by anticancer treatment. This approach provides a diagnostic indicator for drug tolerance and prognostic index for chronic effects. It will help make pharmaceutical development a more efficient process and ultimately benefit clinical oncology by optimizing cancer treatment on a personalized basis.
