Dean Felsher (Medicine)
Jianghong Rao (Radiology)
Frederick Chin (Radiology)
David S. Paik (Radiology)

Cancers are caused by the activation of oncogenes. The Felsher laboratory has shown that cancers can be “oncogene addicted”. Hence, inactivation of oncogenes can be exploited as a novel therapeutic approach to treat cancer. However, the ability to predict when therapeutic agents that shut elicit oncogene addiction is limited by the lack of the existing of suitable approaches to rapidly and noninvasively monitor therapeutic efficacy. We have found a way to predict oncogene addiction rapidly after the initiation of therapy using mathematical models combined with measurements of cell proliferation and death (Felsher and Paik Laboratories). Hence, the capability to rapidly and noninvasively measure both proliferation and death in vivo could be transformative for care of cancer patients. Although Many imaging modalities have been developed to measure proliferation and growth of tumors, no existing probe can be used to in a highly quantitative manner. The Rao and Chin laboratories in collaboration with the Felsher laboratory have developed a potentially highly useful novel smart death probe. Now, we propose to develop this imaging probe to evaluate and predict the response to anti-cancer therapeutics. Our project will represent a collaboration amongst the Felsher, Rao, Chin and Paik groups, that combes work in oncology, radiology, and chemistry. We will take advantages of the novel conditional transgenic mouse models developed (Felsher laboratory) that provides a highly versatile model system to evaluate the smart probes. We will utilize novel chemistry, radio-labeling and molecular imaging methods (Rao and Chin laboratories). We will incorporate mathematical methods developed (Paik laboratory). Our approach will be to use chemistry based on enzyme-triggered intramolecular cyclization reaction and hydrophobic self-assembly and develop a radio-labeled caspase-3 active imaging probe ([18F]CAIP) for apoptosis detection. [18F]CAIP will selectively cyclize and accumulate in apoptotic cells with a long retention, leading to a high signal to background ratio and sensitivity in apoptosis imaging. We will optimize [18F]CAIP in vitro and in vivo and apply it to measure apoptosis in a transgenic mouse tumor model to monitor therapeutic effect and predict oncogene addiction following oncogene inactivation. We already have generated exciting preliminary data that illustrates that our technique and its application in our mouse models, is highly likely to be successful. We believe that our approach can be developed for into the medical clinic for the rapid and sensitive prediction of the efficacy of anti-cancer therapeutics.