Personalized therapy requires imaging methods for assessing drug delivery. Clinically, liposomal agents, such as liposomal doxil, are effective in small subsets of patients, for example, with breast or ovarian cancer, but at present, methods for predicting those that may respond are lacking. Such methods are needed both for efficacy in selecting patients who may benefit from the drug, and avoiding significant toxicity in patients who will not respond. Response is dependent on delivery and imaging delivery should aide response prediction as well as enable development of techniques for improving delivery/therapeutic efficacy even in patients that were initially non-responders. For imaging, MR provides superb soft tissue contrast, but has not been fully capitalized upon for assessing delivery due to a dearth of clinically available agents for predicting delivery that have sufficient signal and low background as well as appropriate architecture to mimic the therapeutic agent. Clinically used agents generally deliver one gadolinium ion/chelate. Amplification schemes are needed to deliver multiple imaging moieties per nanoparticle, however, this need to be done carefully because excess gadolinium (Gd) concentration can result in signal loss. We recently demonstrated that liposomes can be created with Gd-chelates on both the surface and within liposomes (Dual-Gd), and that these have approximately 10,000X greater relaxivity per nanoparticle than traditional Gd-chelates. For nanoparticle therapeutics, delivery is a factor in efficacy and is dependent on the vasculature. We hypothesize that imaging using Dual-Gd liposomes can predict response to liposomal therapy by assessing delivery, and that manipulation of the vasculature can improve response. To assess delivery, imaging liposomes of the same size as liposomal doxil will be produced. Liposomes of such size (~100-200 nm) tend to travel to and get entrapped in tumor vasculature via the enhanced permeability and retention effect (EPR). The functional characteristics of the vasculature can be manipulated by pharmacologic agents that affect normal vasculature or that affect the aberrant angiogenic tumor vasculature; we hypothesize that these may be exploited to improve delivery of nanoparticle therapeutics to the tumor. SA1. Test the hypothesis that Dual-Gd liposomes made the same size as therapeutic-liposomes can predict response to therapeutic-liposomes in breast and ovarian cancer models. SA2. Test the hypothesis that response to therapeutic-liposomes can be improved by vascular manipulation using fast acting agents that affect primarily normal blood vessels to affect vascular parameters such as vasoconstriction, vasodilatation, and/or permeability and that response can be predicted by imaging using Dual-Gd liposomes. SA3. Test the hypothesis that response to therapeutic-liposomes can be improved by vascular manipulation using agents that affect primarily tumor vessels, such as the anti-angiogenic agents, to alter vascular function and that response can be predicted by imaging using Dual-Gd liposomes.
The proposal seeks to investigate imaging methods to evaluate delivery of nanoparticle chemotherapy to predict response and to create methods to improve such delivery and therefore improve survival in patients with cancer.
|Ravoori, Murali K; Singh, Sheela P; Lee, Jaehyuk et al. (2017) In Vivo Assessment of Ovarian Tumor Response to Tyrosine Kinase Inhibitor Pazopanib by Using Hyperpolarized 13C-Pyruvate MR Spectroscopy and 18F-FDG PET/CT Imaging in a Mouse Model. Radiology 285:830-838|
|Ravoori, M K; Singh, S; Bhavane, R et al. (2016) Multimodal Magnetic Resonance and Near-Infrared-Fluorescent Imaging of Intraperitoneal Ovarian Cancer Using a Dual-Mode-Dual-Gadolinium Liposomal Contrast Agent. Sci Rep 6:38991|
|Ravoori, Murali K; Nishimura, Masato; Singh, Sheela P et al. (2015) Tumor T1 Relaxation Time for Assessing Response to Bevacizumab Anti-Angiogenic Therapy in a Mouse Ovarian Cancer Model. PLoS One 10:e0131095|