Serial Diffusion MRI to Monitor and Model Treatment Response of the Targeted Nanotherapy CRLX101
Abstract
Purpose: Targeted nanotherapies are being developed to improve tumor drug delivery and enhance therapeutic response. Techniques that can predict response will facilitate clinical translation and may help define optimal treatment strategies. We evaluated the efficacy of diffusion-weighted magnetic resonance imaging to monitor early response to CRLX101 (a cyclodextrin-based polymer particle containing the DNA topoisomerase I inhibitor camptothecin) nanotherapy (formerly IT-101), and explored its potential as a therapeutic response predictor using a mechanistic model of tumor cell proliferation. Experimental Design: Diffusion MRI was serially conducted following CRLX101 administration in a mouse lymphoma model. Apparent diffusion coefficients (ADCs) extracted from the data were used as treatment response biomarkers. Animals treated with irinotecan (CPT-11) and saline were imaged for comparison. ADC data were also input into a mathematical model of tumor growth. Histological analysis using cleaved-caspase 3, terminal deoxynucleotidyl transferase–mediated dUTP nick end labeling, Ki-67, and hematoxylin and eosin (H&E) were conducted on tumor samples for correlation with imaging results. Results: CRLX101-treated tumors at day 2, 4, and 7 posttreatment exhibited changes in mean ADC = 16 ± 9%, 24 ± 10%, 49 ± 17%, and size (TV) = −5 ± 3%, −30 ± 4%, and −45 ± 13%, respectively. Both parameters were statistically greater than controls [p(ADC) ≤ 0.02, and p(TV) ≤ 0.01 at day 4 and 7], and noticeably greater than CPT-11–treated tumors (ADC = 5 ± 5%, 14 ± 7%, and 18 ± 6%; TV = −15 ± 5%, −22 ± 13%, and −26 ± 8%). Model-derived parameters for cell proliferation obtained using ADC data distinguished CRLX101-treated tumors from controls (P = 0.02). Conclusions: Temporal changes in ADC specified early CRLX101 treatment response and could be used to model image-derived cell proliferation rates following treatment. Comparisons of targeted and nontargeted treatments highlight the utility of noninvasive imaging and modeling to evaluate, monitor, and predict responses to targeted nanotherapeutics.
Additional Information
© 2013 American Association for Cancer Research. Received August 20, 2012. Revision received February 18, 2013. Accepted March 11, 2013. Published Online First March 26, 2013. The authors thank Dr. Thomas Schluep of Calando Pharmaceuticals for providing the CRLX101, Dr. Andrey Demyanenko, Desiree Crow, Bita Alaghebandan, and Sonia Collazo for their technical assistance. Drs. Mark Davis, Yun Yen, and Scott Fraser gave helpful advice and support. The project was funded by NIBIB R01 EB000993, NIH R01 EB00194, NRSA T32GM07616, City of Hope Lymphoma SPORE Grant (P50 CA107399), the Beckman Institute, and the Caltech/City of Hope Biomedical Initiative. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. No potential conflicts of interests were disclosed.Attached Files
Accepted Version - nihms459543.pdf
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Additional details
- PMCID
- PMC3644008
- Eprint ID
- 38981
- Resolver ID
- CaltechAUTHORS:20130619-092133521
- R01 EB000993
- NIH
- R01 EB00194
- NIH
- T32GM07616
- NIH
- P50 CA107399
- City of Hope Lymphoma SPORE
- Caltech Beckman Institute
- Caltech/City of Hope Biomedical Initiative
- Created
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2013-06-19Created from EPrint's datestamp field
- Updated
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2021-11-09Created from EPrint's last_modified field