Detection of orthotopic xenograft tumors is difficult due to poor spatial resolution and reduced image fidelity with traditional optical imaging modalities. In particular, light scattering and attenuation in tissue at depths beyond subcutaneous implantation hinder adequate visualization. We evaluate the use of multispectral optoacoustic tomography (MSOT) to detect upregulated epidermal growth factor (EGF) receptor in orthotopic pancreatic xenografts using a near-infrared (NIR) EGF-conjugated CF-750 fluorescent probe. MSOT is based on the photoacoustic effect and thus not limited by photon scattering, resulting in high-resolution tomographic images. Pancreatic tumor-bearing mice with luciferase-transduced S2VP10L tumors were intravenously injected with EGF-750 probe prior to MSOT imaging. We characterized probe specificity and bioactivity via immunoblotting, immunocytochemistry, and flow cytometric analysis. In vitro data along with optical bioluminescence/fluorescence imaging were used to validate acquired MSOT in vivo images of probe biodistribution. Indocyanine green dye was used as a non-specific control to define specificity of EGF-probe accumulation. Maximum accumulation occurred at six hours post-injection, demonstrating specific intra-tumoral probe uptake and minimal liver and kidney off-target accumulation. Optical bioluminescence and fluorescence imaging confirmed tumor-specific probe accumulation consistent with MSOT images. These studies demonstrate the utility of MSOT to obtain volumetric images of ligand probe biodistribution in vivo to detect orthotopic pancreatic tumor lesions through active targeting of EGF receptor.

Defining tumor stage at diagnosis is a pivotal point for clinical decisions about patient treatment strategies. In this respect, early detection of occult metastasis invisible to current imaging methods would have a major impact on best care and long-term survival. Mathematical models that describe metastatic spreading might estimate the risk of metastasis when no clinical evidence is available. In this study, we adapted a top-down model to make such estimates. The model was constituted by a transport equation describing metastatic growth and endowed with a boundary condition for metastatic emission. Model predictions were compared with experimental results from orthotopic breast tumor xenograft experiments conducted in Nod/Scidγ mice. Primary tumor growth, metastatic spread and growth were monitored by 3D bioluminescence tomography. A tailored computational approach allowed the use of Monolix software for mixed-effects modeling with a partial differential equation model. Primary tumor growth was described best by Bertalanffy, West, and Gompertz models, which involve an initial exponential growth phase. All other tested models were rejected. The best metastatic model involved two parameters describing metastatic spreading and growth, respectively. Visual predictive check, analysis of residuals, and a bootstrap study validated the model. Coefficients of determination were $R^2 = 0.94$ for primary tumor growth and $R^2 = 0.57$ for metastatic growth. The data-based model development revealed several biologically significant findings. First, information on both growth and spreading can be obtained from measures of total metastatic burden. Second, the postulated link between primary tumor size and emission rate is validated. Finally, fast growing peritoneal metastases can only be described by such a complex partial differential equation model and not by ordinary differential equation models. This work advances efforts to predict metastatic spreading during the earliest stages of cancer. Cancer Res; 74(22); 1–11. ©2014 AACR.

Defining tumor stage at diagnosis is a pivotal point for clinical decisions regarding patient treatment strategies. In this respect, early detection of occult metastasis invisible to current imaging methods would have a major impact on best care and long-term survival. Mathematical models that describe metastatic spreading might estimate the risk of metastasis when no clinical evidence is available. In this study, we adapted a top-down model to make such estimates. The model was constituted by a transport equation describing metastatic growth and endowed with a boundary condition for metastatic emission. Model predictions were compared to experimental results from orthotopic breast tumor xenograft experiments conducted in Nod/Scid gamma mice. Primary tumor growth, metastatic spread and growth were monitored by 3D bioluminescence tomography. A tailored computational approach allowed the use of Monolix software for mixed-effects modeling with a partial differential equation model.
Primary tumor growth was described best by Bertalanffy, West and Gompertz models which involve an initial exponential growth phase. All other tested models were rejected. The best metastatic model involved two parameters describing metastatic spreading and growth, respectively. Visual Predictive Check, analysis of residuals and a bootstrap study validated the model. Coefficients of determination were R²=0.94 for primary tumor growth and R²=0.57 for metastatic growth. The data-based model development revealed several biologically significant findings. First, information on both growth and spreading can be obtained from measures of total metastatic burden. Second, the postulated link between primary tumor size and emission rate is validated. Finally, fast growing peritoneal metastases can only be described by such a complex partial differential equation model and not by ordinary differential equation models. This work advances efforts to predict metastatic spreading during the earliest stages of cancer.

Cancers due to germline mutations in the BRCA1 gene tend to lack targets for approved chemoprevention agents. This study aimed at a targeted chemoprevention strategy for BRCA1-associated malignancies. Mutant BRCA1 limits the base-excision DNA repair activity that addresses oxidative DNA damage, the accumulation of which heightens one’s risk for cancer. Therefore, we conducted a high-throughput chemical screen to identify drug candidates that could attenuate the inhibitory effects of mutant BRCA1 on this repair activity, thereby describing a new class of DNA repair-activating chemopreventive agents. In the screen design, such drugs functioned by enhancing base-excision DNA repair of oxidative DNA damage in the presence of mutant BRCA1, with minimal cytotoxicity. We identified at least one new agent that decreased malignant properties associated with tumorigenesis, including anchorage-independent growth and tumor progression. This work offers a preclinical proof-of-concept for a wholly new approach to chemoprevention in carriers of BRCA1 mutations as a strategy to reduce the prevalence of BRCA1-associated malignancy. Cancer Res; 74(21); 1–11. ©2014 AACR.

Cancers due to germline mutations in the BRCA1 gene tend to lack targets for approved chemoprevention agents. This study aimed at a targeted chemoprevention strategy for BRCA1-associated malignancies. Mutant BRCA1 limits the base-excision DNA repair activity that addresses oxidative DNA damage, the accumulation of which heightens one’s risk for cancer. Therefore, we conducted a high-throughput chemical screen to identify drug candidates that could attenuate the inhibitory effects of mutant BRCA1 on this repair activity, thereby describing a new class of DNA repair-activating chemopreventive agents. In the screen design, such drugs functioned by enhancing base-excision DNA repair of oxidative DNA damage in the presence of mutant BRCA1, with minimal cytotoxicity. We identified at least one new agent that decreased malignant properties associated with tumorigenesis, including anchorage-independent growth and tumor progression. This work offers a preclinical proof-of-concept for a wholly new approach to chemoprevention in carriers of BRCA1 mutations, as a strategy to reduce the prevalence of BRCA1-associated malignancy.