Volumetric imaging of optically cleared and fluorescently labeled animal tissue (VIOLA) for quantifying the 3D biodistribution of nanoparticles at cellular resolution in tumor tissue.

Nanoparticle (NP) technology holds significant promise to mediate targeted drug delivery to specific organs in the body. Understanding the 3D biodistribution of NPs in heterogeneous environments such as the tumor tissue can provide crucial information on efficacy, safety and potential clinical outcomes. Here we present a novel end-to-end workflow, VIOLA, which makes use of tissue clearing methodology in conjunction with high resolution imaging and advanced 3D image processing to quantify the spatiotemporal 3D biodistribution of fluorescently labeled ACCURIN® NPs. Specifically, we investigate the spatiotemporal biodistribution of NPs in three different murine tumor models (CT26, EMT6, and KPC-GEM) of increasing complexity and translational relevance. We have developed new endpoints to characterize NP biodistribution at multiple length scales. Our observations reveal that the macroscale NP biodistribution is spatially heterogeneous and exhibits a gradient with relatively high accumulation at the tumor periphery that progressively decreases towards the tumor core in all the tumor models. Microscale analysis revealed that NP extravasation from blood vessels increases in a time dependent manner and plateaus at 72 h post injection. Volumetric analysis and pharmacokinetic modeling of NP biodistribution in the vicinity of the blood vessels revealed that the local NP density exhibits a distance dependent spatiotemporal biodistribution which provide insights into the dynamics of NP extravasation in the tumor tissue. Our data represents a comprehensive analysis of NP biodistribution at multiple length scales in different tumor models providing unique insights into their spatiotemporal dynamics. Specifically, our results show that NPs exhibit a dynamic equilibrium with macroscale heterogeneity combined with microscale homogeneity.

Roadmap on plasticity and epigenetics in cancer.

The role of plasticity and epigenetics in shaping cancer evolution and response to therapy has taken center stage with recent technological advances including single cell sequencing. This roadmap article is focused on state-of-the-art mathematical and experimental approaches to interrogate plasticity in cancer, and addresses the following themes and questions: is there a formal overarching framework that encompasses both non-genetic plasticity and mutation-driven somatic evolution? How do we measure and model the role of the microenvironment in influencing/controlling non-genetic plasticity? How can we experimentally study non-genetic plasticity? Which mathematical techniques are required or best suited? What are the clinical and practical applications and implications of these concepts?

A whole-body circulatory neutrophil model with application to predicting clinical neutropenia from in vitro studies.

A circulatory model of granulopoiesis and its regulation is presented that includes neutrophil trafficking in the lungs, liver, spleen, bone marrow, lymph nodes, and blood. In each organ, neutrophils undergo transendothelial migration from vascular to interstitial space, clearance due to apoptosis, and recycling via the lymphatic flow. The model includes cell cycling of progenitor cells in the bone marrow, granulocyte colony-stimulating factor (G-CSF) kinetics and its neutrophil regulatory action, as well as neutrophil margination in the blood. From previously reported studies, 111 In-labeled neutrophil kinetic data in the blood and sampled organs were used to estimate the organ trafficking parameters in the model. The model was further developed and evaluated using absolute neutrophil count (ANC), band cell, and segmented neutrophil time course data from healthy volunteers following four dose levels of pegfilgrastim (r2  = 0.77-0.99), along with ANC time course responses following filgrastim (r2  = 0.96). The baseline values of various cell types in bone marrow and blood, as well as G-CSF concentration in the blood, predicted by the model are consistent with available literature reports. After incorporating the mechanism of action of both paclitaxel and carboplatin, as determined from an in vitro bone marrow studies, the model reliably predicted the observed ANC time course following paclitaxel plus carboplatin observed in a phase I trial of 46 patients (r2  = 0.70). The circulatory neutrophil model may provide a mechanistic framework for predicting multi-organ neutrophil homeostasis and dynamics in response to therapeutic agents that target neutrophil dynamics and trafficking in different organs.

Structure-Based Drug Design and Synthesis of PI3Kα-Selective Inhibitor (PF-06843195).

The phosphoinositide 3-kinase (PI3K)/mammalian target of rapamycin (mTOR) signaling pathway is a frequently dysregulated pathway in human cancer, and PI3Kα is one of the most frequently mutated kinases in human cancer. A PI3Kα-selective inhibitor may provide the opportunity to spare patients the side effects associated with broader inhibition of the class I PI3K family. Here, we describe our efforts to discover a PI3Kα-selective inhibitor by applying structure-based drug design (SBDD) and computational analysis. A novel series of compounds, exemplified by 2,2-difluoroethyl (3S)-3-{[2'-amino-5-fluoro-2-(morpholin-4-yl)-4,5'-bipyrimidin-6-yl]amino}-3-(hydroxymethyl)pyrrolidine-1-carboxylate (1) (PF-06843195), with high PI3Kα potency and unique PI3K isoform and mTOR selectivity were discovered. We describe here the details of the design and synthesis program that lead to the discovery of 1.

Predicting Chemotherapy-Induced Neutropenia and Granulocyte Colony-Stimulating Factor Response Using Model-Based In Vitro to Clinical Translation.

The ability to predict the incidence of chemotherapy-induced neutropenia in early drug development can inform risk monitoring and mitigation strategies, as well as decisions on advancing compounds to clinical trials. In this report, a physiological model of granulopoiesis that incorporates the drug's mechanism of action on cell cycle proliferation of bone marrow progenitor cells was extended to include the action of the cytotoxic agents paclitaxel, carboplatin, doxorubicin, and gemcitabine. In vitro bone marrow studies were conducted with each compound, and results were used to determine the model's drug effect parameters. Population simulations were performed to predict the absolute neutrophil count (ANC) and incidence of neutropenia for each compound, which were compared to results reported in the literature. In addition, using the single agent in vitro study results, the model was able to predict ANC time course in response to paclitaxel plus carboplatin in combination, which compared favorably to the results reported in a phase 1 clinical trial of 46 patients (r2 = 0.70). Model simulations were used to compare the relative risk (RR) of neutropenia in patients with high baseline ANCs for five chemotherapeutic regimens: doxorubicin (RR = 0.59), paclitaxel plus carboplatin combination (RR = 0.079), carboplatin (RR = 0.047), paclitaxel (RR = 0.031), and gemcitabine (RR = 0.013). Finally, the model was applied to quantify the reduced incidence of neutropenia with coadministration of pegfilgrastim or filgrastim, for both paclitaxel and the combination of paclitaxel plus carboplatin. The model provides a framework for predicting clinical neutropenia using in vitro bone marrow studies of anticancer agents that may guide drug development decisions.

A Microfluidic Perfusion Platform for In Vitro Analysis of Drug Pharmacokinetic-Pharmacodynamic (PK-PD) Relationships.

Static in vitro cell culture studies cannot capture the dynamic concentration profiles of drugs, nutrients, and other factors that cells experience in physiological systems. This limits the confidence in the translational relevance of in vitro experiments and increases the reliance on empirical testing of exposure-response relationships and dose optimization in animal models during preclinical drug development, introducing additional challenges owing to species-specific differences in drug pharmacokinetics (PK) and pharmacodynamics (PD). Here, we describe the development of a microfluidic cell culture device that enables perfusion of cells under 2D or 3D culture conditions with temporally programmable concentration profiles. Proof-of-concept studies using doxorubicin and gemcitabine demonstrated the ability of the microfluidic PK-PD device to examine dose- and time-dependent effects of doxorubicin as well as schedule-dependent effects of doxorubicin and gemcitabine combination therapy on cell viability using both step-wise drug concentration profiles and species-specific (i.e., mouse, human) drug PK profiles. The results demonstrate the importance of including physiologically relevant dynamic drug exposure profiles during in vitro drug testing to more accurately mimic in vivo drug effects, thereby improving translatability across nonclinical studies and reducing the reliance on animal models during drug development.

A physiological model of granulopoiesis to predict clinical drug induced neutropenia from in vitro bone marrow studies: with application to a cell cycle inhibitor.

Neutropenia is one of the most common dose-limiting toxocities associated with anticancer drug therapy. The ability to predict the probability and severity of neutropenia based on in vitro studies of drugs in early drug development will aid in advancing safe and efficacious compounds to human testing. Toward this end, a physiological model of granulopoiesis and its regulation is presented that includes the bone marrow progenitor cell cycle, allowing for a mechanistic representation of the action of relevant anticancer drugs based on in vitro studies. Model development used data from previously reported tracer kinetic studies of granulocyte disposition in healthy humans to characterize the dynamics of neutrophil margination in the presence of endogenous granulocyte-colony stimulating factor (G-CSF). In addition, previously published data from healthy volunteers following pegfilgrastim and filgrastim were used to quantify the regulatory effects of support G-CSF therapies on granulopoiesis. The model was evaluated for the cell cycle inhibitor palbociclib, using an in vitro system of human bone marrow mononuclear cells to quantify the action of palbociclib on proliferating progenitor cells, including its inhibitory effect on G1 to S phase transition. The in vitro results were incorporated into the physiological model of granulopoiesis and used to predict the time course of absolute neutrophil count (ANC) and the incidence of neutropenia observed in three previously reported clinical trials of palbociclib. The model was able to predict grade 3 and 4 neutropenia due to palbociclib treatment with 86% accuracy based on in vitro data.

Assessment of near-infrared fluorophores to study the biodistribution and tumor targeting of an IL13 receptor α2 antibody by fluorescence molecular tomography.

Non-invasive imaging using radiolabels is a common technique used to study the biodistribution of biologics. Due to the limited shelf-life of radiolabels and the requirements of specialized labs, non-invasive optical imaging is an attractive alternative for preclinical studies. Previously, we demonstrated the utility of fluorescence molecular tomography (FMT) an optical imaging modality in evaluating the biodistribution of antibody-drug conjugates. As FMT is a relatively new technology, few fluorophores have been validated for in vivo imaging. The goal of this study was to characterize and determine the utility of near-infrared (NIR) fluorophores for biodistribution studies using interleukin-13 receptor subunit alpha-2 antibody (IL13Rα2-Ab). Eight fluorophores (ex/em: 630/800 nm) with an N-hydroxysuccinimide (NHS) linker were evaluated for Ab conjugation. The resulting antibody-fluorophore (Ab-F) conjugates were evaluated in vitro for degree of conjugation, stability and target-binding, followed by in vivo/ex vivo FMT imaging to determine biodistribution in a xenograft model. The Ab-F conjugates (except Ab-DyLight800) showed good in vitro stability and antigen binding. All Ab-F conjugates (except for Ab-BOD630) resulted in a quantifiable signal in vivo and had similar biodistribution profiles, with peak tumor accumulation between 6 and 24 h post-injection. In vivo/ex vivo FMT imaging showed 17-34% ID/g Ab uptake by the tumor at 96 h. Overall, this is the first study to characterize the biodistribution of an Ab using eight NIR fluorophores. Our results show that 3-dimensional optical imaging is a valuable technology to understand biodistribution and targeting, but a careful selection of the fluorophore for each Ab is warranted.

Found in Translation: Maximizing the Clinical Relevance of Nonclinical Oncology Studies.

Purpose: The translation of nonclinical oncology studies is a subject of continuous debate. We propose that translational oncology studies need to optimize both pharmacokinetic (drug exposure) and pharmacodynamic (xenograft model) aspects. While improvements in pharmacodynamic translatability can be obtained by choosing cell lines or patient-derived xenograft models closer to the clinical indication, significant ambiguity and variability exists when optimizing the pharmacokinetic translation of small molecule and biotherapeutic agents.Experimental Design and Results: In this work, we propose a pharmacokinetic-based strategy to select nonclinical doses for approved drug molecules. We define a clinically relevant dose (CRD) as the dosing regimen in mice that most closely approximates the relevant pharmacokinetic metric in humans. Such metrics include area under the time-concentration curve and maximal or minimal concentrations within the dosing interval. The methodology is applied to six drugs, including targeted agents and chemotherapeutics, small and large molecules (erlotinib, dasatinib, vismodegib, trastuzumab, irinotecan, and capecitabine). The resulting efficacy response at the CRD is compared with clinical responses.Conclusions: We conclude that nonclinical studies designed with the appropriate CRDs of approved drug molecules will maximize the translatability of efficacy results, which is critical when testing approved and investigational agents in combination. Clin Cancer Res; 23(4); 1080-90. ©2016 AACR.

A novel CXCR4 antagonist IgG1 antibody (PF-06747143) for the treatment of hematologic malignancies.

The chemokine receptor CXCR4 is highly expressed and associated with poor prognosis in multiple malignancies. Upon engagement by its ligand, CXCL12, CXCR4 triggers intracellular signaling pathways that control trafficking of cells to tissues where the ligand is expressed, such as the bone marrow (BM). In hematologic cancers, CXCR4-driven homing of malignant cells to the BM protective niche is a key mechanism driving disease and therapy resistance. We developed a humanized CXCR4 immunoglobulin G1 (IgG1) antibody (Ab), PF-06747143, which binds to CXCR4 and inhibits CXCL12-mediated signaling pathways, as well as cell migration. In in vivo preclinical studies, PF-06747143 monotherapy rapidly and transiently mobilized cells from the BM into the peripheral blood. In addition, PF-06747143 effectively induced tumor cell death via its Fc constant region-mediated effector function. This Fc-mediated cell killing mechanism not only enhanced antitumor efficacy, but also played a role in reducing the duration of cell mobilization, when compared with an IgG4 version of the Ab, which does not have Fc-effector function. PF-06747143 treatment showed strong antitumor effect in multiple hematologic tumor models including non-Hodgkin lymphoma (NHL), acute myeloid leukemia (AML), and multiple myeloma (MM). Importantly, PF-06747143 synergized with standard-of-care agents in a chemoresistant AML patient-derived xenograft model and in an MM model. These findings suggest that PF-06747143 is a potential best-in-class anti-CXCR4 antagonist for the treatment of hematologic malignancies, including in the resistant setting. PF-06747143 is currently in phase 1 clinical trial evaluation (registered at www.clinicaltrials.gov as #NCT02954653).

Metabolite and Microbiome Interplay in Cancer Immunotherapy.

The role of the host microbiome has come to the forefront as a potential modulator of cancer metabolism and could be a future target for precision medicine. A recent study revealed that in colon cancer, bacteria form polysaccharide matrices called biofilms at a high frequency in the proximal colon. Comprehensive untargeted and stable isotope-assisted metabolomic analysis revealed that the bacteria utilize polyamine metabolites produced from colon adenomas/carcinomas to build these protective biofilms and may contribute to inflammation and proliferation observed in colon cancer. This study highlighted the importance of finding the biological origin of a metabolite and assessing its metabolism and mechanism of action. This led to a better understanding of host and microbial interactions, thereby aiding therapeutic design for cancer. In this review, we will discuss methodologies for identifying the biological origin and roles of metabolites in cancer progression and discuss the interactions of the microbiome and metabolites in immunity and cancer treatment, focusing on the flourishing field of cancer immunotherapy. Cancer Res; 76(21); 6146-52. ©2016 AACR.

Biodistribution and Targeting of Anti-5T4 Antibody-Drug Conjugate Using Fluorescence Molecular Tomography.

Understanding a drug's whole-body biodistribution and tumor targeting can provide important information regarding efficacy, safety, and dosing parameters. Current methods to evaluate biodistribution include in vivo imaging technologies like positron electron tomography and single-photon emission computed tomography or ex vivo quantitation of drug concentrations in tissues using autoradiography and standard biochemical assays. These methods use radioactive compounds or are cumbersome and do not give whole-body information. Here, for the first time, we show the utility of fluorescence molecular tomography (FMT) imaging to determine the biodistribution and targeting of an antibody-drug conjugate (ADC). An anti-5T4-antibody (5T4-Ab) and 5T4-ADC were conjugated with a near-infrared (NIR) fluorophore VivoTag 680XL (VT680). Both conjugated compounds were stable as determined by SEC-HPLC and plasma stability studies. Flow cytometry and fluorescence microscopy studies showed that VT680-conjugated 5T4-ADC specifically bound 5T4-expressing cells in vitro and also exhibited a similar cytotoxicity profile as the unconjugated 5T4-ADC. In vivo biodistribution and tumor targeting in an H1975 subcutaneous xenograft model demonstrated no significant differences between accumulation of VT680-conjugated 5T4-Ab or 5T4-ADC in either normal tissues or tumor. In addition, quantitation of heart signal from FMT imaging showed good correlation with the plasma pharmacokinetic profile suggesting that it (heart FMT imaging) may be a surrogate for plasma drug clearance. These results demonstrate that conjugation of VT680 to 5T4-Ab or 5T4-ADC does not change the behavior of native biologic, and FMT imaging can be a useful tool to understand biodistribution and tumor-targeting kinetics of antibodies, ADCs, and other biologics. Mol Cancer Ther; 15(10); 2530-40. ©2016 AACR.

Translational modeling and simulation approaches for molecularly targeted small molecule anticancer agents from bench to bedside.

INTRODUCTION: Recent advances in molecular biology have enabled personalized cancer therapies with molecularly targeted agents (MTAs), which offer a promising future for cancer therapy. Dynamic modeling and simulation (M&S) is a powerful mathematical approach linking drug exposures to pharmacological responses, providing a quantitative assessment of in vivo drug potency. Accordingly, a growing emphasis is being placed upon M&S to quantitatively understand therapeutic exposure-response relationships of MTAs in nonclinical models. AREAS COVERED: An overview of M&S approaches for MTAs in nonclinical models is presented with discussion about mechanistic extrapolation of antitumor efficacy from bench to bedside. Emphasis is placed upon recent advances in M&S approaches linking drug exposures, biomarker responses (e.g. target modulation) and pharmacological outcomes (e.g. antitumor efficacy). EXPERT OPINION: For successful personalized cancer therapies with MTAs, it is critical to mechanistically and quantitatively understand their exposure-response relationships in nonclinical models, and to logically and properly apply such knowledge to the clinic. Particularly, M&S approaches to predict pharmacologically active concentrations of MTAs in patients based upon nonclinical data would be highly valuable in guiding the design and execution of clinical trials. Proactive approaches to understand their exposure-response relationships could substantially increase probability of achieving a positive proof-of-concept in the clinic.

Monitoring metabolic responses to chemotherapy in single cells and tumors using nanostructure-initiator mass spectrometry (NIMS) imaging.

BACKGROUND: Tissue imaging of treatment-induced metabolic changes is useful for optimizing cancer therapies, but commonly used methods require trade-offs between assay sensitivity and spatial resolution. Nanostructure-Initiator Mass Spectrometry imaging (NIMS) permits quantitative co-localization of drugs and treatment response biomarkers in cells and tissues with relatively high resolution. The present feasibility studies use NIMS to monitor phosphorylation of 3'-deoxy-3'-fluorothymidine (FLT) to FLT-MP in lymphoma cells and solid tumors as an indicator of drug exposure and pharmacodynamic responses. METHODS: NIMS analytical sensitivity and spatial resolution were examined in cultured Burkitt's lymphoma cells treated briefly with Rapamycin or FLT. Sample aliquots were dispersed on NIMS surfaces for single cell imaging and metabolic profiling, or extracted in parallel for LC-MS/MS analysis. Docetaxel-induced changes in FLT metabolism were also monitored in tissues and tissue extracts from mice bearing drug-sensitive tumor xenografts. To correct for variations in FLT disposition, the ratio of FLT-MP to FLT was used as a measure of TK1 thymidine kinase activity in NIMS images. TK1 and tumor-specific luciferase were measured in adjacent tissue sections using immuno-fluorescence microscopy. RESULTS: NIMS and LC-MS/MS yielded consistent results. FLT, FLT-MP, and Rapamycin were readily detected at the single cell level using NIMS. Rapid changes in endogenous metabolism were detected in drug-treated cells, and rapid accumulation of FLT-MP was seen in most, but not all imaged cells. FLT-MP accumulation in xenograft tumors was shown to be sensitive to Docetaxel treatment, and TK1 immunoreactivity co-localized with tumor-specific antigens in xenograft tumors, supporting a role for xenograft-derived TK1 activity in tumor FLT metabolism. CONCLUSIONS: NIMS is suitable for monitoring drug exposure and metabolite biotransformation with essentially single cell resolution, and provides new spatial and functional dimensions to studies of cancer metabolism without the need for radiotracers or tissue extraction. These findings should prove useful for in vitro and pre-clinical studies of cancer metabolism, and aid the optimization of metabolism-based cancer therapies and diagnostics.

The development of a fully-integrated immune response model (FIRM) simulator of the immune response through integration of multiple subset models.

BACKGROUND: The complexity and multiscale nature of the mammalian immune response provides an excellent test bed for the potential of mathematical modeling and simulation to facilitate mechanistic understanding. Historically, mathematical models of the immune response focused on subsets of the immune system and/or specific aspects of the response. Mathematical models have been developed for the humoral side of the immune response, or for the cellular side, or for cytokine kinetics, but rarely have they been proposed to encompass the overall system complexity. We propose here a framework for integration of subset models, based on a system biology approach. RESULTS: A dynamic simulator, the Fully-integrated Immune Response Model (FIRM), was built in a stepwise fashion by integrating published subset models and adding novel features. The approach used to build the model includes the formulation of the network of interacting species and the subsequent introduction of rate laws to describe each biological process. The resulting model represents a multi-organ structure, comprised of the target organ where the immune response takes place, circulating blood, lymphoid T, and lymphoid B tissue. The cell types accounted for include macrophages, a few T-cell lineages (cytotoxic, regulatory, helper 1, and helper 2), and B-cell activation to plasma cells. Four different cytokines were accounted for: IFN-γ, IL-4, IL-10 and IL-12. In addition, generic inflammatory signals are used to represent the kinetics of IL-1, IL-2, and TGF-ß. Cell recruitment, differentiation, replication, apoptosis and migration are described as appropriate for the different cell types. The model is a hybrid structure containing information from several mammalian species. The structure of the network was built to be physiologically and biochemically consistent. Rate laws for all the cellular fate processes, growth factor production rates and half-lives, together with antibody production rates and half-lives, are provided. The results demonstrate how this framework can be used to integrate mathematical models of the immune response from several published sources and describe qualitative predictions of global immune system response arising from the integrated, hybrid model. In addition, we show how the model can be expanded to include novel biological findings. Case studies were carried out to simulate TB infection, tumor rejection, response to a blood borne pathogen and the consequences of accounting for regulatory T-cells. CONCLUSIONS: The final result of this work is a postulated and increasingly comprehensive representation of the mammalian immune system, based on physiological knowledge and susceptible to further experimental testing and validation. We believe that the integrated nature of FIRM has the potential to simulate a range of responses under a variety of conditions, from modeling of immune responses after tuberculosis (TB) infection to tumor formation in tissues. FIRM also has the flexibility to be expanded to include both complex and novel immunological response features as our knowledge of the immune system advances.

Effective targeting of Hedgehog signaling in a medulloblastoma model with PF-5274857, a potent and selective Smoothened antagonist that penetrates the blood-brain barrier.

Inhibition of the Smoothened (Smo) represents a promising therapeutic strategy for treating malignant tumors that are dependent on the Hedgehog (Hh) signaling pathway. PF-5274857 is a novel Smo antagonist that specifically binds to Smo with a K(i) of 4.6 ± 1.1 nmol/L and completely blocks the transcriptional activity of the downstream gene Gli1 with an IC(50) of 2.7 ± 1.4 nmol/L in cells. This Smo antagonist showed robust antitumor activity in a mouse model of medulloblastoma with an in vivo IC(50) of 8.9 ± 2.6 nmol/L. The downregulation of Gli1 is closely linked to the tumor growth inhibition in patched(+/-) medulloblastoma mice. Mathematical analysis of the relationship between the drug's pharmacokinetics and Gli1 pharmacodynamics in patched(+/-) medulloblastoma tumor models yielded similar tumor and skin Gli1 IC(50) values, suggesting that skin can be used as a surrogate tissue for the measurement of tumor Gli1 levels. In addition, PF-5274857 was found to effectively penetrate the blood-brain barrier and inhibit Smo activity in the brain of primary medulloblastoma mice, resulting in improved animal survival rates. The brain permeability of PF-5274857 was also confirmed and quantified in nontumor-bearing preclinical species with an intact blood-brain barrier. PF-5274857 was orally available and metabolically stable in vivo. These findings suggest that PF-5274857 is a potentially attractive clinical candidate for the treatment of tumor types including brain tumors and brain metastasis driven by an activated Hh pathway.

Mixture model approach to tumor classification based on pharmacokinetic measures of tumor permeability.

PURPOSE: To categorize the disease severity of mammary tumors in an animal model through the application of a novel tumor permeability mixture model within a hierarchical modeling framework. MATERIALS AND METHODS: Thirty-six rats with mammary tumors of varying grade were imaged via dynamic contrast-enhanced (CE) MRI using albumin-(Gd-DTPA)30. Time-dependent contrast agent concentration curves for blood and tumor tissue were obtained and a mathematical model of microvascular blood-tissue exchange was developed under the hypothesis that endothelial integrity is disrupted in a manner proportional to the degree of malignancy, with benign tumors showing no disruption of the vasculature endothelium. This permeability model was incorporated into a statistical model for the benign and malignant tumor subgroups that enabled automatic subject classification. The structural and statistical models were implemented using the software Nonlinear Mixed Effects Modeling (NONMEM) to statistically separate subjects into the two subgroups. RESULTS: Individual tumor classifications (as benign or malignant) were evaluated against the Scarff-Bloom-Richardson microscopic scoring method as applied to the tumor histology of each subject. The model-based classification resulted in 90.9% sensitivity, 92.9% specificity, and 91.7% accuracy. CONCLUSION: Mixture model analysis provides a robust method for subject classification without user intervention and bias. Although the present results are promising, additional research is needed to further evaluate this technique for diagnostic purposes.

Biodistribution and pharmacokinetics of the alphavbeta3-selective tracer 18F-galacto-RGD in cancer patients.

UNLABELLED: (18)F-Galacto-RGD has been developed for PET of alpha(v)beta(3) integrin expression, a receptor involved in, for example, angiogenesis and metastasis. Our aim was to study the kinetics and biodistribution of (18)F-Galacto-RGD in cancer patients. METHODS: Nineteen patients with metastases of malignant melanoma (n = 7), sarcomas (n = 10), or osseous metastases (n = 2) were examined. After injection of 133-200 MBq (18)F-Galacto-RGD, 3 consecutive emission scans from the pelvis to the thorax or dynamic emission scans of the tumor over 60 min, followed by 1 static emission scan of the body, were acquired. Time-activity curves and standardized uptake values (SUVs) were derived by image region-of-interest analysis with image-based arterial input functions. Compartmental modeling was used to derive the distribution volume for muscle tissue and tumors. RESULTS: (18)F-Galacto-RGD showed rapid blood clearance and primarily renal excretion. SUVs in tumors ranged from 1.2 to 9.0. Tumor-to-blood and tumor-to-muscle ratios increased over time, with peak ratios of 3.1 +/- 2.0 and 7.7 +/- 4.3, respectively, at 72 min. The tumor kinetics were consistent with a 2-tissue compartment model with reversible specific binding. Distribution volume values were, on average, 4 times higher for tumor tissue (1.5 +/- 0.8) than those for muscle tissue (0.4 +/- 0.1). The data suggest that there was only minimal free and bound (specific or nonspecific) tracer in muscle tissue. CONCLUSION: (18)F-Galacto-RGD demonstrates a highly favorable biodistribution in humans with specific receptor binding. Most important, this study shows that (18)F-Galacto-RGD allows visualization of alpha(v)beta(3) expression in tumors with high contrast. Consequently, this tracer offers a new strategy for noninvasive monitoring of molecular processes and may supply helpful information for planning and controlling of therapeutic approaches targeting the alpha(v)beta(3) integrin.