Automated segmentation of lungs and lung tumors in mouse micro-CT scans

Here, we have developed an automated image processing algorithm for segmenting lungs and individual lung tumors in in vivo micro-computed tomography (micro-CT) scans of mouse models of non-small cell lung cancer and lung fibrosis. Over 3000 scans acquired across multiple studies were used to train/validate a 3D U-net lung segmentation model and a Support Vector Machine (SVM) classifier to segment individual lung tumors. The U-net lung segmentation algorithm can be used to estimate changes in soft tissue volume within lungs (primarily tumors and blood vessels), whereas the trained SVM is able to discriminate between tumors and blood vessels and identify individual tumors. The trained segmentation algorithms (1) significantly reduce time required for lung and tumor segmentation, (2) reduce bias and error associated with manual image segmentation, and (3) facilitate identification of individual lung tumors and objective assessment of changes in lung and individual tumor volumes under different experimental conditions.

Effect of molecular size on interstitial pharmacokinetics and tissue catabolism of antibodies

Advances in antibody engineering have enabled the construction of novel molecular formats in diverse shapes and sizes, providing new opportunities for biologic therapies and expanding the need to understand how various structural aspects affect their distribution properties. To assess the effect of antibody size on systemic pharmacokinetics (PK) and tissue distribution with or without neonatal Fc receptor (FcRn) binding, we evaluated a series of non-mouse-binding anti-glycoprotein D monoclonal antibody formats, including IgG [~150 kDa], one-armed IgG [~100 kDa], IgG-HAHQ (attenuated FcRn binding) [~150 kDa], F(ab')₂ [~100 kDa], and F(ab) [~50 kDa]. Tissue-specific concentration-time profiles were corrected for blood content based on vascular volumes and normalized based on interstitial volumes to allow estimation of interstitial concentrations and interstitial:serum concentration ratios. Blood correction demonstrated that the contribution of circulating antibody on total uptake was greatest at early time points and for highly vascularized tissues. Tissue interstitial PK largely mirrored serum exposure profiles. Similar interstitial:serum ratios were obtained for the two FcRn-binding molecules, IgG and one-armed IgG, which reached pseudo-steady-state kinetics in most tissues. For non-FcRn-binding molecules, interstitial:serum ratios changed over time, suggesting that these molecules did not reach steady-state kinetics during the study. Furthermore, concentration-time profiles of both intact and catabolized molecule were measured by a dual tracer approach, enabling quantification of tissue catabolism and demonstrating that catabolism levels were highest for IgG-HAHQ. Overall, these data sets provide insight into factors affecting preclinical distribution and may be useful in estimating interstitial concentrations and/or catabolism in human tissues.

Imaging Reveals Importance of Shape and Flexibility for Glomerular Filtration of Biologics

Advances in antibody engineering have enabled the construction of novel molecular formats in diverse shapes and sizes, providing new opportunities for cancer immunotherapeutic drug discovery while also revealing limitations in knowledge of structure-activity relationships. The current understanding of renal filtration originates largely from data reported for dextrans, IgG, albumin, and selected globular proteins. For a one-armed IgG-based T-cell imaging agent, we observed higher renal signal than typically observed for bivalent IgGs, prompting us to explore the factors governing renal filtration of biologics. We constructed a small representative library of IgG-like formats with varied shapes and hinge flexibilities falling broadly into two categories: branched molecules including bivalent IgG and (scFv)2Fc, and nonbranched molecules including one-armed IgG, one-armed IgG with stacked Fab, and one-armed IgG with a rigid IgA2 hinge. Transmission electron microscopy revealed Y-shaped structures for the branched molecules and pseudo-linear structures for the nonbranched molecules. Single-photon emission CT imaging, autoradiography, and tissue harvest studies demonstrated higher renal uptake and catabolism for nonbranched molecules relative to branched molecules. Among the nonbranched molecules, the one-armed IgG with rigid IgA2 hinge molecule demonstrated higher kidney uptake and decreased systemic exposure relative to molecules with a more flexible hinge. Our results show that differences in shape and hinge flexibility drive the increased glomerular filtration of one-armed relative to bivalent antibodies and highlight the practical advantages of using imaging to assess renal filtration properties. These findings are particularly relevant for T-cell-dependent bispecific molecules, many of which have nonstandard antibody structures.

Valency of HER2 targeting antibodies influences tumor cell internalization and penetration

T cell Dependent Bispecific antibodies (TDBs) have been a major advancement in the the treatment of cancer that allow for improved targeting and efficacy for large molecule therapeutics. TDBs are comprised of one arm targeting a surface antigen on a cancer cell and another targeting an engaging surface antigen on a cytotoxic T cell. In order to impart this function, the antibody must be in a bispecific format as opposed to the more conventional bivalent format. Through in vitro and in vivo studies, we sought to determine the impact of changing antibody valency on solid tumor distribution and catabolism. A bivalent anti-HER2 antibody exhibited higher catabolism than its full-length monovalent binding counterpart in vivo by both invasive tissue harvesting and non-invasive SPECT-CT imaging despite similar systemic exposures for the two molecules. In order to determine what molecular factors drove in vivo distribution and uptake, we developed a mechanistic model for binding and catabolism of monovalent and bivalent HER2 antibodies in KPL4 cells. This model suggests that observed differences in cellular uptake of monovalent and bivalent antibodies are caused by the change in apparent affinity conferred by avidity as well as differences in internalization and degradation rates of receptor bound antibodies. To our knowledge, this is the first study to directly compare the targeting abilities of monovalent and bivalent full-length antibodies. These findings may inform diverse antibody therapeutic modalities including T cell redirecting therapies and drug delivery strategies relying upon receptor internalization.

Mechanistic Modeling of Soluble Aβ Dynamics and Target Engagement in the Brain by Anti-Aβ mAbs in Alzheimer’s Disease

Background:

Anti-amyloid-β (Aβ) monoclonal antibodies (mAbs) are currently in development for treating Alzheimer’s disease.

Objectives:

To address the complexity of Aβ target engagement profiles, improve the understanding of crenezumab Pharmacokinetics (PK) and Aβ Pharmacodynamics (PD) in the brain, and facilitate comparison of anti-Aβ therapies with different binding characteristics.

Methods:

A mechanistic mathematical model was developed describing the distribution, elimination, and binding kinetics of anti-Aβ mAbs and Aβ (monomeric and oligomeric forms of Aβ1-40 and Aβ1-42) in the brain, Cerebrospinal Fluid (CSF), and plasma. Physiologically meaningful values were assigned to the model parameters based on the previous data, with remaining parameters fitted to clinical measurements of Aβ concentrations in CSF and plasma, and PK/PD data of patients undergoing anti-Aβ therapy. Aβ target engagement profiles were simulated using a Monte Carlo approach to explore the impact of biological uncertainty in the model parameters.

Results:

Model-based estimates of in vivo affinity of the antibody to monomeric Aβ were qualitatively consistent with the previous data. Simulations of Aβ target engagement profiles captured observed mean and variance of clinical PK/PD data.

Conclusion:

This model is useful for comparing target engagement profiles of different anti-Aβ therapies and demonstrates that 60 mg/kg crenezumab yields a significant increase in Aβ engagement compared with lower doses of solanezumab, supporting the selection of 60 mg/kg crenezumab for phase 3 studies. The model also provides evidence that the delivery of sufficient quantities of mAb to brain interstitial fluid is a limiting step with respect to the magnitude of soluble Aβ oligomer neutralization.

Effect of Modulating FcRn Binding on Direct and Pretargeted Tumor Uptake of Full-length Antibodies

Full-length antibodies lack ideal pharmacokinetic properties for rapid targeted imaging, prompting the pursuit of smaller peptides and fragments. Nevertheless, studying the disposition properties of antibody-based imaging agents can provide critical insight into the pharmacology of their therapeutic counterparts, particularly for those coupled with potent payloads. Here, we evaluate modulation of binding to the neonatal Fc receptor (FcRn) as a protein engineering-based pharmacologic strategy to minimize the overall blood pool background with directly labeled antibodies and undesirable systemic click reaction of radiolabeled tetrazine with circulating pretargeted trans-cyclooctene (TCO)-modified antibodies. Noninvasive SPECT imaging of mice bearing HER2-expressing xenografts was performed both directly (¹¹¹In-labeled antibody) and indirectly (pretargeted TCO-modified antibody followed by ¹¹¹In-labeled tetrazine). Pharmacokinetic modulation of antibodies was achieved by two distinct methods: Fc engineering to reduce binding affinity to FcRn, and delayed administration of an antibody that competes with binding to FcRn. Tumor imaging with directly labeled antibodies was feasible in the absence of FcRn binding, rapidly attaining high tumor-to-blood ratios, but accompanied by moderate liver and spleen uptake. Pretargeted imaging of tumors with non-FcRn-binding antibody was also feasible, but systemic click reaction still occurred, albeit at lower levels than with parental antibody. Our findings demonstrate that FcRn binding impairment of full-length IgG antibodies moderately lowers tumor accumulation of radioactivity, and shifts background activity from blood pool to liver and spleen. Furthermore, reduction of FcRn binding did not eliminate systemic click reaction, but yielded greater improvements in tumor-to-blood ratio when imaging with directly labeled antibodies than with pretargeting.

Biodistribution and efficacy of an anti-TENB2 antibody-drug conjugate in a patient-derived model of prostate cancer

TENB2, a transmembrane proteoglycan protein, is a promising target for antibody drug conjugate (ADC) therapy due to overexpression in human prostate tumors and rapid internalization. We previously characterized how predosing with parental anti-TENB2 monoclonal antibody (mAb) at 1 mg/kg in a patient-derived LuCap77 explant model with high (3+) TENB2 expression could (i) block target-mediated intestinal uptake of tracer (& 0.1 mg/kg) levels of radiolabeled anti-TENB2-monomethyl auristatin E ADC while preserving tumor uptake, and (ii) maintain efficacy relative to ADC alone. Here, we systematically revisit this strategy to evaluate the effects of predosing on tumor uptake and efficacy in LuCap96.1, a low TENB2-expressing (1+) patient-derived model that is more responsive to ADC therapy than LuCap77. Importantly, rather than using tracer (& 0.1 mg/kg) levels, radiolabeled ADC tumor uptake was assessed at 1 mg/kg – one of the doses evaluated in the tumor growth inhibition study – in an effort to bridge tissue distribution (PK) with efficacy (PD). Predosing with mAb up to 1 mg/kg had no effect on efficacy. These findings warrant further investigations to determine whether predosing prior to ADC therapy might improve therapeutic index by preventing ADC disposition and possible toxicological liabilities in antigen-expressing healthy tissues.

Tissue Physiology of Cynomolgus Monkeys: Cross-Species Comparison and Implications for Translational Pharmacology

We previously performed a comparative assessment of tissue-level vascular physiological parameters in mice and rats, two of the most commonly utilized species in translational drug development. The present work extends this effort to non-human primates by measuring tissue- and organ-level vascular volumes (V_v), interstitial volumes (V_i), and blood flow rates (Q) in cynomolgus monkeys. These measurements were accomplished by red blood cell labeling, extracellular marker infusion, and rubidium chloride bolus distribution, respectively, the same methods used in previous rodent measurements. In addition, whole-body blood volumes (BV) were determined across species. The results demonstrate that V_v, V_i, and Q, measured using our methods scale approximately by body weight across mouse, rat, and monkey in the tissues considered here, where allometric analysis allowed extrapolation to human parameters. Significant differences were observed between the values determined in this study and those reported in the literature, including V_v in muscle, brain, and skin and Q in muscle, adipose, heart, thymus, and spleen. The impact of these differences for selected tissues was evaluated via sensitivity analysis using a physiologically based pharmacokinetic model. The blood-brain barrier in monkeys was shown to be more impervious to an infused radioactive tracer, indium-111-pentetate, than in mice or rats. The body weight-normalized total BV measured in monkey agreed well with previously measured value in rats but was lower than that in mice. These findings have important implications for the common practice of scaling physiological parameters from rodents to primates in translational pharmacology.

Site-specific conjugation allows modulation of click reaction stoichiometry for pretargeted SPECT imaging

Antibody pretargeting is a promising strategy for improving molecular imaging, wherein the separation in time of antibody targeting and radiolabeling can lead to rapid attainment of high contrast, potentially increased sensitivity, and reduced patient radiation exposure. The inverse electron demand Diels-Alder ‘click’ reaction between trans-cyclooctene (TCO) conjugated antibodies and radiolabeled tetrazines presents an ideal platform for pretargeted imaging due to rapid reaction kinetics, bioorthogonality, and potential for optimization of both slow and fast clearing components. Herein, we evaluated a series of anti-human epidermal growth factor receptor 2 (HER2) pretargeting antibodies containing distinct molar ratios of site-specifically incorporated TCO. The effect of stoichiometry on tissue distribution was assessed for pretargeting TCO-modified antibodies (monitored by ¹²⁵I) and subsequent accumulation of an ¹¹¹In-labeled tetrazine in a therapeutically relevant HER2+tumor-bearing mouse model. Single photon emission computed tomography (SPECT) imaging was also employed to assess tumor imaging at various TCO-to-monoclonal antibody (mAb) ratios. Increasing TCO-to-mAb molar ratios correlated with increased in vivo click reaction efficiency evident by increased tumor distribution and systemic exposure of ¹¹¹In-labeled tetrazines. The pharmacokinetics of TCO-modified antibodies did not vary with stoichiometry. Pretargeted SPECT imaging of HER2-expressing tumors using ¹¹¹In-labeled tetrazine demonstrated robust click reaction with circulating antibody at ~2 hours and good tumor delineation for both the 2 and 6 TCO-to-mAb ratio variants at 24 hours, consistent with a limited cell-surface pool of pretargeted antibody and benefit from further distribution and internalization. To our knowledge, this represents the first reported systematic analysis of how pretargeted imaging is affected solely by variation in click reaction stoichiometry through site-specific conjugation chemistry.

A Preclinical Population Pharmacokinetic Model for Anti-CD20/CD3 T-Cell-Dependent Bispecific Antibodies

CD20 is a cell‐surface receptor expressed by healthy and neoplastic B cells and is a well‐established target for biologics used to treat B‐cell malignancies. Pharmacokinetic (PK) and pharmacodynamic (PD) data for the anti‐CD20/CD3 T‐cell‐dependent bispecific antibody BTCT4465A were collected in transgenic mouse and nonhuman primate (NHP) studies. Pronounced nonlinearity in drug elimination was observed in the murine studies, and time‐varying, nonlinear PK was observed in NHPs, where three empirical drug elimination terms were identified using a mixed‐effects modeling approach: i) a constant nonsaturable linear clearance term (7 mL/day/kg); ii) a rapidly decaying time‐varying, linear clearance term (t_½ = 1.6 h); and iii) a slowly decaying time‐varying, nonlinear clearance term (t_½ = 4.8 days). The two time‐varying drug elimination terms approximately track with time scales of B‐cell depletion and T‐cell migration/expansion within the central blood compartment. The mixed‐effects NHP model was scaled to human and prospective clinical simulations were generated.

Physiologically based pharmacokinetic models of small molecules and therapeutic antibodies: a mini-review on fundamental concepts and applications

The mechanisms of absorption, distribution, metabolism and elimination of small and large molecule therapeutics differ significantly from one another and can be explored within the framework of a physiologically based pharmacokinetic (PBPK) model. This paper briefly reviews fundamental approaches to PBPK modeling, in which drug kinetics within tissues and organs are explicitly represented using physiologically meaningful parameters. The differences in PBPK models applied to small/large molecule drugs are highlighted, thus elucidating differences in absorption, distribution and elimination properties between these two classes of drugs in a systematic manner. The absorption of small and large molecules differs with respect to their common extravascular routes of delivery (oral versus subcutaneous). The role of the lymphatic system in drug distribution, and the involvement of tissues as sites of elimination (through catabolism and target mediated drug disposition) are unique features of antibody distribution and elimination that differ from small molecules, which are commonly distributed into the tissues but are eliminated primarily by liver metabolism. Fundamental differences exist in the ability to predict human pharmacokinetics based upon preclinical data due to differing mechanisms governing small and large molecule disposition. These differences have influence on the evolving utilization of PBPK modeling in the discovery and development of small and large molecule therapeutics.

GPU-accelerated compartmental modeling analysis of DCE-MRI data from glioblastoma patients treated with bevacizumab

The compartment model analysis using medical imaging data is the well-established but extremely time consuming technique for quantifying the changes in microvascular physiology of targeted organs in clinical patients after antivascular therapies. In this paper, we present a first graphics processing unit-accelerated method for compartmental modeling of medical imaging data. Using this approach, we performed the analysis of dynamic contrast-enhanced magnetic resonance imaging data from bevacizumab-treated glioblastoma patients in less than one minute per slice without losing accuracy. This approach reduced the computation time by more than 120-fold comparing to a central processing unit-based method that performed the analogous analysis steps in serial and more than 17-fold comparing to the algorithm that optimized for central processing unit computation. The method developed in this study could be of significant utility in reducing the computational times required to assess tumor physiology from dynamic contrast-enhanced magnetic resonance imaging data in preclinical and clinical development of antivascular therapies and related fields.

Mixed-effects modeling of clinical DCE-MRI data: application to colorectal liver metastases treated with bevacizumab

PURPOSE

Most dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data are evaluated for individual patients with cohorts analyzed to detect significant changes from baseline values, repeating the process at each posttreatment timepoint. Our study aimed to develop a statistically valid model for the complete time course of DCE-MRI data in a patient cohort.

MATERIALS AND METHODS

Data from 10 patients with colorectal cancer liver metastases were analyzed, including two baseline scans and four post-bevacizumab scans. Apparent changes in tumor median K(trans) were adjusted for changes in observed enhancing tumor fraction (EnF) by multiplying K(trans) by EnF (KEnF). A mixed-effects model (MEM) was defined to describe the KEnF time course for all patients simultaneously by assuming a three-parameter indirect response model with model parameters lognormally distributed across patients.

RESULTS

The typical cohort time course showed a KEnF reduction to 59% of baseline at 24 hours, returning to 65% of baseline values by day 12. Interpatient variability of model parameters ranged from 11% to 307%.

CONCLUSION

The MEM approach has potential for comparing responses at a group level in clinical trials with different doses, schedules, or combination regimens. Furthermore, the KEnF biomarker successfully resolved confounds in interpreting K(trans) arising from therapy induced changes in the volume of enhancing tumor.

GPU-accelerated nonparametric kinetic analysis of DCE-MRI data from glioblastoma patients treated with bevacizumab

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is often used to examine vascular function in malignant tumors and noninvasively monitor drug efficacy of antivascular therapies in clinical studies. However, complex numerical methods used to derive tumor physiological properties from DCE-MRI images can be time-consuming and computationally challenging. Recent advancement of computing technology in graphics processing unit (GPU) makes it possible to build an energy-efficient and high-power parallel computing platform for solving complex numerical problems. This study develops the first reported fast GPU-based method for nonparametric kinetic analysis of DCE-MRI data using clinical scans of glioblastoma patients treated with bevacizumab (Avastin®). In the method, contrast agent concentration-time profiles in arterial blood and tumor tissue are smoothed using a robust kernel-based regression algorithm in order to remove artifacts due to patient motion and then deconvolved to produce the impulse response function (IRF). The area under the curve (AUC) and mean residence time (MRT) of the IRF are calculated using statistical moment analysis, and two tumor physiological properties that relate to vascular permeability, volume transfer constant between blood plasma and extravascular extracellular space (K(trans)) and fractional interstitial volume (ve) are estimated using the approximations AUC/MRT and AUC. The most significant feature in this method is the use of GPU-computing to analyze data from more than 60,000 voxels in each DCE-MRI image in parallel fashion. All analysis steps have been automated in a single program script that requires only blood and tumor data as the sole input. The GPU-accelerated method produces K(trans) and ve estimates that are comparable to results from previous studies but reduces computational time by more than 80-fold compared to a previously reported central processing unit-based nonparametric method. Furthermore, it is at least several orders of magnitudes faster than standard parametric methods that perform compartmental modeling. This finding indicates that the GPU-based method can significantly shorten the computational times required to assess tumor physiology from DCE-MRI data in preclinical and clinical development of antivascular therapies.

Quantification of antiangiogenic and antivascular drug activity by kinetic analysis of DCE-MRI data

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to quantify the response of tumors to vascular targeting agents. Tumor response is frequently assessed using mathematical models that describe the distribution of contrast agents over time as a function of fundamental characteristics of vascular physiology. Generally, mathematical models of biological systems are abstractions that attempt to retain fundamental physiologic characteristics, thereby allowing for multiple potential modeling approaches and structures. Various DCE-MRI modeling techniques are discussed in this article.

Effects of anti-VEGF on predicted antibody biodistribution: roles of vascular volume, interstitial volume, and blood flow

Background

The identification of clinically meaningful and predictive models of disposition kinetics for cancer therapeutics is an ongoing pursuit in drug development. In particular, the growing interest in preclinical evaluation of anti-angiogenic agents alone or in combination with other drugs requires a complete understanding of the associated physiological consequences.

Methodology/Principal Findings

Technescan™ PYP™, a clinically utilized radiopharmaceutical, was used to measure tissue vascular volumes in beige nude mice that were naïve or administered a single intravenous bolus dose of a murine anti-vascular endothelial growth factor (anti-VEGF) antibody (10 mg/kg) 24 h prior to assay. Anti-VEGF had no significant effect (p>0.05) on the fractional vascular volumes of any tissues studied; these findings were further supported by single photon emission computed tomographic imaging. In addition, apart from a borderline significant increase (p = 0.048) in mean hepatic blood flow, no significant anti-VEGF-induced differences were observed (p>0.05) in two additional physiological parameters, interstitial fluid volume and the organ blood flow rate, measured using indium-111-pentetate and rubidium-86 chloride, respectively. Areas under the concentration-time curves generated by a physiologically-based pharmacokinetic model changed substantially (>25%) in several tissues when model parameters describing compartmental volumes and blood flow rates were switched from literature to our experimentally derived values. However, negligible changes in predicted tissue exposure were observed when comparing simulations based on parameters measured in naïve versus anti-VEGF-administered mice.

Conclusions/Significance

These observations may foster an enhanced understanding of anti-VEGF effects in murine tissues and, in particular, may be useful in modeling antibody uptake alone or in combination with anti-VEGF.

Development and evaluation of a novel method for preclinical measurement of tissue vascular volume

Identification of clinically predictive models of disposition kinetics for antibody therapeutics is an ongoing pursuit in drug development. To encourage translation of drug candidates from early research to clinical trials, clinical diagnostic agents may be used to characterize antibody disposition in physiologically relevant preclinical models. TechneScan PYP was employed to measure tissue vascular volumes (V(v)) in healthy mice. Two methods of red blood cell (RBC) labeling were compared: a direct in vivo method that is analogous to a clinical blood pool imaging protocol, and an indirect method in which radiolabeled blood was transfused from donor mice into recipient mice. The indirect method gave higher precision in RBC labeling yields, lower V(v) values in most tissues, and lower (99m)Tc uptake in kidneys and bladder by single photon emission computed tomographic (SPECT) imaging relative to the direct method. Furthermore, the relative influence of each method on the calculated area under the first 7 days of the concentration-time curve (AUC(0-7)) of an IgG in nude mice was assessed using a physiologically based pharmacokinetic model. The model was sensitive to the source of V(v) values, whether obtained from the literature or measured by either method, when used to predict experimental AUC(0-7) values for radiolabeled trastuzumab in healthy murine tissues. In summary, a novel indirect method for preclinical determination of V(v) offered higher precision in RBC labeling efficiency and lower renal uptake of (99m)Tc than the direct method. In addition, these observations emphasize the importance of obtaining accurate physiological parameter values for modeling antibody uptake.

An automated method for nonparametric kinetic analysis of clinical DCE-MRI data: application to glioblastoma treated with bevacizumab

Here, we describe an automated nonparametric method for evaluating gadolinium-diethylene triamine pentaacetic acid (Gd-DTPA) kinetics, based on dynamic contrast-enhanced-MRI scans of glioblastoma patients taken before and after treatment with bevacizumab; no specific model or equation structure is assumed or used. Tumor and venous blood concentration-time profiles are smoothed, using a robust algorithm that removes artifacts due to patient motion, and then deconvolved, yielding an impulse response function. In addition to smoothing, robustness of the deconvolution operation is assured by excluding data that occur prior to the plasma peak; an exhaustive analysis was performed to demonstrate that exclusion of the prepeak plasma data does not significantly affect results. All analysis steps are executed by a single R script that requires blood and tumor curves as the sole input. Statistical moment analysis of the Impulse response function yields the area under the curve (AUC) and mean residence time (MRT). Comparison of deconvolution results to fitted Tofts model parameters suggests that AUCMRT and AUC of the Impulse response function closely approximate fractional clearance from plasma to tissue (K(trans)) and fractional interstitial volume (v(e)). Intervisit variability is shown to be comparable when using the deconvolution method (11% [AUCMRT] and 13%[AUC]) compared to the Tofts model (14%[K(trans)] and 24%[v(e)]). AUC and AUCMRT both exhibit a statistically significant decrease (P < 0.005) 1 day after administration of bevacizumab.

Derivation of a compartmental model for quantifying 64Cu-DOTA-RGD kinetics in tumor-bearing mice

Radiolabeled arginine-glycine-aspartate (RGD) peptides are increasingly used in preclinical and clinical studies to assess the expression and function of the alphavbeta3 integrin, a cellular adhesion molecule involved in angiogenesis and tumor metastasis formation. To better understand the PET signal obtained with radiolabeled RGD peptides, we have constructed a compartmental model that can describe the time-activity curves in tumors after an intravenous injection.

METHODS

We analyzed 60-min dynamic PET scans obtained with 64Cu-1,4,7,10-tetraazacyclododecane-N,N',N'',N'''-tetraacetic acid (DOTA)-RGD in 20 tumor-bearing severe combined immunodeficient (SCID) mice after a bolus dose (18,500 kBq [500 microCi]), using variations of the standard 2-compartment (4k) tissue model augmented with a compartment for irreversible tracer internalization. alphavbeta3 binding sites were blocked in 5 studies with a coinjection of cold peptide. In addition, 20 h after injection, static PET was performed on 9 of 20 mice. We fitted 2k (k3=k4=0), 3k (k4=0), 4k, and 4kc (k4=constant) models to the PET data and used several criteria to determine the best model structure for describing 64Cu-DOTA-RGD kinetics in mice. Akaike information criteria (AIC), calculated from model fits and the ability of each model to predict tumor concentration 20 h after tracer injection, were considered.

RESULTS

The 4kc model has the best profile in terms of AIC values and predictive ability, and a constant k4 is further supported by Logan-Patlak analysis and results from iterative Bayesian parameter estimation. The internalization compartment allows quantification of the putative tracer internalization rate for each study, which is estimated here to be approximately an order of magnitude less than k3 and thus does not confound the apparent specific binding of the tracer to the tumor integrin during the first 60 min of the scan. Analysis of specific (S) and nonspecific or nondisplaceable (ND) binding using fitted parameter values showed that the 4kc model provided expected results when comparing alphavbeta3 blocked and nonblocked studies. That is, specific volume of distribution, [VS=(K1k3)/(k2k4)], is much higher than is nondisplaceable volume of distribution, [VND=(K1/k2)], in nonblocking studies (2.2+/-0.6 vs. 0.85+/-0.14); VS and VND are about the same in the blocking studies (0.46+/-1.6 vs. 0.56+/-0.09). Also, the ratio of static tumor and plasma measurements at 60 and 10 min [CT(60)/CP(10)] is highly correlated (RS=0.92) to tumor VS.

CONCLUSION

We have developed and tested a compartmental model for use with the 64Cu-DOTA-RGD PET tracer and demonstrated its potential as a tool for analysis and design of preclinical and clinical imaging studies.

Evaluation of [(18)F]gefitinib as a molecular imaging probe for the assessment of the epidermal growth factor receptor status in malignant tumors

PURPOSE

Gefitinib, an inhibitor of the epidermal growth factor receptor-tyrosine kinase (EGFR-TK), has shown potent effects in a subset of patients carrying specific EGFR-TK mutations in advanced non-small-cell lung cancer. In this study, we asked whether PET with [(18)F]gefitinib may be used to study noninvasively the pharmacokinetics of gefitinib in vivo and to image the EGFR status of cancer cells.

MATERIALS AND METHODS

Synthesis of [(18)F]gefitinib has been previously described. The biodistribution and metabolic stability of [(18)F]gefitinib was assessed in mice and vervet monkeys for up to 2 h post injection by both micropositron emission tomography (PET)/computed tomography (CT) scans and postmortem ex vivo tissue harvesting. Uptake levels of radiolabeled gefitinib in EGFR-expressing human cancer cell lines with various levels of EGFR expression or mutation status were evaluated both in vivo and in vitro.

RESULTS

MicroPET/CT scans in two species demonstrated a rapid and predominantly hepatobiliary clearance of [(18)F]gefitinib in vivo. However, uptake levels of radiolabeled gefitinib, both in vivo and in vitro, did not correlate with EGFR expression levels or functional status. This unexpected observation was due to high nonspecific, nonsaturable cellular uptake of gefitinib.

CONCLUSION

The biodistribution of the drug analogue [(18)F]gefitinib suggests that it may be used to assess noninvasively the pharmacokinetics of gefitinib in patients by PET imaging. This is of clinical relevance, as insufficient intratumoral drug concentrations are considered to be a factor for resistance to gefitinib therapy. However, the highly nonspecific cellular binding of [(18)F]gefitinib may preclude the use of this imaging probe for noninvasive assessment of EGFR receptor status in patients.

Estimation of the 18F-FDG input function in mice by use of dynamic small-animal PET and minimal blood sample data

Derivation of the plasma time-activity curve in murine small-animal PET studies is a challenging task when tracers that are sequestered by the myocardium are used, because plasma time-activity curve estimation usually involves drawing a region of interest within the area of the reconstructed image that corresponds to the left ventricle (LV) of the heart. The small size of the LV relative to the resolution of the small-animal PET system, coupled with spillover effects from adjacent myocardial pixels, makes this method reliable only for the earliest frames of the scan. We sought to develop a method for plasma time-activity curve estimation based on a model of tracer kinetics in blood, muscle, and liver.

METHODS

Sixteen C57BL/6 mice were injected with (18)F-FDG, and approximately 15 serial blood samples were taken from the femoral artery via a surgically inserted catheter during 60-min small-animal PET scans. Image data were reconstructed by use of filtered backprojection with CT-based attenuation correction. We constructed a 5-compartment model designed to predict the plasma time-activity curve of (18)F-FDG by use of data from a minimum of 2 blood samples and the dynamic small-animal PET scan. The plasma time-activity curve (TACp) was assumed to have 4 exponential components (TAC(P)=A(1)e(lambda(1)t)+A(2)e(lambda(2)t)+A(3)e(lambda(3)t)-(A(1)+A(2)+A(3))e(lambda(4)t)) based on the serial blood samples. Using Bayesian constraints, we fitted 2-compartment submodels of muscle and liver to small-animal PET data for these organs and simultaneously fitted the input (forcing) function to early small-animal PET LV data and 2 blood samples (approximately 10 min and approximately 1 h).

RESULTS

The area under the estimated plasma time-activity curve had an overall Spearman correlation of 0.99 when compared with the area under the gold standard plasma time-activity curve calculated from multiple blood samples. Calculated organ uptake rates (Patlak K(i)) based on the predicted plasma time-activity curve had a correlation of approximately 0.99 for liver, muscle, myocardium, and brain when compared with those based on the gold standard plasma time-activity curve. The model was also able to accurately predict the plasma time-activity curve under experimental conditions that resulted in different rates of clearance of the tracer from blood.

CONCLUSION

We have developed a robust method for accurately estimating the plasma time-activity curve of (18)F-FDG by use of dynamic small-animal PET data and 2 blood samples.

A two-tiered physiologically based model for dually labeled single-chain Fv-Fc antibody fragments

Monoclonal antibodies (mAb) are being used at an increasing rate in the treatment of cancer, with current efforts focused on developing engineered antibodies that exhibit optimal biodistribution profiles for imaging and/or radioimmunotherapy. We recently developed the single-chain Fv-Fc (scFv-Fc) mAb, which consists of a single-chain antibody Fv fragment (light-chain and heavy-chain variable domains) coupled to the IgG1 Fc region. Point mutations that attenuate binding affinity to FcRn were introduced into the Fc region of the wild-type scFv-Fc mAb, resulting in several new antibodies, each with a different half-life. Here, we describe the construction of a two-tiered physiologically based pharmacokinetic model capable of simulating the apparent biodistribution of both (111)In- and (125)I-labeled scFv-Fc mAbs, where (111)In-labeled metabolites from degraded (111)In-labeled mAbs tend to become trapped within the lysosomal compartment, whereas free (125)I from degraded (125)I-labeled mAbs is quickly eliminated via the urinary pathway. The different concentration-time profiles of (111)In- and (125)I-labeled mAbs permits estimation of the degradation capacity of each organ and elucidates the dependence of cumulative degradation in liver, muscle, and skin on FcRn affinity and tumor mass. Liver is estimated to account for approximately 50% of all degraded mAb when tumor is small (approximately 0.1 g) and drops to about 35% when tumor mass is larger (approximately 0.3 g). mAb degradation in residual carcass (primarily skin and muscle) decreases from approximately 45% to 16% as FcRn affinity of the three mAb variants under consideration increases. In addition, elimination of a small amount of mAb in the kidneys is shown to be required for a successful fit of model to data.

A predictive model of therapeutic monoclonal antibody dynamics and regulation by the neonatal Fc receptor (FcRn)

We constructed a novel physiologically-based pharmacokinetic (PBPK) model for predicting interactions between the neonatal Fc receptor (FcRn) and anti-carcinoembryonic antigen (CEA) monoclonal antibodies (mAbs) with varying affinity for FcRn. Our new model, an integration and extension of several previously published models, includes aspects of mAb-FcRn dynamics within intracellular compartments not represented in previous PBPK models. We added mechanistic structure that details internalization of class G immunoglobulins by endothelial cells, subsequent FcRn binding, recycling into plasma of FcRn-bound IgG and degradation of free endosomal IgG. Degradation in liver is explicitly represented along with the FcRn submodel in skin and muscle. A variable tumor mass submodel is also included, used to estimate the growth of an avascular, necrotic tumor core, providing a more realistic picture of mAb uptake by tumor. We fitted the new multiscale model to published anti-CEA mAb biodistribution data, i.e. concentration-time profiles in tumor and various healthy tissues in mice, providing new estimates of mAb-FcRn related kinetic parameters. The model was further validated by successful prediction of F(ab')2 mAb fragment biodistribution, providing additional evidence of its potential value in optimizing intact mAb and mAb fragment dosing for clinical imaging and immunotherapy applications.

A phosphorylation site in Bruton's tyrosine kinase selectively regulates B cell calcium signaling efficiency by altering phospholipase C-gamma activation

Loss of function of Bruton's tyrosine kinase (Btk) causes X-linked agammaglobulinemia (XLA) in humans and X-linked immunodeficiency in mice (xid). By using MS analysis and phosphopeptide-specific antibodies, we identified a tyrosine phosphorylation site (Y617) near the carboxyl terminus of the Btk domain from Btk expressed in 293T as well as DT-40 cells. Y617 is conserved in all Tec family kinases except murine Tec. Replacement of Y617 with a negatively charged glutamic acid (E) suppressed Btk-mediated phospholipase Cgamma2 activation and calcium response in DT-40 cells, whereas Akt activation was not affected. The Btk Y617E mutant could partially restore conventional B cell development and proliferation in Btk(-)/Tec(-) mice but failed to rescue CD5(+) B-1 cell development and the TI-II immune response to 2,4,6,-trinitrophenyl-Ficoll. These data suggest that Y617 phosphorylation or a negative charge at this site may down-regulate the function of Btk by selectively suppressing the B cell calcium signaling pathway.

Phosphoinositide 3-kinase and Bruton's tyrosine kinase regulate overlapping sets of genes in B lymphocytes

Bruton's tyrosine kinase (Btk) acts downstream of phosphoinositide 3-kinase (PI3K) in a pathway required for B cell receptor (BCR)-dependent proliferation. We used DNA microarrays to determine what fraction of genes this pathway influences and to investigate whether PI3K and Btk mediate distinct gene regulation events. As complete loss-of-function mutations in PI3K and Btk alter B cell subpopulations and may cause compensatory changes in gene expression, we used B cells with partial loss of function in either PI3K or Btk. Only about 5% of the BCR-dependent gene expression changes were significantly affected by reduced PI3K or Btk. The results indicate that PI3K and Btk share target genes, and that PI3K influences additional genes independently of Btk. These data are consistent with PI3K acting through Btk and other effectors to regulate expression of a critical subset of BCR target genes that determine effective entry into the cell cycle.