Peter J. O’Brien

In vitro cytotoxicity assessment.

The most frequent reason cited for withdrawal of an approved drug is toxicity, yet no simple solution exists to adequately predict such adverse effects. Compound prioritization and optimization during in vitro screening cascades need to be based on confidence, not only in efficacy and bioavailability, but also in safety. A wider number and diversity of potential molecular and cellular effects of compound interactions might affect safety than might affect efficacy or bioavailability. Accordingly, cytotoxicity assessment is less specific, more multiparametric, and extrapolatable with less certainty, unless there are specific safety signals indicated by the chemical structure or by precedents. Cytotoxicity assessments have been limited by their inability to measure multiple, mechanistic parameters that capture a wide spectrum of potential cytopathological changes. Assays with multiple parameters for key, multiple, and different features, such as in high content screening (HCS), are more predictive because they cover a wider spectrum of effects. Assays need to be applied to a large set of marketed drugs that produce toxicity by numerous and different mechanisms for assessment of correlation with human toxicity. This will enable determination of the concordance between in vitro and in vivo results. Multiparametric, live cell, prelethal cytotoxic HCS assays for assessing the potential of compounds for causing human toxicity address some of the limitations of traditional in vitro methods. Assays of this class were used to screen a library of drugs with varying degrees of toxicity and it was found that the sensitivity of the assays was 87%, whereas assay specificity was more than 90%, thereby minimizing false positives.

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

BackgroundThe 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.ResultsA 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-β. 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.ConclusionsThe 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.

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

BackgroundTissue 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.MethodsNIMS 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.ResultsNIMS 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.ConclusionsNIMS 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.

Development and validation of an alpha fetoprotein immunoassay using Gyros technology.

Circulating alpha fetoprotein (AFP) is a diagnostic and prognostic biomarker for hepatocellular carcinoma (HCC) with potential utility as a pharmacodynamic endpoint in rodent tumor models. This application is limited, however, by low sample volumes, highlighting the need for sensitive, sample-sparing biomarker assay methods. In order to improve the utility of AFP as an oncology biomarker, we developed a method for AFP using the Gyrolab™, an automated microimmunoassay platform. Commercially available antibodies were screened to identify optimal combinations that were then used in a multi-factorial design of experiments (DOE) to optimize reaction conditions. Analytical validation included assessments of accuracy and precision (A&P), and dilutional linearity/hook effect, as well as reagent and sample stability. The method is reliable, with total error, a measure of accuracy and precision, less than 30% for all concentrations tested. AFP concentrations were measurable in diseased mice and undetectable in normal mice. Therefore, this novel, low volume AFP immunoassay is suitable for pre-clinical drug development, where its miniaturized format facilitates serial sampling in rodent models of cancer.

Factor XIa-specific IgG and a reversal agent to probe factor XI function in thrombosis and hemostasis.

A noneffector, active site–dependent human IgG1 specific to factor XIa inhibits thrombus formation in two animal models at clinically relevant doses without a detectable effect on hemostasis. To clot or not: Anticoagulation without bleeding Current drugs designed to prevent blood clots, heart attack, or stroke also increase the risk of hazardous bleeding. Toward testing whether selective block of one branch of the coagulation cascade might inhibit clotting without causing bleeding, David et al. developed an antibody that occupies and blocks the active site of a critical protein called FXIa. This antibody inhibited clotting of human blood and prevented blood vessel block in animal models but did not cause bleeding. So that the antibody can be used safely in people, the authors also developed a second antibody that can reverse the action of the first. Thrombosis is a major cause of morbidity and mortality. Current antithrombotic drugs are not ideal in that they must balance prevention of thrombosis against bleeding risk. Inhibition of coagulation factor XI (FXI) may offer an improvement over existing antithrombotic strategies by preventing some forms of thrombosis with lower bleeding risk. To permit exploration of this hypothesis in humans, we generated and characterized a series of human immunoglobulin Gs (IgGs) that blocked FXIa active-site function but did not bind FXI zymogen or other coagulation proteases. The most potent of these IgGs, C24 and DEF, inhibited clotting in whole human blood and prevented FeCl3-induced carotid artery occlusion in FXI-deficient mice reconstituted with human FXI and in thread-induced venous thrombosis in rabbits at clinically relevant doses. At doses substantially higher than those required for inhibition of intravascular thrombus formation in these models, DEF did not increase cuticle bleeding in rabbits or cause spontaneous bleeding in macaques over a 2-week study. Anticipating the desirability of a reversal agent, we also generated a human IgG that rapidly reversed DEF activity ex vivo in human plasma and in vivo in rabbits. Thus, an active site–directed FXIa-specific antibody can block thrombosis in animal models and, together with the reversal agent, may facilitate exploration of the roles of FXIa in human disease.

Luciferase does not Alter Metabolism in Cancer Cells.

Luciferase transfected cell lines are used extensively for cancer models, revealing valuable biological information about disease mechanisms. However, these genetically encoded reporters, while useful for monitoring tumor response in cancer models, can impact cell metabolism. Indeed firefly luciferase and fatty acyl-CoA synthetases differ by a single amino acid, raising the possibility that luciferase activity might alter metabolism and introduce experimental artifacts. Therefore knowledge of the metabolic response to luciferase transfection is of significant importance, especially given the thousands of research studies using luciferase as an in vivo bioluminescence imaging reporter. Untargeted metabolomics experiments were performed to examine three different types of lymphoblastic leukemia cell lines (Ramos, Raji and SUP-T1) commonly used in cancer research, each were analyzed with and without vector transduction. The Raji model was also tested under perturbed starvation conditions to examine potential luciferase-mediated stress responses. The results showed that no significant metabolic differences were observed between parental and luciferase transduced cells for each cell line, and that luciferase overexpression does not alter cell metabolism under basal or perturbed conditions.

New Technologies for Cellular Analysis

Cytometric technologies have been indispensable for understanding biological and pathological processes, and are increasingly used to provide critical information on safety and efficacy in drug development. Highly sophisticated multiparametric cytometry methods are now available to measure treatment-induced changes in the phenotypes and functions of individual cells in heterogeneous populations. Numerous phenotypic and functional cytometry assays have been validated for pharmacodynamic studies in clinical drug trials, and that number is likely to expand as new analytical technologies become available. This chapter will discuss three new cytometric technologies that will likely impact clinical drug development in the near future: Imaging cytometry on a chip; Imaging flow cytometry; and Mass cytometry. Each of these platforms is well-suited to specific aspects of cellular analysis, and combines new technologies with tried and true cytometry methods.