Raquel Sevilla

Etanercept ameliorates inflammation and pain in a novel mono-arthritic multi-flare model of streptococcal cell wall induced arthritis

BackgroundThe impact of anti-TNF, corticosteroid and analgesic therapy on inflammation and pain was evaluated in a novel mono-arthritic multi-flare rat Streptococcal Cell Wall (SCW) model using Etanercept, Dexamethasone and Buprenorphine.MethodsMultiple flares of arthritis were induced with an intra-articular injection of SCW in the hind ankle on day 1, followed by intravenous challenges on days 21 and 42. Inflammation and pain were monitored in the hind paws. Cytokine profiling, cell phenotyping, bioluminescence imaging and histopathological evaluation were also performed.ResultsLocal injection of SCW caused a rapid onset of inflammation and pain in the injected ankle which resolved within 4 days (Flare 1). Intravenous injection 20 days after sensitization resulted in an increase in ankle diameter and pain, which partially resolved in 8 days (Flare 2). The subsequent intra-venous injection in the same animals 14 days after resulted in a more chronic disease with inflammation and pain persisting over a period of 10 days (Flare 3). In Flare 2, therapeutic administration of Dexamethasone inhibited paw swelling (95%; P<0.001) and pain (55%; P<0.05). Therapeutic administration of Buprenorphine inhibited pain (80%; P<0.001) without affecting paw swelling (0%). Prophylactic administration of Etanercept in Flare 2 inhibited paw swelling (≥60%; P<0.001) and pain by ≥30%. Expression of IL-1β, IL-6, MCP-1 and CINC was reduced by >50% (P<0.001). Treatment with Etanercept in Flare 3 inhibited paw swelling by 60% (P<0.001) and pain by 25%. Prior treatment with Etanercept in Flare 2 followed by re-administration in Flare 3 led to a complete loss in the efficacy of Etanercept. Systemic exposure of Etanercept corroborated with lack of efficacy. Dexamethasone inhibited inflammation and pain in both Flares 2 and 3 (P<0.001).ConclusionsWe established a novel multi-flare SCW arthritis model enabling drug intervention in different stages of disease. We show for the first time the evaluation of inflammation and pain simultaneously in this model. Etanercept and Dexamethasone inhibited inflammation, pain and proinflammatory cytokines in this model. Taken together, this model facilitates the assessment of anti-rheumatic agents targeting inflammation and pain in the multiple flare paradigm and offers a powerful tool for drug discovery.

Anti-inflammatory actions of Chemoattractant Receptor-homologous molecule expressed on Th2 by the antagonist MK-7246 in a novel rat model of Alternaria alternata elicited pulmonary inflammation

Alternaria alternata is a fungal allergen linked to the development of severe asthma in humans. In view of the clinical relationship between A. alternata and asthma, we sought to investigate the allergic activity of this antigen after direct application to the lungs of Brown Norway rats. Here we demonstrate that a single intratracheal instillation of A. alternata induces dose and time dependent eosinophil influx, edema and Type 2 helper cell cytokine production in the lungs of BN rats. We established the temporal profile of eosinophilic infiltration and cytokine production, such as Interleukin-5 and Interleukin-13, following A. alternata challenge. These responses were comparable to Ovalbumin induced models of asthma and resulted in peak inflammatory responses 48h following a single challenge, eliminating the need for multiple sensitizations and challenges. The initial perivascular and peribronchiolar inflammation preceded alveolar inflammation, progressing to a more sub-acute inflammatory response with notable epithelial cell hypertrophy. To limit the effects of an A. alternata inflammatory response, MK-7246 was utilized as it is an antagonist for Chemoattractant Receptor-homologous molecule expressed in Th2 cells. In a dose-dependent manner, MK-7246 decreased eosinophil influx and Th2 cytokine production following the A. alternata challenge. Furthermore, therapeutic administration of corticosteroids resulted in a dose-dependent decrease in eosinophil influx and Th2 cytokine production. Reproducible asthma-related outcomes and amenability to pharmacological intervention by mechanisms relevant to asthma demonstrate that an A. alternata induced pulmonary inflammation in BN rats is a valuable preclinical pharmacodynamic in vivo model for evaluating the pharmacological inhibitors of allergic pulmonary inflammation.

A Brain Penetrant Mutant IDH1 Inhibitor Provides In Vivo Survival Benefit

Mutations in IDH1 are highly prevalent in human glioma. First line treatment is radiotherapy, which many patients often forego to avoid treatment-associated morbidities. The high prevalence of IDH1 mutations in glioma highlights the need for brain-penetrant IDH1 mutant-selective inhibitors as an alternative therapeutic option. Here, we have explored the utility of such an inhibitor in IDH1 mutant patient-derived models to assess the potential therapeutic benefits associated with intracranial 2-HG inhibition. Treatment of mutant IDH1 cell line models led to a decrease in intracellular 2-HG levels both in vitro and in vivo. Interestingly, inhibition of 2-HG production had no effect on in vitro IDH1 mutant glioma cell proliferation. In contrast, IDH1 mutant-selective inhibitors provided considerable survival benefit in vivo. However, even with near complete inhibition of intratumoral 2-HG production, not all mutant glioma models responded to treatment. The results suggest that disruption of 2-HG production with brain-penetrant inhibitors in IDH1 mutant gliomas may have substantial patient benefit.

Abstract A23: Development of a novel preclinical model to delineate the role of tumor microenvironment on mechanism of action and efficacy of PD-1 checkpoint blockade

Background: The cellular environment in which the tumor exists, also known as tumor microenvironment, includes surrounding blood vessels, immune cells, fibroblasts, signaling molecules, and the extracellular matrix. This microenvironment can contribute to the growth and metastases of tumors, potentially influencing the efficacy of therapeutic agents. Thus, understanding the contribution of the microenvironment on tumorigenesis may enable us to investigate biology and kinetics between tumor and surrounding environment and improve target selection for standalone or combination therapies. Methods: To interrogate the role of the microenvironment we developed a tumor model in which the tumors can grow inside an air-pouch created in the dorsal part of the mouse. The air-pouch serves as the local microenvironment, which can be modulated by pro or anti-inflammatory stimuli to study the impact of local cells and cytokines on tumor growth as well as the efficacy of therapeutic agents. Results: Using luciferized mouse colon carcinoma (mc38-LUC2) syngeneic cells, we demonstrate that the kinetics of tumor growth within the air-pouch is similar to standard subcutaneously induced tumor models and was quantified via bioluminescence imaging. Additionally, further characterization of the tumor microenvironment was performed using MR and CT imaging, cytokine expression, and cell phenotyping. Furthermore, we also evaluated checkpoint inhibitor agent targeting the PD-1pathway to evaluate its effect on tumor growth and impact on cellular and cytokine microenvironment. Conclusions: Taken together, our novel model can facilitate innovative assessment of the mechanism of action of immunomodulatory agents across multiple oncological malignancies and evaluation of next generation therapeutics. Citation Format: Kalyan Chakravarthy, Raquel Sevilla, Michael Caniga, Weisheng Zhang, Anwar Murtaza, Lily Moy, Milenko Cicmil. Development of a novel preclinical model to delineate the role of tumor microenvironment on mechanism of action and efficacy of PD-1 checkpoint blockade. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2016 Oct 20-23; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2017;5(3 Suppl):Abstract nr A23.

Automated segmentation of knee and ankle regions of rats from CT images to quantify bone mineral density for monitoring treatments of rheumatoid arthritis

Bone mineral density (BMD) obtained from a CT image is an imaging biomarker used pre-clinically for characterizing the Rheumatoid arthritis (RA) phenotype. We use this biomarker in animal studies for evaluating disease progression and for testing various compounds. In the current setting, BMD measurements are obtained manually by selecting the regions of interest from three-dimensional (3-D) CT images of rat legs, which results in a laborious and low-throughput process. Combining image processing techniques, such as intensity thresholding and skeletonization, with mathematical techniques in curve fitting and curvature calculations, we developed an algorithm for quick, consistent, and automatic detection of joints in large CT data sets. The implemented algorithm has reduced analysis time for a study with 200 CT images from 10 days to 3 days and has improved the robust detection of the obtained regions of interest compared with manual segmentation. This algorithm has been used successfully in over 40 studies.

Automated 3D mouse lung segmentation from CT images for extracting quantitative tumor progression biomarkers

Genetically engineered mouse models of lung cancer are essential for preclinical evaluation of disease progression and treatments as well as in drug development. Micro-computed Tomography (microCT) is an imaging modality that is widely used in visualizing the anatomy of subjects in vivo and extracting quantitative and translatable biomarkers. This work demonstrates the use of uCT imaging and image segmentation techniques in large population phenotyping studies of transgenic mouse models of lung cancer. We studied 8 genotypes of transgenic mice with 99 subjects imaged at 4 time points. We developed (1) a high throughput image acquisition technique that acquires 60 subjects in 3 hours at an isotropic resolution of about 100 um, and (2) an automated segmentation algorithm to compute tumor and vasculature volume (TVV), a previously validated biomarker for lung cancer progression. TVV is computed as the difference between the whole lung and the functional lung (air space within lung) volumes. Previous work on automated lung segmentation focused on healthy lung or on segmentation of pulmonary nodules. We automatically compute TVV by determining a lung region of interest (ROI) by using the rib cage, the functional lung volume by thresholding within the lung ROI, and the whole lung volume by iteratively performing morphological hole-fill, bridge, and image close operations on the functional lung. We compare the automated results with that of manual analysis. Automated functional lung volume results were highly correlated to manual results (R2≥0.95) at all the time points. Whole lung volume was well-correlated to manual measurements (R2≥0.8 up to the 2nd time point), but required some manual correction at later time points when the tumors almost filled the lung. Overall this approach provided about 66% time saving compared to manual analysis. Our innovative workflow with high throughput acquisition and automated segmentation enabled efficient phenotyping studies to aid drug development.