A computational diffusion model to study antibody transport within reconstructed tumor microenvironments
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RESEARCH ARTICLE
Open Access
A computational diffusion model to study antibody transport within reconstructed tumor microenvironments Ana Luísa Cartaxo1,2, Jaime Almeida3,4, Emilio J. Gualda5, Maria Marsal5, Pablo Loza‑Alvarez5, Catarina Brito1,2 and Inês A. Isidro1,2*
*Correspondence: [email protected] 1 iBET, Instituto de Biologia Experimental e Tecnológica, Oeiras, Portugal Full list of author information is available at the end of the article
Abstract Background: Antibodies revolutionized cancer treatment over the past decades. Despite their successfully application, there are still challenges to overcome to improve efficacy, such as the heterogeneous distribution of antibodies within tumors. Tumor microenvironment features, such as the distribution of tumor and other cell types and the composition of the extracellular matrix may work together to hinder antibodies from reaching the target tumor cells. To understand these interactions, we propose a framework combining in vitro and in silico models. We took advantage of in vitro cancer models previously developed by our group, consisting of tumor cells and fibro‑ blasts co-cultured in 3D within alginate capsules, for reconstruction of tumor microen‑ vironment features. Results: In this work, an experimental-computational framework of antibody trans‑ port within alginate capsules was established, assuming a purely diffusive transport, combined with an exponential saturation effect that mimics the saturation of binding sites on the cell surface. Our tumor microenvironment in vitro models were challenged with a fluorescent antibody and its transport recorded using light sheet fluorescence microscopy. Diffusion and saturation parameters of the computational model were adjusted to reproduce the experimental antibody distribution, with root mean square error under 5%. This computational framework is flexible and can simulate different random distributions of tumor microenvironment elements (fibroblasts, cancer cells and collagen fibers) within the capsule. The random distribution algorithm can be tuned to follow the general patterns observed in the experimental models. Conclusions: We present a computational and microscopy framework to track and simulate antibody transport within the tumor microenvironment that complements the previously established in vitro models platform. This framework paves the way to the development of a valuable tool to study the influence of different components of the tumor microenvironment on antibody transport. Keywords: Antibody diffusion, Tumor microenvironment, 3D in vitro cancer models, Computational modelling, Light sheet fluorescence microscopy
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