iBET, Instituto de Biologia Experimental e Tecnológica, Oeiras, Portugal.
Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal.
BMC Bioinformatics. 2020 Nov 17;21(1):529. doi: 10.1186/s12859-020-03854-2.
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 fibroblasts co-cultured in 3D within alginate capsules, for reconstruction of tumor microenvironment features.
In this work, an experimental-computational framework of antibody transport 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.
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.
在过去的几十年中,抗体彻底改变了癌症治疗方法。尽管它们已成功应用,但仍存在一些挑战需要克服,以提高疗效,例如抗体在肿瘤内的不均匀分布。肿瘤微环境的特征,如肿瘤和其他细胞类型的分布以及细胞外基质的组成,可能共同作用,阻碍抗体到达目标肿瘤细胞。为了理解这些相互作用,我们提出了一个结合体外和计算模型的框架。我们利用了我们小组先前开发的体外癌症模型,这些模型由肿瘤细胞和成纤维细胞在藻酸盐胶囊中 3D 共培养而成,用于重建肿瘤微环境特征。
在这项工作中,建立了一个在藻酸盐胶囊内抗体传输的实验计算框架,假设了一个纯粹的扩散传输,结合了一个指数饱和效应,模拟了细胞表面结合位点的饱和。我们的体外肿瘤微环境模型受到荧光抗体的挑战,并用光片荧光显微镜记录其传输。计算模型的扩散和饱和参数进行了调整,以再现实验抗体分布,均方根误差低于 5%。这个计算框架具有灵活性,可以模拟胶囊内肿瘤微环境元素(成纤维细胞、癌细胞和胶原纤维)的不同随机分布。随机分布算法可以根据实验模型中观察到的一般模式进行调整。
我们提出了一个用于跟踪和模拟抗体在肿瘤微环境中传输的计算和显微镜框架,补充了之前建立的体外模型平台。该框架为开发一种有价值的工具来研究肿瘤微环境的不同成分对抗体传输的影响铺平了道路。