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Mimicking Tumors: Toward More Predictive In Vitro Models for Peptide- and Protein-Conjugated Drugs

[Image: see text] Macromolecular drug candidates and nanoparticles are typically tested in 2D cancer cell culture models, which are often directly followed by in vivo animal studies. The majority of these drug candidates, however, fail in vivo. In contrast to classical small-molecule drugs, multiple...

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Detalles Bibliográficos
Autores principales: van den Brand, Dirk, Massuger, Leon F., Brock, Roland, Verdurmen, Wouter P. R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2017
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5355905/
https://www.ncbi.nlm.nih.gov/pubmed/28122451
http://dx.doi.org/10.1021/acs.bioconjchem.6b00699
Descripción
Sumario:[Image: see text] Macromolecular drug candidates and nanoparticles are typically tested in 2D cancer cell culture models, which are often directly followed by in vivo animal studies. The majority of these drug candidates, however, fail in vivo. In contrast to classical small-molecule drugs, multiple barriers exist for these larger molecules that two-dimensional approaches do not recapitulate. In order to provide better mechanistic insights into the parameters controlling success and failure and due to changing ethical perspectives on animal studies, there is a growing need for in vitro models with higher physiological relevance. This need is reflected by an increased interest in 3D tumor models, which during the past decade have evolved from relatively simple tumor cell aggregates to more complex models that incorporate additional tumor characteristics as well as patient-derived material. This review will address tissue culture models that implement critical features of the physiological tumor context such as 3D structure, extracellular matrix, interstitial flow, vascular extravasation, and the use of patient material. We will focus on specific examples, relating to peptide-and protein-conjugated drugs and other nanoparticles, and discuss the added value and limitations of the respective approaches.