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Proteinaceous Hydrogels for Bioengineering Advanced 3D Tumor Models

The establishment of tumor microenvironment using biomimetic in vitro models that recapitulate key tumor hallmarks including the tumor supporting extracellular matrix (ECM) is in high demand for accelerating the discovery and preclinical validation of more effective anticancer therapeutics. To date,...

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Detalles Bibliográficos
Autores principales: Blanco‐Fernandez, Barbara, Gaspar, Vítor M., Engel, Elisabeth, Mano, João F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887602/
https://www.ncbi.nlm.nih.gov/pubmed/33643799
http://dx.doi.org/10.1002/advs.202003129
Descripción
Sumario:The establishment of tumor microenvironment using biomimetic in vitro models that recapitulate key tumor hallmarks including the tumor supporting extracellular matrix (ECM) is in high demand for accelerating the discovery and preclinical validation of more effective anticancer therapeutics. To date, ECM‐mimetic hydrogels have been widely explored for 3D in vitro disease modeling owing to their bioactive properties that can be further adapted to the biochemical and biophysical properties of native tumors. Gathering on this momentum, herein the current landscape of intrinsically bioactive protein and peptide hydrogels that have been employed for 3D tumor modeling are discussed. Initially, the importance of recreating such microenvironment and the main considerations for generating ECM‐mimetic 3D hydrogel in vitro tumor models are showcased. A comprehensive discussion focusing protein, peptide, or hybrid ECM‐mimetic platforms employed for modeling cancer cells/stroma cross‐talk and for the preclinical evaluation of candidate anticancer therapies is also provided. Further development of tumor‐tunable, proteinaceous or peptide 3D microtesting platforms with microenvironment‐specific biophysical and biomolecular cues will contribute to better mimic the in vivo scenario, and improve the predictability of preclinical screening of generalized or personalized therapeutics.