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Article . 2019 . Peer-reviewed
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3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments

Authors: Fanben Meng; Carolyn M. Meyer; Daeha Joung; Daniel A. Vallera; Michael C. McAlpine; Angela Panoskaltsis‐Mortari;

3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments

Abstract

AbstractThe development of 3D in vitro models capable of recapitulating native tumor microenvironments could improve the translatability of potential anticancer drugs and treatments. Here, 3D bioprinting techniques are used to build tumor constructs via precise placement of living cells, functional biomaterials, and programmable release capsules. This enables the spatiotemporal control of signaling molecular gradients, thereby dynamically modulating cellular behaviors at a local level. Vascularized tumor models are created to mimic key steps of cancer dissemination (invasion, intravasation, and angiogenesis), based on guided migration of tumor cells and endothelial cells in the context of stromal cells and growth factors. The utility of the metastatic models for drug screening is demonstrated by evaluating the anticancer efficacy of immunotoxins. These 3D vascularized tumor tissues provide a proof‐of‐concept platform to i) fundamentally explore the molecular mechanisms of tumor progression and metastasis, and ii) preclinically identify therapeutic agents and screen anticancer drugs.

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Keywords

Tissue Engineering, Tissue Scaffolds, Biomimetics, Neoplasms, Printing, Three-Dimensional, Tumor Microenvironment, Humans, Drug Screening Assays, Antitumor

  • BIP!
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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    228
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 0.1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 0.1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
228
Top 0.1%
Top 10%
Top 0.1%
bronze
Related to Research communities
Cancer Research