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Every normal cell or tissue is embedded in a complex local environment called stroma, consisting of different cell types, a basal membrane, and blood vessels. As normal cells mutate and develop into cancer cells, their local environment also changes to allow cancer progression. The tumor microenvironment (TME) consists of a complex cellular matrix of stromal cells and the developing tumor. The cross-talk between cancer cells and surrounding stromal cells is critical to disrupt normal tissue...
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Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
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Related Experiment Video

Updated: Sep 3, 2025

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How to build a tumor: An industry perspective.

Julia Schueler1, Jeffrey Borenstein2, Ludoviko Buti3

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Innovative 3D in vitro systems have advanced disease research, but require improved predictivity and validity. This review guides selection of the best 3D models for specific scientific questions.

Keywords:
3D in vitro modelsOncology drug developmentTechnology landscape

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Area of Science:

  • Biomedical Engineering
  • Cell Biology
  • Drug Discovery

Background:

  • Over 15 years, numerous 3D in vitro systems have emerged, enabling isolated manipulation of cellular and molecular disease contributors.
  • These advanced models offer potential for identifying key factors in disease pathogenesis.

Purpose of the Study:

  • To review prominent 3D in vitro systems, focusing on their applications and translational relevance.
  • To provide an industry perspective on the drivers for adopting these advanced models.
  • To aid researchers in selecting appropriate 3D models by detailing their pros and cons.

Main Methods:

  • Literature review of innovative 3D in vitro systems.
  • Analysis of system applications, translational relevance, and industry adoption factors.
  • Comparative assessment of different 3D model platforms.

Main Results:

  • A wide array of 3D in vitro systems are available, offering enhanced control over experimental variables.
  • Key challenges remain in improving the predictivity and validity of current 3D models.
  • Selecting the optimal assay and readout combination is critical for addressing specific scientific inquiries.

Conclusions:

  • A thorough understanding of 3D in vitro platforms is essential for effective model selection.
  • Continued development is needed to enhance the predictive power and translational value of 3D models.
  • This review serves as a guide for researchers and industry professionals navigating the landscape of 3D in vitro systems.