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Related Experiment Video

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Assessing chemotherapeutic effectiveness using a paper-based tumor model.

Matthew W Boyce1, Gabriel J LaBonia2, Amanda B Hummon2

  • 1Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

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|July 14, 2017
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Summary
This summary is machine-generated.

Paper-based cultures (PBCs) mimic tumor environments to better screen cancer drugs. These 3D models reveal how oxygen gradients affect drug sensitivity, improving therapeutic predictions.

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Area of Science:

  • Biomedical Engineering
  • Cancer Research
  • Drug Discovery

Background:

  • Traditional 2D cell cultures have limited predictive power for cancer chemotherapeutics.
  • Tumor microenvironments are complex 3D structures that promote chemoresistance.
  • Existing models fail to replicate diffusion-limited conditions found in poorly vascularized tumors.

Purpose of the Study:

  • To develop and characterize paper-based cultures (PBCs) for assessing chemotherapeutic effectiveness.
  • To engineer 3D, diffusion-limited environments that mimic solid tumors.
  • To evaluate the impact of chemical gradients on drug sensitivity.

Main Methods:

  • Assembled cell-laden paper scaffolds into thick, tissue-like structures.
  • Created monotonic chemical gradients across stacked scaffolds.
  • Utilized fluorescence imaging to analyze cell viability and proliferation.
  • Adjusted cell density to modulate oxygen gradients and assess SN-38 sensitivity.

Main Results:

  • Viable and proliferative cells concentrated in nutrient-rich scaffold regions.
  • Oxygen gradients significantly influenced cellular sensitivity to SN-38.
  • Spatiotemporal oxygen gradient evolution correlated with cellular chemosensitivity.
  • PBCs demonstrated distinct chemical environments within scaffolds.

Conclusions:

  • Paper-based cultures (PBCs) effectively model 3D, diffusion-limited tumor environments.
  • PBCs can predict chemotherapeutic effectiveness under varying chemical conditions.
  • This model enhances the assessment of drug response by considering tumor microenvironment factors.