3D Bioprinted Multidrug Resistance (MDR)-Dependent Tumor Spheroids

Minki Hong1, Sera Hong1, Joon Myong Song1

  • 1College of Pharmacy, Seoul National University, Seoul 08826, South Korea.

PubMed

Insights

This study developed a 3D bioprinting platform to assess cancer drug resistance. The platform accurately predicts chemotherapy effectiveness by considering multidrug resistance (MDR) phenotypes in tumor spheroids.

Area of Science:

  • Biotechnology
  • Cancer Research
  • Pharmacology

Background:

  • Multidrug resistance (MDR) in cancer cells is a major challenge in chemotherapy, driven by ATP-binding cassette (ABC) transporters.
  • Accurate drug screening requires consideration of varying MDR levels in different cancer types.
  • Tailoring chemotherapy dosage based on individual MDR profiles is crucial for treatment efficacy.

Purpose of the Study:

  • To establish a 3D bioprinting-based platform for evaluating anticancer drug efficacy.
  • To investigate the correlation between MDR phenotypes and drug response in tumor spheroids.
  • To demonstrate the utility of this platform in drug discovery and personalized medicine.

Main Methods:

  • Fabrication of three-dimensional (3D) tumor spheroids from HeLa, HepG2, and A549 cells using 3D bioprinting.
  • Characterization of MDR phenotypes (MRP1 and BCRP expression) in the fabricated spheroids.
  • Quantitative assessment of doxorubicin (DOX) efficacy using EC50 values against 2D cells and 3D spheroids, with and without ABC transporter inhibitors.

Main Results:

  • 3D bioprinted tumor spheroids successfully retained their native MDR phenotypes.
  • Doxorubicin (DOX) showed significantly higher EC50 values (over 2-fold) in 3D spheroids compared to 2D cells.
  • DOX efficacy in spheroids was proportional to ABC transporter expression levels, with A549 spheroids exhibiting the highest resistance.
  • ABC transporter inhibitors (MK-571 and NOV) significantly reduced DOX EC50 values in resistant spheroids.

Conclusions:

  • The 3D bioprinting platform effectively models cancer MDR phenotypes.
  • This platform enables quantitative evaluation of anticancer drug efficacy, accounting for MDR.
  • The findings support the development of personalized chemotherapy strategies and improved drug screening processes.

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