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Related Experiment Video

Updated: Jan 10, 2026

A 3D Spheroid Model for Glioblastoma
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3D bioprinted glioma models.

Defne Yigci1, Misagh Rezapour Sarabi2, Merve Ustun2

  • 1School of Medicine, Koc University, 34450 Istanbul, Turkey.

Progress in Biomedical Engineering (Bristol, England)
|November 25, 2025
PubMed
Summary

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This summary is machine-generated.

3D bioprinting creates advanced in vitro models to study glioma invasion and drug resistance. This technology offers a cost-effective way to mimic the brain tumor microenvironment for personalized treatments.

Area of Science:

  • Biomedical Engineering
  • Cancer Research
  • Neuro-oncology

Background:

  • Glioma is a highly invasive and often incurable brain cancer.
  • Glioma cell invasiveness complicates surgical resection and treatment.
  • Current models struggle to fully replicate the complex tumor microenvironment.

Purpose of the Study:

  • To review 3D bioprinted models for studying glioma.
  • To explore their utility in probing glioma cell invasion and drug resistance.
  • To discuss future applications of 4D printing and machine learning in glioma modeling.

Main Methods:

  • Review of emerging 3D bioprinting technologies for creating in vitro glioma models.
  • Focus on biomimetic scaffold-free cultures, organ-on-chip systems, and bioprinted platforms.
Keywords:
3D bioprintingbrain cancercancer treatmentgliomain vitro models

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  • Discussion of patient-specific modeling capabilities.

    • Main Results:

    • 3D bioprinting enables the creation of in vitro models with structural and functional tissue characteristics.
    • These models can recapitulate the brain environment and glioma tumors.
    • 3D bioprinting offers a time- and cost-efficient approach for advanced research.

    Conclusions:

    • 3D bioprinting is a promising technology for developing sophisticated in vitro glioma models.
    • These models can advance understanding of glioma invasion, drug resistance, and gliomagenesis.
    • Future integration with 4D printing and machine learning holds significant potential for personalized glioma treatment strategies.