Glioblastoma-Derived Three-Dimensional Ex Vivo Models to Evaluate Effects and Efficacy of Tumor Treating Fields

Vera Nickl1, Ellina Schulz1, Ellaine Salvador1

  • 1Section Experimental Neurosurgery, Department of Neurosurgery, University of Würzburg, 97080 Würzburg, Germany.

Cancers
|November 11, 2022
PubMed

Insights

New 3D models show Tumor Treating Fields (TTFields) effectively reduce glioblastoma (GBM) growth and proliferation in patient-derived cells, while preserving individual tumor response variability for personalized treatment insights.

Area of Science:

  • Neuro-oncology
  • Cancer Biology
  • Biomedical Engineering

Background:

  • Glioblastoma (GBM) exhibits significant heterogeneity, leading to therapeutic resistance and recurrence.
  • Current ex vivo models are insufficient for evaluating Tumor Treating Fields (TTFields) effects or screening patient responses.
  • TTFields represent a promising therapeutic modality for GBM treatment.

Purpose of the Study:

  • To develop and validate patient-derived 3D tissue culture models for TTFields application in glioblastoma.
  • To assess the efficacy of TTFields on GBM microtumors and organoids.
  • To investigate the impact of TTFields on GBM cell proliferation marker Ki67.

Main Methods:

  • Adaptation of patient-derived primary cells (PDPC) onto murine organotypic hippocampal slice cultures (OHSC).
  • Application of TTFields (200 kHz) to GBM microtumors and organoids cultured on OHSC.
  • Evaluation of Ki67 proliferation marker expression post-TTFields treatment.

Main Results:

  • GBM microtumors demonstrated enhanced sensitivity to TTFields compared to traditional monolayer cultures.
  • TTFields treatment led to a reduction in microtumor size and Ki67-positive cell percentage, indicating decreased proliferation and improved viability.
  • Variability in treatment response was observed across different patient-derived samples, mirroring clinical heterogeneity.

Conclusions:

  • Developed 3D GBM models are suitable for simulating patient treatment responses to TTFields.
  • These models offer a platform for investigating molecular mechanisms underlying TTFields response and resistance.
  • The models hold potential for personalized medicine approaches in glioblastoma treatment.

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