Modeling immunotherapies in live 3D human cancer tissue bioreactors

Yizheng Zhang1, Ivan Foth1, Ahmad Makky1

  • 1Department of Pathology and Neuropathology, University Hospital and Comprehensive Cancer Center Tübingen, Germany.

Theranostics
|February 16, 2026
PubMed

Insights

A new 3D bioreactor model preserves the human tumor microenvironment (TME) for testing cancer immunotherapies. This approach enables rapid ex vivo assessment of treatment responses, aiding personalized medicine and improving patient outcomes.

Area of Science:

  • Oncology
  • Immunology
  • Biotechnology

Background:

  • Cancer immunotherapies show variable efficacy, necessitating predictive biomarkers and better models.
  • Existing models fail to fully replicate the human tumor microenvironment (TME).
  • A need exists for physiologically relevant models to predict individual immunotherapy responses.

Purpose of the Study:

  • To develop an ex vivo 3D human tissue culture model preserving the native TME for immunotherapy testing.
  • To establish a platform for rapid ex vivo assessment of therapeutic responses to guide clinical decisions.
  • To evaluate the efficacy of CAR T cell therapies and antibody-based treatments in a preserved TME.

Main Methods:

  • Human lymph node (LN) tissue pieces were cultured in perfusion bioreactors for three days.
  • CAR T cell therapies and antibody-based treatments were administered ex vivo.
  • Tissue viability, cell infiltration, and treatment efficacy were assessed using flow cytometry, histology, and microscopy.

Main Results:

  • The bioreactor system significantly improved tissue viability compared to traditional plate cultures.
  • Novel CAR T cells showed enhanced tissue infiltration but similar cytotoxicity to conventional CAR T cells.
  • Pembrolizumab (PD-1 inhibitor) reduced lymphoma and melanoma cell viability without harming benign LN tissues.

Conclusions:

  • The optimized bioreactor culture system is a robust platform for evaluating immunotherapy efficacy in a physiologically relevant TME.
  • This model has potential for advancing personalized treatment strategies and understanding immunotherapy mechanisms.
  • The system may improve clinical outcomes by enabling better prediction of treatment responses.

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