Microfluidic Model for Evaluation of Immune Checkpoint Inhibitors in Human Tumors

Ashley L Beckwith1,2, Luis F Velásquez-García1, Jeffrey T Borenstein2

  • 1Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA.

Insights

This study introduces a 3D-printed device for real-time monitoring of tumor tissue response to immunotherapy. It enables precise drug testing on patient tumor samples, advancing precision medicine for cancer treatment.

Area of Science:

  • Biomedical Engineering
  • Immunology
  • Oncology

Background:

  • Developing effective immunotherapies requires understanding drug response within the tumor microenvironment.
  • Current methods often lack the ability to assess real-time responses in patient-specific tumor tissues.

Purpose of the Study:

  • To demonstrate a novel technology for real-time monitoring of lymphocyte response to immunotherapeutic agents in biopsied tumor tissue.
  • To establish a platform for drug development and precision medicine in immunotherapy.

Main Methods:

  • A microfluidic tumor trapping device was fabricated using a novel 3D-printed, transparent, noncytotoxic substrate (Pro3dure GR-10).
  • The device sustains biopsied tumor fragment viability under dynamic perfusion for at least 72 hours.
  • Confocal microscopy with fluorescent tracers enabled real-time monitoring of tumor response to various immunotherapies.

Main Results:

  • The 3D-printed device successfully maintained tumor tissue viability and allowed simultaneous drug treatment administration.
  • Real-time monitoring of resident lymphocyte populations within the tumor microenvironment was achieved.
  • This platform demonstrated the ability to test immune checkpoint inhibitors on human tumor fragments in a dynamic perfusion system.

Conclusions:

  • This technology represents the first real-time monitoring system for immunotherapy response in perfused human tumor microenvironments.
  • The developed platform offers a valuable tool for drug development and personalized immunotherapy strategies.
  • This methodology aids in modeling and analyzing tumor response for improved prediction of patient-specific immunotherapy efficacy.

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