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Updated: Aug 22, 2025

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Microfluidics guided by deep learning for cancer immunotherapy screening.

Zheng Ao1, Hongwei Cai1, Zhuhao Wu1

  • 1Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN 47405.

Proceedings of the National Academy of Sciences of the United States of America
|November 7, 2022
PubMed
Summary

This study introduces a microfluidic platform to track T cell infiltration and killing in 3D tumors. It identified an epigenetic drug that enhances immunotherapy for solid tumors.

Keywords:
cancer immunotherapydeep learningdrug screeningimmune infiltrationmicrofluidics

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Area of Science:

  • Immunology
  • Oncology
  • Biotechnology

Background:

  • T cell infiltration and cytotoxicity are crucial for inflammation and cancer immunotherapy.
  • Current screening methods fail to assess T cell penetration into tumor stroma, hindering solid tumor treatment development.

Purpose of the Study:

  • To develop an automated high-throughput microfluidic platform for simultaneous tracking of T cell infiltration and cytotoxicity in 3D tumor cultures.
  • To evaluate treatment efficacy using a deep learning-based clinical tumor-infiltrating lymphocyte (TIL) score analyzer.
  • To discover novel immuno- and combination therapies for solid tumors.

Main Methods:

  • An automated microfluidic platform was developed for 3D tumor cultures with tunable stromal composition.
  • Simultaneous tracking of T cell infiltration dynamics and cytotoxicity was performed.
  • A clinical data-driven deep learning method (TIL score analyzer) was employed to score T cell infiltration patterns.
  • A drug library was screened using this platform.

Main Results:

  • The platform successfully evaluated T cell infiltration and cytotoxicity in 3D tumor models.
  • Screening identified an epigenetic drug (lysine-specific histone demethylase 1 inhibitor, LSD1i) that significantly promoted T cell tumor infiltration.
  • LSD1i demonstrated enhanced therapeutic efficacy when combined with an immune checkpoint inhibitor (anti-PD1) in vivo.

Conclusions:

  • The developed automated system and strategy enable effective screening of immunocyte-solid tumor interactions.
  • This approach facilitates the discovery of potent immuno- and combination therapies for solid tumors.
  • The study highlights the potential of targeting T cell infiltration for improved cancer immunotherapy outcomes.