Microsystems & Nanoengineering (Sep 2024)

Microdissection tools to generate organoids for modeling the tumor immune microenvironment

  • Seth C. Cordts,
  • Kanako Yuki,
  • Maria F. Henao Echeverri,
  • Balasubramanian Narasimhan,
  • Calvin J. Kuo,
  • Sindy K. Y. Tang

DOI
https://doi.org/10.1038/s41378-024-00756-8
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 14

Abstract

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Abstract Patient-derived tumor organoids have emerged as promising models for predicting personalized drug responses in cancer therapy, but they typically lack immune components. Preserving the in vivo association between tumor cells and endogenous immune cells is critical for accurate testing of cancer immunotherapies. Mechanical dissection of tumor specimens into tumor fragments, as opposed to enzymatic digestion into single cells, is essential for maintaining these native tumor-immune cell spatial relationships. However, conventional mechanical dissection relying on manual mincing is time-consuming and irreproducible. This study describes two microdissection devices, the µDicer and µGrater, to facilitate the generation of intact tumor fragments from mouse B16 melanoma, a common model of human melanoma. The µDicer- and µGrater-cut tumor fragments were used to generate air‒liquid interface (ALI) organoids that copreserve tumor cells with infiltrating immune subsets without artificial reconstitution. The µDicer, consisting of a hexagonal array of silicon microblades, was employed to investigate the effect of organoid size. The viability of ALI organoid immune cells appeared insensitive to organoid sizes exceeding ~400 µm but diminished in organoids ~200 µm in size. The µGrater, consisting of an array of submillimeter holes in stainless steel, was employed to accelerate dissection. For the samples studied, the µGrater was 4.5 times faster than manual mincing. Compared with those generated by manual mincing, ALI organoids generated by the µGrater demonstrated similar viability, immune cell composition, and responses to anti-PD-1 immunotherapy. With further optimization, the µGrater holds potential for integration into clinical workflows to support the advancement of personalized cancer immunotherapy.