PLoS ONE (Jan 2015)

A computer-assisted 3D model for analyzing the aggregation of tumorigenic cells reveals specialized behaviors and unique cell types that facilitate aggregate coalescence.

  • Amanda Scherer,
  • Spencer Kuhl,
  • Deborah Wessels,
  • Daniel F Lusche,
  • Brett Hanson,
  • Joseph Ambrose,
  • Edward Voss,
  • Emily Fletcher,
  • Charles Goldman,
  • David R Soll

DOI
https://doi.org/10.1371/journal.pone.0118628
Journal volume & issue
Vol. 10, no. 3
p. e0118628

Abstract

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We have developed a 4D computer-assisted reconstruction and motion analysis system, J3D-DIAS 4.1, and applied it to the reconstruction and motion analysis of tumorigenic cells in a 3D matrix. The system is unique in that it is fast, high-resolution, acquires optical sections using DIC microscopy (hence there is no associated photoxicity), and is capable of long-term 4D reconstruction. Specifically, a z-series at 5 μm increments can be acquired in less than a minute on tissue samples embedded in a 1.5 mm thick 3D Matrigel matrix. Reconstruction can be repeated at intervals as short as every minute and continued for 30 days or longer. Images are converted to mathematical representations from which quantitative parameters can be derived. Application of this system to cancer cells from established lines and fresh tumor tissue has revealed unique behaviors and cell types not present in non-tumorigenic lines. We report here that cells from tumorigenic lines and tumors undergo rapid coalescence in 3D, mediated by specific cell types that we have named "facilitators" and "probes." A third cell type, the "dervish", is capable of rapid movement through the gel and does not adhere to it. These cell types have never before been described. Our data suggest that tumorigenesis in vitro is a developmental process involving coalescence facilitated by specialized cells that culminates in large hollow spheres with complex architecture. The unique effects of select monoclonal antibodies on these processes demonstrate the usefulness of the model for analyzing the mechanisms of anti-cancer drugs.