Intrinsic Differences in Spatiotemporal Organization and Stromal Cell Interactions Between Isogenic Lung Cancer Cells of Epithelial and Mesenchymal Phenotypes Revealed by High-Dimensional Single-Cell Analysis of Heterotypic 3D Spheroid Models

Maria L. Lotsberg, Gro V. Røsland, Austin J. Rayford, Sissel E. Dyrstad, Camilla T. Ekanger, Ning Lu, Kirstine Frantz, Linda E.B. Stuhr, Henrik J. Ditzel, Jean Paul Thiery, Lars A. Akslen, James B. Lorens, Agnete S.T. Engelsen*

*Corresponding author for this work

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Abstract

The lack of inadequate preclinical models remains a limitation for cancer drug development and is a primary contributor to anti-cancer drug failures in clinical trials. Heterotypic multicellular spheroids are three-dimensional (3D) spherical structures generated by self-assembly from aggregates of two or more cell types. Compared to traditional monolayer cell culture models, the organization of cells into a 3D tissue-like structure favors relevant physiological conditions with chemical and physical gradients as well as cell-cell and cell-extracellular matrix (ECM) interactions that recapitulate many of the hallmarks of cancer in situ. Epidermal growth factor receptor (EGFR) mutations are prevalent in non-small cell lung cancer (NSCLC), yet various mechanisms of acquired resistance, including epithelial-to-mesenchymal transition (EMT), limit the clinical benefit of EGFR tyrosine kinase inhibitors (EGFRi). Improved preclinical models that incorporate the complexity induced by epithelial-to-mesenchymal plasticity (EMP) are urgently needed to advance new therapeutics for clinical NSCLC management. This study was designed to provide a thorough characterization of multicellular spheroids of isogenic cancer cells of various phenotypes and demonstrate proof-of-principle for the applicability of the presented spheroid model to evaluate the impact of cancer cell phenotype in drug screening experiments through high-dimensional and spatially resolved imaging mass cytometry (IMC) analyses. First, we developed and characterized 3D homotypic and heterotypic spheroid models comprising EGFRi-sensitive or EGFRi-resistant NSCLC cells. We observed that the degree of EMT correlated with the spheroid generation efficiency in monocultures. In-depth characterization of the multicellular heterotypic spheroids using immunohistochemistry and high-dimensional single-cell analyses by IMC revealed intrinsic differences between epithelial and mesenchymal-like cancer cells with respect to self-sorting, spatiotemporal organization, and stromal cell interactions when co-cultured with fibroblasts. While the carcinoma cells harboring an epithelial phenotype self-organized into a barrier sheet surrounding the fibroblasts, mesenchymal-like carcinoma cells localized to the central hypoxic and collagen-rich areas of the compact heterotypic spheroids. Further, deep-learning-based single-cell segmentation of IMC images and application of dimensionality reduction algorithms allowed a detailed visualization and multiparametric analysis of marker expression across the different cell subsets. We observed a high level of heterogeneity in the expression of EMT markers in both the carcinoma cell populations and the fibroblasts. Our study supports further application of these models in pre-clinical drug testing combined with complementary high-dimensional single-cell analyses, which in turn can advance our understanding of the impact of cancer-stroma interactions and epithelial phenotypic plasticity on innate and acquired therapy resistance in NSCLC.

Original languageEnglish
Article number818437
JournalFrontiers in Oncology
Volume12
Number of pages24
ISSN2234-943X
DOIs
Publication statusPublished - 22. Apr 2022

Bibliographical note

Publisher Copyright:
Copyright © 2022 Lotsberg, Røsland, Rayford, Dyrstad, Ekanger, Lu, Frantz, Stuhr, Ditzel, Thiery, Akslen, Lorens and Engelsen.

Keywords

  • drug resistance
  • erlotinib-resistance
  • heterotypic 3D models
  • imaging mass cytometry
  • in vitro cell culture models
  • non-small cell lung cancer (NSCLC)
  • tumor microenvironment

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