A 31-plex panel for high-dimensional single-cell analysis of murine preclinical models of solid tumors by imaging mass cytometry

Front Immunol. 2023 Jan 19:13:1011617. doi: 10.3389/fimmu.2022.1011617. eCollection 2022.

Abstract

Currently, the study of resistance mechanisms and disease progression in cancer relies on the capacity to analyze tumors as a complex ecosystem of healthy and malignant cells. Therefore, one of the current challenges is to decipher the intra-tumor heterogeneity and especially the spatial distribution and interactions of the different cellular actors within the tumor. Preclinical mouse models are widely used to extend our understanding of the tumor microenvironment (TME). Such models are becoming more sophisticated and allow investigating questions that cannot be addressed in clinical studies. Indeed, besides studying the tumor cell interactions within their environment, mouse models allow evaluating the efficacy of new drugs and delivery approaches, treatment posology, and toxicity. Spatially resolved analyses of the intra-tumor heterogeneity require global approaches to identify and localize a large number of different cell types. For this purpose, imaging mass cytometry (IMC) is a major asset in the field of human immuno-oncology. However, the paucity of validated IMC panels to study TME in pre-clinical mouse models remains a critical obstacle to translational or basic research in oncology. Here, we validated a panel of 31 markers for studying at the single-cell level the TME and the immune landscape for discovering/characterizing cells with complex phenotypes and the interactions shaping the tumor ecosystem in mouse models.

Keywords: Imaging mass cytometry; cellular network; high dimensional multiplexing; immune signature; preclinical mouse model; tumor microenvironment.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Disease Models, Animal
  • Ecosystem*
  • Humans
  • Image Cytometry
  • Mice
  • Neoplasms*
  • Tumor Microenvironment

Grants and funding

This work was supported by the INCa-Cancéropôle GSO ‘programme emergence’ and the INCa PLBIO18-332 and the French National Research Agency under the program “Investissements d’avenir” grant agreement LabEx MAbImprove. The Imaging Mass Cytometry platform was financially supported by the Region Occitanie, Regional European Development Funds and the SIRIC Montpellier Cancer “Grant INCa-DGOS-Inserm_12553”.