Frontiers in Immunology (Jan 2022)

Picturing of the Lung Tumor Cellular Composition by Multispectral Flow Cytometry

  • Catherine Olesch,
  • David Brunn,
  • Öznur Aktay-Cetin,
  • Evelyn Sirait-Fischer,
  • Soni Savai Pullamsetti,
  • Soni Savai Pullamsetti,
  • Friedrich Grimminger,
  • Friedrich Grimminger,
  • Werner Seeger,
  • Werner Seeger,
  • Werner Seeger,
  • Bernhard Brüne,
  • Bernhard Brüne,
  • Bernhard Brüne,
  • Andreas Weigert,
  • Andreas Weigert,
  • Andreas Weigert,
  • Rajkumar Savai,
  • Rajkumar Savai,
  • Rajkumar Savai,
  • Rajkumar Savai

DOI
https://doi.org/10.3389/fimmu.2022.827719
Journal volume & issue
Vol. 13

Abstract

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The lung tumor microenvironment plays a critical role in the tumorigenesis and metastasis of lung cancer, resulting from the crosstalk between cancer cells and microenvironmental cells. Therefore, comprehensive identification and characterization of cell populations in the complex lung structure is crucial for development of novel targeted anti-cancer therapies. Here, a hierarchical clustering approach with multispectral flow cytometry was established to delineate the cellular landscape of murine lungs under steady-state and cancer conditions. Fluorochromes were used multiple times to be able to measure 24 cell surface markers with only 13 detectors, yielding a broad picture for whole-lung phenotyping. Primary and metastatic murine lung tumor models were included to detect major cell populations in the lung, and to identify alterations to the distribution patterns in these models. In the primary tumor models, major altered populations included CD324+ epithelial cells, alveolar macrophages, dendritic cells, and blood and lymph endothelial cells. The number of fibroblasts, vascular smooth muscle cells, monocytes (Ly6C+ and Ly6C–) and neutrophils were elevated in metastatic models of lung cancer. Thus, the proposed clustering approach is a promising method to resolve cell populations from complex organs in detail even with basic flow cytometers.

Keywords