Journal article

Picturing of the Lung Tumor Cellular Composition by Multispectral Flow Cytometry


Authors listOlesch, Catherine; Brunn, David; Aktay-Cetin, Oeznur; Sirait-Fischer, Evelyn; Pullamsetti, Soni Savai; Grimminger, Friedrich; Seeger, Werner; Bruene, Bernhard; Weigert, Andreas; Savai, Rajkumar

Publication year2022

JournalFrontiers in Immunology

Volume number13

ISSN1664-3224

Open access statusGold

DOI Linkhttps://doi.org/10.3389/fimmu.2022.827719

PublisherFrontiers Media


Abstract
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.



Citation Styles

Harvard Citation styleOlesch, C., Brunn, D., Aktay-Cetin, O., Sirait-Fischer, E., Pullamsetti, S., Grimminger, F., et al. (2022) Picturing of the Lung Tumor Cellular Composition by Multispectral Flow Cytometry, Frontiers in Immunology, 13, Article 827719. https://doi.org/10.3389/fimmu.2022.827719

APA Citation styleOlesch, C., Brunn, D., Aktay-Cetin, O., Sirait-Fischer, E., Pullamsetti, S., Grimminger, F., Seeger, W., Bruene, B., Weigert, A., & Savai, R. (2022). Picturing of the Lung Tumor Cellular Composition by Multispectral Flow Cytometry. Frontiers in Immunology. 13, Article 827719. https://doi.org/10.3389/fimmu.2022.827719



Keywords


hierarchical clusteringlung tumor heterogeneitymultispectral flow cytometryNK1.1NKT CELLSTUMOR MICROENVIRONMENT

Last updated on 2025-10-06 at 11:35