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Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
Published on: March 25, 2020
Development of Tools for the Selective Visualization and Quantification of TLS-Immune Cells on Tissue Sections
Christophe Klein1,2,3, Priyanka Devi-Marulkar2,3,4,5, Marie-Caroline Dieu-Nosjean2,3,4
1Center of Cellular Imaging and Cytometry, Institut National de la Santé et de la Recherche Médicale (INSERM) UMRS 1138, Cordeliers Research Center, Paris, France.
Abstract:
Tertiary lymphoid structures (TLS) are considered as genuine markers of inflammation. Their presence within inflamed tissues or within the tumor microenvironment has been associated with the local development of an active immune response. While high densities of TLS are correlated with disease severity in autoimmune diseases or during graft rejection, it has been associated with longer patient survival in many cancer types. Their efficient visualization and quantification within human tissues may represent new tools for helping clinicians in adjusting their therapeutic strategy. Some immunohistochemistry (IHC) protocols are already used in the clinic to appreciate the level of immune infiltration in formalin-fixed, paraffin-embedded (FFPE) tissues. However, the use of two or more markers may sometimes be useful to better characterize this immune infiltrate, especially in the case of TLS. Besides the growing development of multiplex labeling approaches, imaging can also be used to overcome some technical difficulties encountered during the immunolabeling of tissues with several markers.This chapter describes IHC methods to visualize in a human tissue (tumoral or not) the presence of TLS. These methods are based on the immunostaining of four TLS-associated immune cell populations, namely follicular B cells, follicular dendritic cells (FDCs), mature dendritic cells (mDCs), and follicular helper T cells (TFH), together with non-TFH T cells. Methodologies for subsequent quantification of TLS density are also proposed, as well as a virtual multiplexing method based on image registration using the open-source software ImageJ (IJ), aiming at co-localizing several immune cell populations from different IHC stainings performed on serial tissue sections.
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