Open Access
CC BY-NC-ND 4.0 · Laryngorhinootologie 2022; 101(S 02): S207
DOI: 10.1055/s-0042-1746690
Poster
Head-Neck-Oncology: HPV / Tumor marker

Multiplex immunohistochemistry for mapping the tumor microenvironment of head and neck squamous cell carcinoma

Authors

  • Christoph Netzer

    1   Universitätsmedizin Göttingen, Klinik für Hals-Nasen-Ohrenheilkunde Göttingen

  • Andreas Weigert

    2   Goethe-Universität Frankfurt, Institut für Biochemi I Frankfurt

  • Dirk Beutner

    1   Universitätsmedizin Göttingen, Klinik für Hals-Nasen-Ohrenheilkunde Göttingen
Weitere Informationen
Auch verfügbar auf
 

Multiplex immunohistochemistry for mapping the tumor microenvironment of head and neck squamous cell carcinoma

Interactions between tumor cells and the tumor microenvironment play an important role in the development and metastasis of head and neck squamous cell carcinoma (HNSCC). Both, the composition of the tumor microenvironment and the localization of the cells in the tumor influence its development. Immunohistochemistry is a tried and tested method for examining solid tumors, as it involves uncomplicated sample preparation and, in particular, paraffin-fixed tissue can be stored for a long time. Today, multiplex staining techniques enable tissues to be immunotyped by simultaneously quantifying a large number of antigens. A major advantage over flow cytometry or next generation sequencing is that additional information about tumor morphology and spatial cell-cell relationships is preserved. Logistical hurdles in such analyzes are the large amounts of data and the heterogeneity between the samples. In the following, we share various workflows based on the R programming language for analyzing the tumor microenvironment in HNSCCs using multiplex immunohistochemistry, which our group has developed in recent years. This includes workflows for single cell phenotyping as well as for examining cell density and cell neighborhoods. We believe that multiplex immunohistochemistry is an extremely effective tool for identifying and quantifying cell populations as well as for determining cell neighborhood relationships in samples with a high degree of heterogeneity.



Publikationsverlauf

Artikel online veröffentlicht:
24. Mai 2022

© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Georg Thieme Verlag
Rüdigerstraße 14, 70469 Stuttgart, Germany