Digital pathology scoring of immunohistochemical staining reliably identifies prognostic markers and anatomical associations in a large cohort of oral cancers
Utilizing digital pathology algorithms for the objective quantification of immunohistochemical staining, this study aimed to identify robust prognostic biomarkers for oral cancer. Tissue microarrays with specimens of a large cohort of oral squamous cell carcinoma (n=222) were immunohistochemically s...
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| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
29 July 2021
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| In: |
Frontiers in oncology
Year: 2021, Volume: 11, Pages: 1-11 |
| ISSN: | 2234-943X |
| DOI: | 10.3389/fonc.2021.712944 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.3389/fonc.2021.712944 Verlag, kostenfrei, Volltext: https://www.frontiersin.org/article/10.3389/fonc.2021.712944 
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| Author Notes: | Julius Moratin, Andreas Mock, Sonja Obradovic, Karl Metzger, Christa Flechtenmacher, Karim Zaoui, Stefan Fröhling, Dirk Jäger, Jürgen Krauss, Jürgen Hoffmann, Kolja Freier, Dominik Horn, Jochen Hess and Christian Freudlsperger |
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| 520 | |a Utilizing digital pathology algorithms for the objective quantification of immunohistochemical staining, this study aimed to identify robust prognostic biomarkers for oral cancer. Tissue microarrays with specimens of a large cohort of oral squamous cell carcinoma (n=222) were immunohistochemically stained to determine the expression of PD-L1, EGFR, and COX-2 and the amount of infiltrating NK cells and CD8-positive T cells. Immunoreactivity scores were assessed using both a classical manual scoring procedure and a digital semi-automatic approach using QuPath. Digital scoring was successful in quantifying the expression levels of different prognostic biomarkers (CD8: p<0.001; NK cells: p=0.002, PD-L1: p=0.026) and high levels of concordance with manual scoring results were observed. A combined score integrating EGFR expression, neck node status and immune cell signatures with a significant impact on overall and progression-free survival was identified (p<0.001). These data may contribute to the ongoing research on the identification of reliable and clinically relevant biomarkers for the individualization of primary and adjuvant treatment in oral cancer. | ||
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