P13.04.B Dissecting high-grade glioma immune infiltration in samples from fluorescence-guided surgery: digital pathology with automated image analysis. (5th September 2022)

• Record Type: Journal Article
• Authors: Lang, A; Jeron, R L; Kiesel, B; Mischkulnig, M; Bergmeister-Berghoff, A S; Ricken, G; Wöhrer, A; Rössler, K; Lötsch-Gojo, D; Rötzer-Pejrimovsky, T; Hainfellner, J A; Höftberger, R; Widhalm, G; Erhart, F
• Is Part Of: Neuro-oncology. Volume 24(2022)Supplement 2
• Page Start: ii81
• Page End: ii81
• Publication Date: 2022-09-05
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noac174.284
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: Background: Fluorescence-guided surgery with 5-aminolevulinic acid (5-ALA) is a widely used technique to conduct maximum safe resection of high-grade gliomas (HGG). 5-ALA accumulates in malignant tumor tissue where it is metabolized to Protoporphyrin IX (PpIX), an agent with fluorescence properties. It helps neurosurgeons to distinguish between tumor-infiltrated tissue and healthy brain parenchyma. Even though fluorescence-guided surgery is clinically well established, the biological properties of different fluorescence levels are not comprehensively studied yet. A relevant current gap in that respect is the pattern of immune cell infiltration in fluorescent versus non-fluorescent tissue samples. In light of future research, reliable, standardized histopathology methods that allow high-throughput analysis are desirable and digital pathology with automated image analysis is an attractive option to explore. Material and Methods: 128 formalin-fixed paraffin-embedded (FFPE) tissue blocks of 39 patients who underwent fluorescence-guided surgery of a HGG were included. Samples were selected based on their documented 5-ALA fluorescence intensity status (strong, vague, negative). Microtome-cut sections of the tissue were stained with antibodies against CD8, CD68, CD163 and FOX P3, representing immune cell populations of specific interest (cytotoxic T cells, glioma-associated macrophages, regulatory T cells). A total of 512 stained slides were then available for assessment. In addition to a classical, semi-quantitative analysis by two independent human reviewers, the immune infiltration intensity was measured via automated image analysis with the digital pathology software QuPath Version 0.3.2. Results: Across all stained FFPE samples CD68 showed the overall highest intensity, followed by CD163. CD8 and FoxP3 showed generally lower average intensities. In 5-ALA negative and positive high-grade glioma samples the immune cell infiltration pattern was the same. Quantitative automatic digital pathology correlated well with the classical human histopathological analysis for the majority of markers evaluated. Conclusion: We successfully explored and established novel digital pathology technologies for the study of immune cell infiltration patterns in neurooncology, specifically in the context of fluorescence-guided resection. Leveraging this platform could allow parallelized and high-throughput analysis of immune cell infiltration also in other contexts.