Abstract 6876: Cyclic immunofluorescent analysis of the tumor microenvironment across human brain cancer subtypes
Authors: Fails Danielle , Spencer Michael 
Published: March 2024

Abstract
Introduction: The tumor microenvironment (TME) has been the focus of a myriad of studies over the last decade and advancements in the field of cancer research have grown as a result. Improvements in the number of biomarkers that can be screened has increased across a variety of methods and the field of spatial profiling has largely adapted to keep pace with this. However, many challenges persist: 1) tissue microarrays can be limited by tumor heterogeneity and 2) newer technology can be cost-prohibitive. Brain tumors are of significant importance, especially those of glial origin, as they swiftly progress and result in a high fatality rate. As such, the need for more diverse therapeutic approaches is growing with many already pioneering new IHC-based strategies. The aim of this study was to address both challenges addressed above in the neurobiology space.
Methods: Biomarkers of importance in brain cancer tissues were identified and three distinct panels were designed. The first panel consisted of CD68, CTLA-4, p16ink4A, p14ARF, and p53. The second included PDPN, Calretinin, MAGE-D2, PTEN, and Vimentin. The third panel included IDH2, BRAF, GFAP, VEGF, and BOP1. Staining was achieved using Bethyl Laboratories IHC-validated primary and secondary antibodies and Akoya Opal™ Polaris 7-color IHC kit fluorophores (Akoya Biosciences [NEL861001KT]). Optimization was achieved using FFPE tissue microarrays containing normal neural tissue and brain cancer subtypes. The final optimized order was then tested on whole serial sections of meningioma, astrocytoma, and glioblastoma in six-color mIF. Images were generated using the PhenoImager HT® and subsequently merged and analyzed by Pathomics.
Results: Phenotyping and total cell counts for each marker were identified for each serially stained tissue set. Expression levels of MAGE-D2 and BRAF were high across malignant tissues of variable gradations. Conversely, in tissues with high expression of MAGE-D2, p53 levels in these samples were lower. This is consistent with findings that suggested that MAGE-D2 is a potential dissociator of p53 by impairing transcriptional activity. Macrophage expression appeared to correlate with CTLA4 and overall tumor infiltration.
Conclusions: Utilizing several unique biomarkers to understand the spatial relationships and phenotypes within the tumor microenvironment is becoming a more common practice among researchers. In using this method of serially staining tissue sections and merging the resulting images, more researchers will have access to spatial information which may have been cost-prohibitive otherwise. Additionally, in utilizing whole sections of difficult-to-treat cancerous tissue rather than microarrays, phenotypic information is available across the entire tumor microenvironment enabling a more comprehensive assessment of the TME.
Citation Format: Danielle Fails, Michael Spencer. Cyclic immunofluorescent analysis of the tumor microenvironment across human brain cancer subtypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6876.