Abstract
Abstract Background: The complex and dynamic nature of the tumor-immune microenvironment (TME) presents challenges for identification of robust and predictive biomarkers in immuno-oncology (IO). Standard multiplex immunohistochemistry (mIHC) or multiplex immuno-fluorescent assays (mIF) allow for the phenotyping on the cellular level but are limited by the number of markers available and the detection systems. Gene expression or next generation sequencing (NGS) platforms provide high-plex bulk data sets about the TME, but the spatial context of the tumor and immune cell interactions is lost. The NanoString GeoMx Digital Spatial Profiler (DSP) combines spatial context, utilizing fluorescent morphological markers, with molecular profiling capabilities. This combination allows for the quantitative analysis of high-plex analyte abundance which can be traced back to a region of interest within a sample, providing biological inference in the region of interest. Methods: Formalin-fixed paraffin-embedded (FFPE) specimens from HNSCC patients were cut in 5µm sections for all analyses. Whole section tissue analysis for a 770 gene expression panel was previously performed utilizing the NanoString PanCancer IO 360 Gene Expression Panel. Specific tumor microenvironment (TME) region gene expression was analyzed using two different gene expression panels with the NanoString GeoMx digital spatial profiling technology, the GeoMx Immune Pathways Panel (84 genes) and the GeoMx Human Whole Transcriptome Atlas (WTA) panel (18,000 genes). For both panels, the TME regions of interest (ROI) were identified using a set of morphology markers consisting of panCK, CD45 and Syto13, 12 ROIs were selected from each sectioned tumor material. Results: The IO360 nCounter readout was high-throughput but lacked the spatial definition that can be crucial to understanding the heterogeneity of the TME. The GeoMx Immune Pathways Panel provided counts for 84 targets known to be crucial in the immuno-oncology field, including the PD-1/PD-L1 inhibitor pathway blockade. These counts were successfully mapped to the 12 ROIs on the tissue. The WTA panel provided an unbiased view of 18,000 protein-coding genes with the same ROI spatial resolution as the Immune Pathways Panel along with increased insight into the TME. Conclusions: The technologies described above enable the investigation of the TME for use in biomarker discovery in the field of immunotherapy but can also facilitate the discovery of prognostic markers or mechanism of action studies because of the high dimensional data with spatial context. The detailed analysis of the 18,000 genes provides exhaustive information on the biology of the tumor microenvironment that was formerly limited in spatial resolution. Citation Format: Carlee Hemphill. High dimensional spatial gene expression analysis of tumor micro-environment in head and neck squamous cell carcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3806.
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