Abstract 2637: Multiplex immunohistochemistry, spatial analysis, and gene expression profiling of the tumor-immune microenvironment in HNSCC tumors
Authors: Hemphill Carlee , Maynor Timothy , Bauman John , Schroyer Caitlin , Shuster Jeffery , Turi Thomas , Anderson Steven M. 
Published: September 2020

Background: The complex and dynamic nature of the tumor-immune microenvironment presents challenges for identification of robust and predictive biomarkers in immuno-oncology (IO). Multiplex immunohistochemistry (mIHC) facilitates the ability to detect, phenotype, and quantify spatial relationships of cells within the tumor microenvironment (TME). Gene expression profiling allows for sensitive and high-throughput analysis of genes and signatures associated with the tumor, the immune response, and the TME, allowing examination of tumor-immune cell interactions. We used these approaches to generate multiple data sets from a cohort of HNSCC tumors and evaluated the correlation of the various analyte detection methods. These complementary technologies provide useful tools in the IO biomarker toolkit.

Methods: Formalin-fixed paraffin-embedded (FFPE) specimens from HNSCC patients were cut into 5µm sections for all technologies. Multiplex fluorescent IHC was performed for TME markers CD3, CD8, PD-L1, PD1, CD68, Granzyme B, Ki67, and panCK/SOX10. Visualization and data analysis were performed with an Akoya Vectra Polaris and Akoya inForm and HALO software (Indica Labs). Data analysis included cell identification, phenotyping, spatial relationships, and quantitative digital pathology. Gene expression for 770 genes was performed utilizing the NanoString PanCancer IO 360 Gene Expression Panel. Transcripts were quantitated using a NanoString nCounter and target gene counts were normalized to internal housekeeping genes.

Results: Analysis of the multiplex fluorescent IHC indicated a range of expression for the assayed TME biomarkers for the different tumor samples. Quantitative analysis of mIHC phenotype counts and normalized RNA counts for the targets contained in the antibody panel revealed a significant correlation between the analytic methods. Comparison of mIHC phenotype counts with a previously validated IO gene signature containing a broader set of IO-relevant genes, the Tumor Information Signature, (Ayers, et al., J Clin Invest. 2017; 127:2930) also showed a correlation.

Conclusions: The technologies described above enable the investigation of the TME for use in biomarker discovery, drug discovery, and IO pathway interrogation. These technologies can be used in parallel to uncover roles in the biomarker discovery pathway for genes of interest. The combination of mIHC and gene expression panels can be used to screen a broad range of targets, that then can be further investigated using the spatial analysis capabilities of mIHC to gain greater insight into the immune infiltrate density at any singular area of the TME.

Citation Format: Carlee Hemphill, Timothy Maynor, John Bauman, Caitlin Schroyer, Jeffery Shuster, Thomas Turi, Steven M. Anderson. Multiplex immunohistochemistry, spatial analysis, and gene expression profiling of the tumor-immune microenvironment in HNSCC tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2637.