Abstract 4634: Identifying and analyzing tumor subtypes using custom morphology markers for NanoString® GeoMx® Digital Spatial Profiler

Abstract

Abstract Molecular subtyping studies have allowed the allocation of cancer into groups based on similar molecular, morphological, and clinical characteristics. Such studies are critical to help researchers identify actionable targets for drug design and biomarkers to predict therapeutic response. Based on multi-omics data, various approaches have been used to identify and analyze tumor subtypes and their correlation with tumor immunity and immunotherapy success. The NanoString GeoMx Digital Spatial Profiler is one approach that combines morphological context with spatial transcriptomics on a single tissue specimen. A critical step in this approach involves staining with morphology markers to identify relevant regions of interest (ROIs) for analysis. Yet, widespread adoption of GeoMx DSP has revealed a significant limitation, namely that researchers base transcriptional analysis of thousands of RNA targets on the spatial information provided by only a few morphology markers. Recent efforts have greatly expanded the availability of morphology markers to facilitate cell type-specific analyses. To evaluate the ability of this technology to selectively enrich specific cell types, we developed custom morphology markers to stain non-small-cell lung cancer (NSCLC) tissue specimens of various subtypes. Focusing on squamous cell carcinoma and adenocarcinoma, we stained with P40 and TTF-1 and transcriptionally profiled cell type-specific ROIs with the Cancer Transcriptome Atlas panel. Differential gene expression analysis of the whole transcriptome was performed using GeoMx DSP Analysis Suite software. The data reveal differences in gene expression in several key cancer pathways between tumor subtypes are correlated with the presence or absence of specific cell types. The data support the use of custom morphology markers for cell type stratification in tumor subtypes, providing more meaningful gene expression analysis. Ongoing work continues to explore the utility of this technology for cell type-specific gene expression analysis within different tumor subtypes. Citation Format: Jessica Runyon, Vijay Baichwal, Weston Stauffer, Christian Nievera. Identifying and analyzing tumor subtypes using custom morphology markers for NanoString® GeoMx® Digital Spatial Profiler. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4634.