Abstract 876: spatialGE: Empowering researchers to study the tumor microenvironment leveraging spatial transcriptomics

Abstract

Abstract The use of single-cell RNA-seq (scRNA-seq) to understand the complexity of the tumor microenvironment (TME) has been pivotal in advancing cancer research and treatment strategies. Nevertheless, locating the individual TME components in their spatial contexts is essential to understanding the complexity of the TME, tumorigenesis, metastasis, and drug response. The recent popularity of spatially resolved transcriptomics (SRT) allows researchers to describe the TME and their spatial neighborhoods; however, SRT data analysis can be challenging for non-data scientists. Thus, we have developed spatialGE, a point-and-click web application designed to empower researchers in the analysis of SRT data. Our application offers a suite of functionalities, including the visualization of spatial gene expression activity maps, quantification of the spatial heterogeneity, testing of pathway-level spatial aggregation, tissue domain/niche detection, detection of spatial gradients in expression patterns, and differential expression analysis. Furthermore, spatialGE allows direct comparative analysis of gene expression with the morphology in tissue images, as well as methods for cell/domain phenotyping. Data input has been streamlined and made flexible to receive outputs from multiple SRT platforms. Analyses and results are stored within user-defined projects to facilitate accessibility at any time. We demonstrate the usefulness of spatialGE through its application to leptomeningeal metastatic melanoma (LMM) tissues assayed with the Visium platform. The gene expression tissue domain detection and gradient analysis in spatialGE indicated that SERPINA3 expression is higher in tumor regions closer to stroma. This finding led to cell culture experiments indicating that knocking down SERPINA3 results in the sensitization of tumors to MAPK-targeting therapy. These results highlight the utility of spatialGE for exploring SRT data and the empowerment of cancer researchers to explore the spatial architecture of the TME. Citation Format: Oscar Ospina, Roberto Manjarres-Betancur, Guillermo Gonzalez-Calderon, Alex C. Soupir, Inna Smalley, Kenneth Tsai, Joseph Markowitz, Anders Berglund, Xiaoqing Yu, Brooke L. Fridley. spatialGE: Empowering researchers to study the tumor microenvironment leveraging spatial transcriptomics [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 876.