Abstract 4168: All-in-one digital pathology compares and contrasts the tumor microenvironment of renal cell carcinoma tissue with paired, patient derived tumoroids

Abstract AI-powered pathology advances translational research by shrinking the gap from discovery to diagnosis through highly performant analytical capabilities. Here, we utilize the HALO®/HALO AI quantitative image analysis platform to compare the tumor microenvironment (TME) of patient tumor samples and corresponding tumoroids. Tumoroids created (in vitro) from primary tumor tissue (in vivo) allow researchers in the field of oncology to more accurately replicate the TME of patient biological specimens. Tumoroids compared to 2-D cell culture are believed to better mimic the physiologically relevant environment by reducing the destruction of native tissue structure and cellular composition. We perform AI-powered image and spatial analysis on multiplexed immunofluorescent tissues incorporating biomarkers for immune subtypes and key features of tumoroids such as TME, cell proliferation, immune profile. The samples have been obtained from the BioStudies BioImage Archive under the study S-BIAD1661 containing samples of clear cell Renal Cell Carcinoma (ccRCC)1. By applying digital pathology techniques to these research approaches, we demonstrate a thorough and versatile analysis workflow to address the characterization of tumoroids and their corresponding patient samples and highlight the impact of these tools on research, discovery and diagnostics. 1. Greice Michele Zickuhr, Hazem Abdullah, In Hwa Um, Alexander Laird, Peter Mullen, David J. Harrison and Alison L. Dickson. "Clear Cell Renal Cell Carcinoma Patient-Derived Tumoroids characterisation by Spatial Mass Spectrometry, Histology and Multiplex Immunofluorescence." BioStudies, S-BIAD1661, 2025, www.ebi.ac.uk. Accessed 22 September 2025. Citation Format: Levi Maston, Amber L. Ortiz, . All-in-one digital pathology compares and contrasts the tumor microenvironment of renal cell carcinoma tissue with paired, patient derived tumoroids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4168.