Abstract 7483: A new spatial multi-omics approach to deeply characterize human cancer tissue using a single slide: a new spatial muti-omics approach to deeply characterize human cancer tissue using a single slide

Abstract Introduction: In digital pathology, extracting comprehensive data from a single tissue sample is critical for enhancing diagnostic precision and therapeutic strategies. Techniques like multiplex imaging and spatial transcriptomics offer unprecedented depth of information. This study introduces a novel and innovative approach combining for the first time Phenocycler® (with a 34-marker panel) and Visium® spatial transcriptomics on the same tissue section of squamous cell carcinoma of the upper aerodigestive tract. A single tissue section was analyzed using Phenocycler® (PP) for proteomics with a 34-marker panel targeting microenvironment and structural proteins, followed by H&E staining and Visium® spatial transcriptomics (ST) to map RNA expression. This approach allowed for the thorough assessment of immune cell spatial distribution and transcriptomic profiles, while evaluating the impact of proteomic treatment on RNA integrity and gene expression. Results: Despite initial concerns about RNA degradation due to multiplex staining treatments, RNA integrity in the PP+ST sample was comparable to ST-only samples, as indicated by similar total gene expression distributions. The PP+ST sample exhibited high-density feature points across the tissue, suggesting that proteomic pre-treatment did not impair subsequent transcriptomic analysis. Unsupervised UMAP visualization revealed similar clustering patterns between PP+ST and ST-only samples, indicating preserved cellular heterogeneity and molecular signatures. Consistent spatial distributions and clustering were observed between Phenocycler® pseudospots and Visium® data, with significant correlations in the spatial distribution of key cell types, including malignant clusters and immune cells. This study is a pioneering demonstration of the feasibility and efficiency of integrating spatial proteomics and transcriptomics on the same tissue section, guaranteeing high fidelity in molecular profiling. This combined method is crucial for deepening the understanding of the tumor microenvironment, with potential implications for improving diagnostics and personalized cancer therapies. The ability to analyze multiple data layers on the same cells enhances the development of precise AI-based diagnostic tools and personalized treatment strategies. Citation Format: yasmine adimi, clement Levin, Emilia Puig Lombardi, Marion Classe, Cecile Badoual. A new spatial multi-omics approach to deeply characterize human cancer tissue using a single slide: a new spatial muti-omics approach to deeply characterize human cancer tissue using a single slide [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7483.