Abstract 6862: A scalable workflow for in silico TMA construction and groupwise comparison of spatial transcriptomic data for analyzing tumor microenvironment.

Abstract Background: Spatial transcriptomics provides high-resolution characterization of the tumor microenvironment (TME), offering insights into cellular architecture, spatial interactions, and molecular heterogeneity. However, integrating data across multiple tissue sections or multiple samples from tissue microarrays (TMAs) remains a substantial challenge, particularly for bioinformatics workflows requiring scalability and flexible cohort design. The difficulty is amplified in high-density platforms such as Visium HD, where datasets contain large numbers of cells and preserving spatial relationships during multi-slide integration is critical. Consequently, there is a growing need for a scalable computational framework that enables efficient in silico TMA construction and supports groupwise comparisons for robust TME analysis. Methods: We developed a flexible and modular computational workflow enabling in silico TMA construction and groupwise comparison of gastric cancer Visium HD data. From a total of 48 samples (2 mm core), yielding over 3.1 million 8-µm bins of spatially resolved expression data, was used for the integration and scalable group-wise comparison. Selected cores from different slides were digitally reassembled into new TMA-like layouts with automatically re-registered H3 million Visium HD bins from gastric cancer slides, it enables systematic TME profiling and identification of spatially resolved biomarkers relevant to tumor progression and therapeutic response. Citation Format: Dongjoo Lee, Sungwoo Bae, Yeonjae Jung, Kwon Joong Na, Hongyoon Choi, . A scalable workflow for in silico TMA construction and groupwise comparison of spatial transcriptomic data for analyzing tumor microenvironment 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 6862.