Abstract LB016: Spatial transcriptomics-based platform for pathological diagnosis and research of colorectal cancer

Abstract The application of spatial transcriptomic (ST) in contemporary pathology is promising yet rarely validated. We herein established a ST-based platform to analyze colorectal cancers following the logic and workflow of routine histopathological diagnosis. By integrating spatial coordinate traits with in-situ gene expression matrix, we reproduced and extended key diagnostic features for tumor diagnosis and molecular analysis including proliferation evaluation, vasculature identification, immune scoring and dMMR/pMMR molecular subtyping. Meanwhile, spatial and morphological distinction ST co-dominated broadened avenues for targeted cancer therapy and research. In hyperplasia/carcinoma confusion sites, we detected mixed cnv patterns in single crypt with distinct spatial distributions; Meanwhile, RNA-based molecular subtypes prevailed with intratumor heterogeneity and concurrently exhibited uniformed histological characteristics; Moreover, landscape of temporal molecular variation during cancer infiltration stages revealed potential metastatic biomarkers and mechanisms. In conclusion, we have herein established a comprehensive platform to perform and extensely extend assessment for tumor diagnosis. Additionally, by aligning histological features and gene expression profiles, we excavated significant opportunity for pathological investigation and coordination of multimodal molecular pathology dimensions, which is suitable and ideal for scientific discoveries and molecular diagnosis. With improvement in efficiency and cost-effectiveness, we foresee that this de novo platform will significantly advance pathological diagnosis and research of cancer tissue. Citation Format: Chi Qu, Huaqiang Huang, Yan Quan, Xuqing He, Weifeng Zhang, Tianbi Duan, Jiajun Zhang, Jiang Gu. Spatial transcriptomics-based platform for pathological diagnosis and research of colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB016.