Abstract 6271: Interactions between CD8+ T cells and tumor cells decode tumor heterogeneity and provide treatment recommendations for colorectal cancer

Abstract Introduction: Individual heterogeneity in colorectal cancer (CRC) remains a major challenge in therapy optimization, despite diagnostic and treatment advances. CD8+ T cells, pivotal players in anti-tumor immunity, display diverse functional subtypes shaped by interactions within the tumor microenvironment (TME). However, the specific role of CD8+ T cells in mediating heterogeneity through interacting with CRC cells, as well as their influence on the immune response of CRC, remains poorly understood. Here, we employ multi-transcriptomic analyses to discover the factors underlying patient heterogeneity based on interactions between various CD8+ T cell subtypes and CRC cells and develop effective, personalized therapeutic strategies. Methods & Results: Data analysis of CRC patients was conducted by harmonizing information from reputable public databases. Single-cell analysis was used to investigate the functionality and evolutionary trajectories of various CD8+ T cell subgroups. Cellular interactions and spatial omics analyses were employed to examine the receptor-ligand pairs between CD8+ T cell subtypes and CRC cells. Based on TCGA-CRC data, patients were classified into three prognostically distinct clusters through consensus clustering of the receptor-ligand pairs. Among them, cluster 2 (C2) was the most crucial one with poorest prognosis. TME patterns were predicted with multiple algorithms, and immunotherapy responses were evaluated using the TIDE and EaSleR analysis. Notably, C2 was significantly associated with exhausted CD8+ T cells and Tregs, with the lowest response to immunotherapy. High-activity transcription factors for each cluster were predicted using the univariate linear model, while hub genes were identified via WGCNA. Furthermore, functional insights into each cluster were derived from GO and KEGG enrichment analyses. We found that C2 exhibited up-regulated SMADs and SP1, signifying high immunosuppressive potential. Prognostic risk models were built utilizing multivariate Cox regression and LASSO analysis, identifying a predictive model for C2 including GPT, GPX3, etc., with robustness validated. Finally, using the oncoPredict algorithm, we predicted chemotherapy drug sensitivity and discovered that C2 showed a superior response to dasatinib and AZ960, while exhibiting resistance to ulixertinib. Conclusions: This study provides critical insights into the complex interactions between CD8+ T cells and CRC cells, highlighting their pivotal role in tumor heterogeneity. Leveraging these findings, we developed a novel classification system for CRC patients that captured TME heterogeneity and stratified patients into distinct groups. This system lays a foundation for personalized therapeutic strategies based on tumor-immune dynamics, offering significant potential to improve prognosis for CRC patients. Citation Format: Hongyu Huang, Zize Zhao, Fan Huang, Luoxinyi Yang, Shichu He, Boya Mu, Xiaoyue Liu, Ruixi Li, Yaqi Guan, Jiahao Li, Chen Gu, Jing Xu, Na Li. Interactions between CD8+ T cells and tumor cells decode tumor heterogeneity and provide treatment recommendations for colorectal cancer [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 6271.