Abstract 3116: High-definition spatial transcriptomics reveals microenvironment features associated with resistance to anti-PD1 therapies in lung cancer

Abstract Introduction: Primary resistance to immune checkpoint inhibitors (anti PD1) presents a significant hurdle in lung cancer treatment. Tumor microenvironment (TME) features, particularly within the immune compartment, are central to shaping therapeutic response. This study employs high-definition spatial transcriptomics to identify biomarkers and mechanisms underlying resistance. Methods: Formalin-fixed, paraffin-embedded (FFPE) lung cancer tissues from patients resistant to anti PD1 therapies were analyzed using the Visium HD spatial transcriptomics platform. Unsupervised clustering of spatial transcriptomics data was performed to identify distinct gene expression patterns within the immune compartment. Tissue morphology was integrated with gene expression profiles to map spatial heterogeneity. Results: Our in-depth analysis of lung cancer tumor samples, utilizing high-throughput spatial transcriptomics and multiplexed immunohistofluorescence (IHF), revealed that primary resistance to PD1 PDL1 therapies is associated with a distinct tumor microenvironment. Unsupervised clustering of spatial transcriptomics data identified clear groupings that differentiated responders from resistant patients, based on immune compartment gene expression profiles. This analysis highlighted a suppression of immune-activating pathways and enrichment of immunosuppressive signals in resistant tumors, particularly within peritumoral regions. These findings underscore the pivotal role of the tumor microenvironment in modulating the likelihood of response to PD-1 blockade. Conclusion: This study underscores the transformative potential of high-definition, single-cell scale spatial transcriptomics in revealing microenvironmental features associated with primary resistance to PD1 therapies in lung cancer. By enabling precise spatial evaluation of the tumor microenvironment, the identified biomarkers offer a robust foundation for developing predictive tools and personalizing immunotherapy strategies for improved patient outcomes. Citation Format: Corinne Ramos, Sandra Delebecq, Richard Ruez, Victor Senechal. High-definition spatial transcriptomics reveals microenvironment features associated with resistance to anti-PD1 therapies in lung 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 3116.