Abstract 7480: Spatial Groups provide a pan-tumor spatial transcriptomic biomarker of immunotherapy response

Abstract Immune checkpoint blockade (ICB) has transformed cancer therapy and is now approved in every type of cancer, yet it remains difficult to identify the ∼ 20% of patients that will benefit from such therapy. Explainable models that predict ICB response can potentially spare ‘responders’ from toxic chemotherapies while identifying alternative options for ‘non-responders’. The only widely approved ICB biomarker of response, PD-L1, treats TME cells as individual components and is only weakly predictive of outcomes. Recent studies have suggested that biomarkers built on cell-to-cell spatial proximity, such as tumor cell to CD8+ T cell distance, can improve upon PD-L1 in predicting ICB efficacy. Yet, there is a lack of generalized approaches for identifying tumor spatial biology relationships relevant to ICB response, especially considering the wealth of information generated by high-resolution spatial biology techniques. Our approach was (1) to integrate spatial transcriptomics datasets from 96 tumors across twelve tumor types and (2) to apply statistical covariation approaches to identify organizing principles of spatial biology that would facilitate the comparison of these datasets. The basis of this approach is our identification of a conserved unit of pan-tumor spatial organization that we termed ‘Spatial Groups’. Spatial Groups (SGs) are multi-cellular units demonstrating coordinated transcriptional programs contained within spatial domains ranging in size from tens of microns (dozens of cells) to mm-scale (large regions of a tumor). SGs are hierarchically organized such that large-scale SGs exert contextual field effects on their nested small-scale SGs. For example, we found that T cell presence in large-scale SGs impacted metabolic pathway shifts occurring within nested medium-scale SGs, which in turn impacted cell adhesion programs within nested small-scale SGs. We found that SGs revealed immune-related spatial biology patterns that we hypothesized would serve as a genome-wide spatial biomarker of ICB response. To test this idea, we performed a retrospective study of 16 patients with metastatic non-small cell lung cancer treated with ICB or chemotherapy-ICB in the frontline setting. Unlike PD-L1 status, our SG-derived biomarker was highly significant in predicting progression-free survival after therapy initiation. Additionally, analysis of SGs in non-responder patients provided insights into patient-specific spatial biology architectures limiting ICB efficacy. In summary, our discovery of Spatial Groups provides a general framework for using spatial biology to identify pan-tumor ICB response. Citation Format: Vivek Behera, Hannah Giba, Ue-Yu Pen, Anna Di Lello, Benjamin A. Doran, Alessandra Esposito, Apameh Pezeshk, Christine Bestvina, Justin P. Kline, Marina C. Garassino, Arjun S. Raman. Spatial Groups provide a pan-tumor spatial transcriptomic biomarker of immunotherapy response [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 7480.