Abstract PO-030: Single cell spatial analysis of large B cell lymphoma identifies biomarkers correlated with genetic subtypes and clincal outcomes

Abstract Single cell and multiplex imaging modalities have opened new insights into the organization and architecture of the immune microenvironment of cancer. Our group was one of the first to demonstrate these methods in the analysis of Hodgkin 1, 2 and non-Hodgkin lymphoma 3. Most recently, we demonstrated that spatial biomarkers outperform gene-expression biomarkers in predicting relapse after autologous transplant 4. Here we present previously unpublished data demonstrating single cell multiplexed spatial analysis, using the imaging mass cytometry platform, in a cohort of 426 patients with large cell lymphoma. Gene expression and mutational analysis are available for a majority of cases allowing us to correlate spatial signature with genetic classes such as LymphGen 5, and deconvolution methods such as EcoTyper 6. Using this cohort, we identify spatial biomarkers that improve prediction of clinical outcomes beyond cell of origin or genetic subgroup and identify novel targets for clinical development. Finally, we will present our approaches to move our discovery level spatial profiling into clinical diagnostic space through application of automated multiplex immunofluorescence imaging and a machine learning based image analysis pipeline. 1 Aoki T, et al. Single-Cell Transcriptome Analysis Reveals Disease-Defining T-cell Subsets in the Tumor Microenvironment of Classic Hodgkin Lymphoma. Cancer Discov. 2020 doi: 10. 1158/2159-8290. CD-19-0680. 2 Xu, A. et al. Single cell spatial analysis and biomarker discovery in Hodgkin lymphoma. Biorxiv, 2023. https: //doi. org/10. 1101/2023. 05. 24. 542195. 3 Colombo AR, et al. Single-cell spatial analysis of tumor immune architecture in diffuse large B-cell lymphoma. Blood Adv. 2022 doi: 10. 1182/bloodadvances. 2022007493. 4 Aoki T, et al. Spatially Resolved Tumor Microenvironment Predicts Treatment Outcomes in Relapsed/Refractory Hodgkin Lymphoma. J Clin Oncol. 2024 doi: 10. 1200/JCO. 23. 01115. 5 Wright GW, et al. A Probabilistic Classification Tool for Genetic Subtypes of Diffuse Large B Cell Lymphoma with Therapeutic Implications. Cancer Cell. 2020 doi: 10. 1016/j. ccell. 2020. 03. 015. 6 Steen CB, et al. The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma. Cancer Cell. 2021 doi: 10. 1016/j. ccell. 2021. 08. 011. Citation Format: Alexander Xu, Joseph Lownik, Anton Villamejor, Simeon Mahov, Ying Li, Yidan Xu-Monette, Ken Young, Akil Merchant. Single cell spatial analysis of large B cell lymphoma identifies biomarkers correlated with genetic subtypes and clincal outcomes abstract. In: Proceedings of the Fourth AACR International Meeting on Advances in Malignant Lymphoma: Maximizing the Basic-Translational Interface for Clinical Application; 2024 Jun 19-22; Philadelphia, PA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5 (3Suppl): Abstract nr PO-030.