Session: 622. Lymphomas: Translational–Non-Genetic: Poster I
Hematology Disease Topics & Pathways:
Research, Hodgkin lymphoma, Translational Research, Lymphomas, bioinformatics, Diseases, immunology, Lymphoid Malignancies, Technology and Procedures, imaging, omics technologies
Materials and Methods: Here we apply Imaging Mass Cytometry (IMC), a technology to perform ~40-plex protein analysis with 1 micron resolution in tissue, to study a cohort of 260 matched samples at diagnosis and after relapse from 90 patients with relapsed/refractory Hodgkin's Lymphoma. We developed a computational pipeline to perform cell phenotyping, spatial analysis, and biostatistics, to describe tumor architecture and propose putative biomarkers of Hodgkin’s clinical response and relapse. A novel feature of the pipeline is to quantify proteins and spatial analysis on the same numerical scale for each cell, to generate hybrid biomarkers.
Results and Discussion: We analyzed over 7 million cells for their phenotype and spatial organization. We use IMC to describe spatial features of the tumor - cell subtypes and their positioning - that correlate to clinical outcomes. We identify proteins such as CXCR5 that correlate to survival in specific spatial contexts, and we describe spatial reorganization from diagnosis to the relapsed tumor as it relates to survival and relevant clinical factors such as MHC expression and EBV infection. A significant conceptual advance was to use spatial metrics to perform “digital biopsies”, a selection of tumor regions comparable across patients. We also describe cell rosetting, a localized recruitment of immune cells to tumor that is characteristic of Hodgkin's. We validated multiple existing biomarkers in the literature using our data set and proposed novel biomarkers using IMC data.
Conclusions: Spatial analysis of the HL microenvironment revealed composite features of the TME that predict clinical outcomes. These features cannot be described using single cell tools or low-plexed imaging, and represent a truer picture of HL biology. The pipeline developed here can be universally applied to other spatial protein data for biomarker discovery and analysis, and the biomarkers proposed here will be validated with IHC.
Figure caption: IMC analysis of Hodgkin’s Lymphoma. A. IMC generates a 40-plex protein image. B, C. The image is converted to single cells and analyzed for protein and spatial features. D. A UMAP of cell phenotypes and the spatial interactions of specific phenotypes. E. The spatial and protein values are used to generate predictive biomarkers of clinical response.
Disclosures: Steidl: Roche: Consultancy; Bayer: Consultancy; AbbVie: Consultancy; Curis Inc: Consultancy; Seattle Genetics: Consultancy; Trillium Therapeutics: Research Funding; Bristol-Myers Squibb: Consultancy; Epizyme: Research Funding.
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