1179. Deep spatial immuno-profiling through high biomarker colocalization in FFPE tumor tissue samples Abdul Mohammed, Chineme Onwubueke, and Maël Manesse Ultivue, Inc. 763D Concord Avenue, Cambridge, MA 02138 • +1-617-945-2662 • www.ultivue.com • [email protected] • Twitter: @Ultivue The recent emergence of multiplexed immunohistochemistry (IHC) has the potential to revolutionize immuno-oncology and pathology research as it enables the identification of complex cell subtypes and their interactions in the tumor environment. Comprehensive classification of the different cell types in immuno-oncology presents a unique challenge as many of the relevant biomarkers are common to large subsets of cell types within a particular cell class. Therefore, a key feature for accurate phenotypic classification is the ability to detect a high number of colocalized biomarkers. In this study, we demonstrate how the InSituPlex ® technology enables researchers to reliably label and detect phenotypes with markers expressed in the same compartment (membrane, cytoplasmic, or nuclear) on single cells of a NSCLC tissue section stained with 16 different markers. For more information, refer to poster #1183. Conclusions Introduction PD-L1 Panel APC Panel High co-expression and deep phenotyping in a single NSCLC tissue section For Research Use Only. Not for use in diagnostic procedures. Tissue samples were procured from commercial vendors for this research study. Ultivue®, InSituPlex®, UltiMapper™ are either registered trademarks or trademarks of Ultivue in the United States and/or other countries. All other trademarks are property of their respective owners. In this poster, we demonstrate research of the identification of phenotypes based on the co-expression and colocalization of biomarkers on the same cells in a lung tumor section. Analysis of the high dimensional, spatially resolved data obtained from a 16- plex assay provided phenotypic information of different lymphocytes, macrophages, dendritic cells, antigen-presenting cells, and tumor cell populations with multiple colocalized biomarkers. Overlay CD3 CD8 Cytotoxic T cells Overlay CD3 CD4 Helper T cells Overlay CD3 CD4 FOXP3 Naïve regulatory T cells Overlay CD3 CD8 GrB Cytotoxic T cells expressing Granzyme B Overlay CD3 CD4 CD45RO Memory helper T cells Overlay CD11c Dendritic cells B cells Overlay CD20 Overlay CD3 CD4 CD45RO FOXP3 Memory regulatory T cells Overlay CD3 CD8 CD45RO LAG3 PD-1 Exhausted memory cytotoxic T cells Overlay CD3 CD8 CD45RO Memory cytotoxic T cells Overlay CD68 CD163 M2 macrophages CD8 regulatory T cells Overlay CD3 CD8 FOXP3 Overlay CD68 CD163 PD-L1 Immunosuppressive M2 macrophages Overlay CD68 MHCII Antigen-presenting M1 macrophages APC Panel (ROI) CK Ki67 Overlay Proliferating tumor cells Proliferating immune evading tumor cells CK PD-L1 Ki67 Overlay DAPI CD3 CD4 CD8 CD11c CD20 CD45RO CD68 CD163 FoxP3 GranzymeB Ki67 LAG3 MHCII PD-1 PD-L1 Cytokeratin Proliferating exhausted memory T cells CD3 CD45RO PD-1 Ki67 Overlay Overlay CD3 CD8 GrB NK cells expressing Granzyme B Tumor Cells Immune Cells
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1179. Deep spatial immuno-profiling through high biomarker colocalization in FFPE tumor tissue samplesAbdul Mohammed, Chineme Onwubueke, and Maël ManesseUltivue, Inc. 763D Concord Avenue, Cambridge, MA 02138 • +1-617-945-2662 • www.ultivue.com • [email protected] • Twitter: @Ultivue
The recent emergence of multiplexed immunohistochemistry(IHC) has the potential to revolutionize immuno-oncology andpathology research as it enables the identification of complex cellsubtypes and their interactions in the tumor environment.Comprehensive classification of the different cell types inimmuno-oncology presents a unique challenge as many of therelevant biomarkers are common to large subsets of cell typeswithin a particular cell class. Therefore, a key feature for accuratephenotypic classification is the ability to detect a high number ofcolocalized biomarkers. In this study, we demonstrate how theInSituPlex® technology enables researchers to reliably label anddetect phenotypes with markers expressed in the samecompartment (membrane, cytoplasmic, or nuclear) on single cellsof a NSCLC tissue section stained with 16 different markers. Formore information, refer to poster #1183.
Conclusions
Introduction
PD-L1 Panel APC Panel
High co-expression and deep phenotyping in a single NSCLC tissue section
For Research Use Only. Not for use in diagnostic procedures.Tissue samples were procured from commercial vendors for this research study.Ultivue®, InSituPlex®, UltiMapper™ are either registered trademarks or trademarks of Ultivue in the United States and/or other countries. All other trademarks are property of their respective owners.
In this poster, we demonstrate research of the identification ofphenotypes based on the co-expression and colocalization ofbiomarkers on the same cells in a lung tumor section. Analysis ofthe high dimensional, spatially resolved data obtained from a 16-plex assay provided phenotypic information of differentlymphocytes, macrophages, dendritic cells, antigen-presentingcells, and tumor cell populations with multiple colocalizedbiomarkers.
Overlay CD3 CD8
Cytotoxic T cells
Overlay CD3 CD4
Helper T cellsOverlay CD3 CD4 FOXP3
Naïve regulatory T cells
Overlay CD3 CD8 GrB
Cytotoxic T cells expressing Granzyme B
Overlay CD3 CD4 CD45RO
Memory helper T cells
Overlay CD11c
Dendritic cells B cellsOverlay CD20
Overlay CD3 CD4 CD45RO FOXP3
Memory regulatory T cells
Overlay CD3 CD8 CD45RO LAG3 PD-1
Exhausted memory cytotoxic T cells
Overlay CD3 CD8 CD45RO
Memory cytotoxic T cells
Overlay CD68 CD163
M2 macrophagesCD8 regulatory T cells
Overlay CD3 CD8 FOXP3
Overlay CD68 CD163 PD-L1
Immunosuppressive M2 macrophages
Overlay CD68 MHCII
Antigen-presenting M1 macrophages
APC Panel (ROI)
CK Ki67Overlay
Proliferating tumor cells
Proliferating immune evading tumor cells
CK PD-L1 Ki67Overlay
DAPICD3CD4CD8CD11cCD20CD45ROCD68CD163FoxP3GranzymeBKi67LAG3MHCIIPD-1PD-L1Cytokeratin
Proliferating exhausted memory T cellsCD3 CD45RO PD-1 Ki67Overlay
Overlay CD3 CD8 GrB
NK cells expressing Granzyme B
TumorCells
ImmuneCells
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