Abstract 5318: Identifying immune cell phenotypes and their function by using high throughput spatial multiomics

Abstract Advances in our understanding of the tumor microenvironment (TME) will help inform the development of next generation immunotherapies and engineered immune-cell therapies. Spatially characterizing immune cells with cell marker protein and activation marker RNAs is crucial to determine therapeutic efficacy and potential therapeutic toxicity. To address this, we have developed a high throughput RNAscope™ assay on the BOND RX to spatially visualize RNA and protein markers on the same slide. We utilized the new RNAscope™ Multiomic LS assay that can detect up to 6 RNA and protein targets on the same slide. The TSA-based amplification strategy offers signal boost for both RNA and protein targets. To optimize protein detection, the workflow is completely protease-free there by preserving antigen integrity and tissue morphology. The assay can be customized to include any target RNA and proteins of interest. Here, we demonstrate the use of our pre-conjugated antibody panel which includes CD8, CD4, FoxP3 and PanCK to visualize tumor infiltrating lymphocytes (TILs). We also utilized unconjugated primary antibodies for CD68 and CD163 to detect tumor macrophages in multiple tumor tissues. Using the HALO® image analysis software from Indica Labs, we performed RNA and protein quantification as well as cell phenotyping and spatial analysis. Infiltrating Cytotoxic T cell lymphocytes were detected using CD8, GZMB and IFNG co-expression. Regulatory T cells were detected using CD4, FOXP3 co-expression. PanCK was used as a tumor marker to delineate tumor from stroma. Similarly, tumor associated macrophages were detected using CD163, CD68 , IL10 and IL-1B expression. We were also able to identify distinct M1 and M2 macrophage populations in the tumor samples. The protease-free RNAscope Multiomic LS assay was successfully able to interrogate different subpopulation of immune cells with high fidelity RNA and protein signal while maintaining tissue morphology. The higher plex capability provides detection of more markers simultaneously, in turn enabling immune phenotype profiling while maintaining the sensitivity and specificity. Finally, the assay affords a very high throughput on the BOND Rx allowing large-scale pre-clinical and patient sample analysis. Citation Format: Debia Wakhloo, Julia Yu, Sonali Deshpande, Donald Allen, Anne Hellebust, Anushka Dikshit. Identifying immune cell phenotypes and their function by using high throughput spatial multiomics [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 5318.

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Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-5318
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Abstract 5318: Identifying immune cell phenotypes and their function by using high throughput spatial multiomics

Julia Yu, Debia Wakhloo, Sonali Deshpande, Anushka Dikshit et al.
Cancer Research
Single-cell and spatial transcriptomics
article

Abstract 5318: Identifying immune cell phenotypes and their function by using high throughput spatial multiomics

Julia Yu, Debia Wakhloo, Sonali Deshpande, Anushka Dikshit, Anne Hellebust, Donald M. Allen
article en

Abstract

Abstract Advances in our understanding of the tumor microenvironment (TME) will help inform the development of next generation immunotherapies and engineered immune-cell therapies. Spatially characterizing immune cells with cell marker protein and activation marker RNAs is crucial to determine therapeutic efficacy and potential therapeutic toxicity. To address this, we have developed a high throughput RNAscope™ assay on the BOND RX to spatially visualize RNA and protein markers on the same slide. We utilized the new RNAscope™ Multiomic LS assay that can detect up to 6 RNA and protein targets on the same slide. The TSA-based amplification strategy offers signal boost for both RNA and protein targets. To optimize protein detection, the workflow is completely protease-free there by preserving antigen integrity and tissue morphology. The assay can be customized to include any target RNA and proteins of interest. Here, we demonstrate the use of our pre-conjugated antibody panel which includes CD8, CD4, FoxP3 and PanCK to visualize tumor infiltrating lymphocytes (TILs). We also utilized unconjugated primary antibodies for CD68 and CD163 to detect tumor macrophages in multiple tumor tissues. Using the HALO® image analysis software from Indica Labs, we performed RNA and protein quantification as well as cell phenotyping and spatial analysis. Infiltrating Cytotoxic T cell lymphocytes were detected using CD8, GZMB and IFNG co-expression. Regulatory T cells were detected using CD4, FOXP3 co-expression. PanCK was used as a tumor marker to delineate tumor from stroma. Similarly, tumor associated macrophages were detected using CD163, CD68 , IL10 and IL-1B expression. We were also able to identify distinct M1 and M2 macrophage populations in the tumor samples. The protease-free RNAscope Multiomic LS assay was successfully able to interrogate different subpopulation of immune cells with high fidelity RNA and protein signal while maintaining tissue morphology. The higher plex capability provides detection of more markers simultaneously, in turn enabling immune phenotype profiling while maintaining the sensitivity and specificity. Finally, the assay affords a very high throughput on the BOND Rx allowing large-scale pre-clinical and patient sample analysis. Citation Format: Debia Wakhloo, Julia Yu, Sonali Deshpande, Donald Allen, Anne Hellebust, Anushka Dikshit. Identifying immune cell phenotypes and their function by using high throughput spatial multiomics [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 5318.

Cancer ResearchVol. 85(8_Supplement_1)
Radiology Associates of Albuquerque (US)
Openalex Percentile: Top 93%
Single-cell and spatial transcriptomics
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