Spatial multiomics reveals T-cell activation and exhaustion states in the tumor microenvironment 3446

Abstract Description Spatial Multiomics allows for context-based study of the tumor microenvironment (TME). TME consists of diverse cells that collectively influence tumor progression and immune activation. CD8 T-cells, essential for antitumor immunity, often become exhausted in the TME. PD1+ TCF1+ stem-like CD8 T-cells retains differentiation potential and can be rejuvenated through cytokine signaling and immune checkpoint modulation. Here we introduce a workflow for RNAscope™ Multiplex Fluorescent v2 assay combining RNA in-situ hybridization (ISH) and protein immunofluorescence to study cell marker (CD8, PD1) with RNA targets (TNFA, TCF7, IFNG) in a tumor microarray (TMA). The Manual Multiplex Protease-Free workflow enables simultaneous RNA and protein visualization without enzymatic disruption, preserving antigen integrity and tissue morphology. Using this Multiomics assay, we can study CD8 T-cell differentiation and activation. Co-detection of RNA transcripts and proteins provides insights into specific T cell phenotypes and their activation/exhaustion status. Data reveal robust co-expression patterns of these targets, particularly in the tumor-cell neighboring stromal and immune cells in breast, cervical and stomach cancers, reflecting immune activation and exhaustion across distinct TME niches. This methodology lays a foundation for refining immunotherapeutic strategies targeting PD1+ TCF7+ CD8 T-cells, enhancing effector functions, and advancing precision oncology interventions. Topic Categories Tumor Immunology: Cellular Responses and Tumor Microevironment (TIME)

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Publication Details

Journal
The Journal of Immunology
Published
2025-11-01
DOI
https://doi.org/10.1093/jimmun/vkaf283.1251
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

Spatial multiomics reveals T-cell activation and exhaustion states in the tumor microenvironment 3446

Li-Chong Wang, Steve Zhou, Debia Wakhloo, Anushka Dikshit et al.
The Journal of Immunology
Single-cell and spatial transcriptomics
article

Spatial multiomics reveals T-cell activation and exhaustion states in the tumor microenvironment 3446

Li-Chong Wang, Steve Zhou, Debia Wakhloo, Anushka Dikshit, Maithreyan Srinivasan, Yifan Wang
article en

Abstract

Abstract Description Spatial Multiomics allows for context-based study of the tumor microenvironment (TME). TME consists of diverse cells that collectively influence tumor progression and immune activation. CD8 T-cells, essential for antitumor immunity, often become exhausted in the TME. PD1+ TCF1+ stem-like CD8 T-cells retains differentiation potential and can be rejuvenated through cytokine signaling and immune checkpoint modulation. Here we introduce a workflow for RNAscope™ Multiplex Fluorescent v2 assay combining RNA in-situ hybridization (ISH) and protein immunofluorescence to study cell marker (CD8, PD1) with RNA targets (TNFA, TCF7, IFNG) in a tumor microarray (TMA). The Manual Multiplex Protease-Free workflow enables simultaneous RNA and protein visualization without enzymatic disruption, preserving antigen integrity and tissue morphology. Using this Multiomics assay, we can study CD8 T-cell differentiation and activation. Co-detection of RNA transcripts and proteins provides insights into specific T cell phenotypes and their activation/exhaustion status. Data reveal robust co-expression patterns of these targets, particularly in the tumor-cell neighboring stromal and immune cells in breast, cervical and stomach cancers, reflecting immune activation and exhaustion across distinct TME niches. This methodology lays a foundation for refining immunotherapeutic strategies targeting PD1+ TCF7+ CD8 T-cells, enhancing effector functions, and advancing precision oncology interventions. Topic Categories Tumor Immunology: Cellular Responses and Tumor Microevironment (TIME)

The Journal of ImmunologyVol. 214(Supplement_1)
Advanced Cell Diagnostics (United States) (US)
Openalex Percentile: Top 68%
Single-cell and spatial transcriptomics
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