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Author Spotlight: Unlocking Insights into the Immune Cell Landscape of Tumors
Published on: August 18, 2023
Spatial insights into immunotherapy response in non-small cell lung cancer (NSCLC) by multiplexed tissue imaging
James Monkman1, Afshin Moradi1, Joseph Yunis1,2
1Faculty of Medicine, Frazer Institute, The University of Queensland, 37 Kent Street, Woolloongabba, Brisbane, QLD, 4102, Australia.
Abstract:
The spatial localisation of immune cells within tumours are key to understand the intercellular communications that can dictate clinical outcomes. Here, we demonstrate an analysis pipeline for highly multiplexed CODEX data to phenotype and profile spatial features and interactions in NSCLC patients that subsequently received PD1 axis immunotherapy. We found that regulatory T cells (Tregs) are enriched in non-responding patients and this was consistent with their localization within stromal and peripheral tumour-margins. Proximity-based interactions between Tregs and both monocytes (p = 0.009) and CD8+ T cells (p = 0.009) were more frequently found in non-responding patients, while macrophages were more frequently located in proximity to HLADR+ tumour cells (p = 0.01) within responding patients. Cellular neighbourhoods analysis indicated that both macrophages (p = 0.003) and effector CD4+ T cells (p = 0.01) in mixed tumour neighbourhoods, as well as CD8+ T cells (p = 0.03) in HLADR+ tumour neighbourhoods were associated with favorable clinical response. Evaluation of the inferred regulatory functions between immune cells relative to the tumour suggested that macrophages exhibit an immunosuppressive phenotype against both CD4+ and CD8+ T cells, and that this association scores more highly in ICI refractory patients. These spatial patterns are associated with overall survival in addition to ICI response and may thus indicate features for the functional understanding of the tumour microenvironment.
Insights
Spatial analysis of immune cells in non-small cell lung cancer (NSCLC) reveals key interactions. Regulatory T cells (Tregs) in non-responders and specific immune cell neighborhoods in responders correlate with immunotherapy outcomes.
Area of Science:
- Immunology
- Computational Biology
- Oncology
Background:
- Immune cell spatial localization within tumors is crucial for understanding intercellular communication and clinical outcomes.
- Non-small cell lung cancer (NSCLC) patient responses to PD-1 axis immunotherapy are influenced by the tumor microenvironment.
- Highly multiplexed imaging techniques enable detailed profiling of cellular interactions.
Purpose of the Study:
- To develop and apply an analysis pipeline for highly multiplexed CODEX data in NSCLC patients.
- To phenotype and profile spatial features and immune cell interactions in relation to PD-1 axis immunotherapy response.
- To identify spatial patterns associated with clinical outcomes and overall survival.
Main Methods:
- Utilized a CODEX data analysis pipeline for spatial feature and interaction profiling.
- Performed proximity-based interaction analysis between immune cell types and tumor cells.
- Conducted cellular neighborhoods analysis to assess immune cell clustering and associations with response.
- Inferred regulatory functions between immune cells and tumor cells.
Main Results:
- Regulatory T cells (Tregs) were enriched in non-responding NSCLC patients, localized in stromal and peripheral tumor margins.
- Proximity interactions between Tregs and monocytes/CD8+ T cells were more frequent in non-responders.
- Macrophages were found near HLADR+ tumor cells in responders; specific immune cell neighborhoods (macrophages, CD4+ T cells, CD8+ T cells) were associated with favorable response.
- Macrophages exhibited an immunosuppressive phenotype against CD4+ and CD8+ T cells, particularly in immunotherapy-refractory patients.
Conclusions:
- Spatial immune cell distribution and interactions significantly impact NSCLC patient response to PD-1 axis immunotherapy.
- Specific immune cell neighborhoods and interactions, such as Treg enrichment or macrophage immunosuppression, can predict clinical outcomes.
- These findings highlight potential biomarkers for immunotherapy response and offer insights into tumor microenvironment function.
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