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Updated: May 15, 2025

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
Published on: March 25, 2020
Integrated single-cell and spatial analysis identifies context-dependent myeloid-T cell interactions in head and neck
Athena E Golfinos-Owens1, Taja Lozar1,2,3, Parth Khatri1,4
1McArdle Laboratory for Cancer Research, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792.
Background:
Approximately 15-20% of head and neck cancer squamous cell carcinoma (HNSCC) patients respond favorably to immune checkpoint blockade (ICB). Previous single-cell RNA-Seq (scRNA-Seq) studies identified immune features, including macrophage subset ratios and T-cell subtypes, in HNSCC ICB response. However, the spatial features of HNSCC-infiltrated immune cells in response to ICB treatment need to be better characterized.
Methods:
Here, we perform a systematic evaluation of cell interactions between immune cell types within the tumor microenvironment using spatial omics data using complementary techniques from both 10X Visium spot-based spatial transcriptomics and Nanostring CosMx single-cell spatial omics with RNA gene panel including 435 ligands and receptors. In this study, we used integrated bioinformatics analyses to identify cellular neighborhoods of co-localizing cell types in single-cell spatial transcriptomics and proteomics data. In addition, we used both publicly available scRNA-Seq and in-house spatial RNA-Seq data to identify spatially constrained Ligand-Receptor interactions in Responder patients.
Results:
With 522,399 single cells profiled with both RNA and protein from 26 patients, in addition to spot-resolved spatial RNA-Seq from 8 patients treated with ICB together with bioinformatics analysis of publicly available single-cell and bulk RNA-Seq, we have identified a spatial and cell-type specific context-dependency of myeloid and T cell interaction difference between Responders and Non-Responders. We defined further cellular neighborhood and the sources of chemokine CXCL9/10-CXCR3 interactions in Responders, emerging targets in ICB, as well as CXCL16-CXCR6, CCL4/5-CCR5, and other underappreciated and potential markers and targets for ICB response in HNSCC. In addition, we have contributed a rich data resource of cell-cell Ligand Receptor interactions for the immunotherapy and HNSCC research community.
Discussion:
Our work provides a comprehensive single-cell and spatial atlas of immune cell interactions that correlate with response to ICB in HNSCC. We showcase how integrating multiple technologies and bioinformatics approaches can provide new insights into potential immune-based biomarkers of ICB response. Our results suggested refining future studies using preclinical animal models in a more context-specific manner to elucidate potential underlying mechanisms that lead to improved ICB responses.
Insights
This study reveals spatial immune cell interactions in head and neck cancer (HNSCC) that predict response to immune checkpoint blockade (ICB). Identifying these spatial features offers new biomarkers for improving ICB therapy effectiveness in HNSCC patients.
Area of Science:
- Immunology
- Oncology
- Genomics
Background:
- Head and neck squamous cell carcinoma (HNSCC) exhibits variable response to immune checkpoint blockade (ICB), with only 15-20% of patients benefiting.
- Previous studies using single-cell RNA sequencing (scRNA-Seq) highlighted immune cell subsets in HNSCC ICB response, but spatial characteristics remain underexplored.
Purpose of the Study:
- To systematically evaluate spatial immune cell interactions within the tumor microenvironment of HNSCC patients undergoing ICB treatment.
- To identify spatial biomarkers and cellular neighborhoods associated with ICB response in HNSCC.
Main Methods:
- Integrated spatial omics (10X Visium and Nanostring CosMx) and single-cell RNA sequencing (scRNA-Seq) data from HNSCC patients.
- Bioinformatics analyses to define cellular neighborhoods and spatially constrained ligand-receptor interactions.
- Profiling of 522,399 single cells for RNA and protein, alongside spatial transcriptomics from 8 patients.
Main Results:
- Identified spatial and cell-type specific differences in myeloid and T cell interactions between ICB responders and non-responders.
- Defined cellular neighborhoods and pinpointed key chemokine interactions (e.g., CXCL9/10-CXCR3, CXCL16-CXCR6, CCL4/5-CCR5) associated with ICB response.
- Generated a comprehensive dataset of ligand-receptor interactions for the immunotherapy and HNSCC research community.
Conclusions:
- The study provides a spatial atlas of immune cell interactions correlating with ICB response in HNSCC.
- Integration of multi-omics technologies and bioinformatics offers novel insights into potential immune-based biomarkers for ICB therapy.
- Results suggest refining future preclinical studies for a more context-specific understanding of ICB response mechanisms.

