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Updated: Jun 17, 2025
Author Spotlight: Unlocking Insights into the Immune Cell Landscape of Tumors
Published on: August 18, 2023
The current landscape of spatial biomarkers for prediction of response to immune checkpoint inhibition
Hannah L Williams1, Ana Leni Frei2,3, Thibaud Koessler4,5,6
1Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland. hannah.williams@unibe.ch.
Abstract:
Enabling the examination of cell-cell relationships in tissue, spatially resolved omics technologies have revolutionised our perspectives on cancer biology. Clinically, the development of immune checkpoint inhibitors (ICI) has advanced cancer therapeutics. However, a major challenge of effective implementation is the identification of predictive biomarkers of response. In this review we examine the potential added predictive value of spatial biomarkers of response to ICI beyond current clinical benchmarks.
Insights
Spatially resolved omics reveal cell interactions in cancer. Spatial biomarkers may predict response to immune checkpoint inhibitors (ICI) beyond current clinical standards, improving cancer therapy.
Area of Science:
- Cancer biology
- Immunotherapy
- Biomarker discovery
Background:
- Spatially resolved omics technologies revolutionize cancer biology by enabling examination of cell-cell relationships within tissues.
- Immune checkpoint inhibitors (ICI) represent a significant advancement in cancer therapeutics.
- Identifying predictive biomarkers for ICI response remains a critical clinical challenge.
Purpose of the Study:
- To review the potential added predictive value of spatial biomarkers for ICI response.
- To assess if spatial biomarkers can surpass current clinical benchmarks in predicting treatment efficacy.
Main Methods:
- Literature review of spatially resolved omics technologies.
- Analysis of current clinical biomarkers for ICI response.
- Evaluation of studies investigating spatial biomarkers in the context of ICI therapy.
Main Results:
- Spatial omics provide unprecedented insights into the tumor microenvironment.
- Emerging spatial biomarkers show promise in predicting ICI response.
- Integration of spatial data may enhance current predictive models.
Conclusions:
- Spatial biomarkers hold significant potential to improve patient selection for ICI therapy.
- Further research is needed to validate and integrate spatial biomarkers into clinical practice.
- Harnessing spatial omics data can refine our understanding of immunotherapy response mechanisms.
