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Spatial Robustness of Prostate Cancer Biomarkers Evaluated by Spatial Transcriptomics
Kristofer G Taylor1,2, Bjarne Johannessen1, Ian G Mills3,4
1Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital-Radiumhospitalet, Oslo, Norway.
The Prostate
|March 30, 2026
Summary
Spatial transcriptomics reveals significant gene expression variability in localized prostate cancer. Several Oncotype DX genes showed spatial patterns, offering potential for more robust prognostic panels despite heterogeneity.
Area of Science:
- Genomics and Molecular Biology
- Cancer Research
- Spatial Biology
Background:
- Bulk sequencing prognostic biomarker panels are useful for localized prostate cancer but limited by tumor heterogeneity.
- Spatial transcriptomics can analyze gene expression patterns and localization within tissue microenvironments.
Purpose of the Study:
- To investigate spatial gene expression of biomarker genes from established prognostic panels in localized prostate cancer.
- To assess the utility of spatial transcriptomics in understanding biomarker localization and variability within heterogeneous tumors.
Main Methods:
- Analyzed biomarker genes from four prognostic panels (Oncotype DX, Prolaris, Decipher, ProClass) using Visium Spatial Platform on 37 tissue sections from two high-grade prostate cancer patients.
- Quantified gene abundance, assessed spatial variability (Moran's I), and identified localization via spatial co-expression network analysis.
Main Results:
- Significant variation in tissue composition and biomarker gene expression was observed across sections.
- Several Oncotype DX and Decipher genes demonstrated consistent spatial variability; Prolaris and ProClass genes showed limited expression.
- Spatial co-expression network analysis linked Oncotype DX genes to stromal networks and Decipher genes to diverse networks.
Conclusions:
- Spatial transcriptomics demonstrates proof-of-concept for analyzing prognostic biomarker panels in heterogeneous prostate cancer.
- Spatially variable Oncotype DX genes predominantly localized to stromal regions, suggesting potential for spatially informed prognostic panels.
- Integrating spatial data may overcome limitations of current panels and improve prognostic reliability in the context of molecular heterogeneity.
