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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
PubMed
Summary
This summary is machine-generated.

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.

Keywords:
expression signaturesheterogeneityprognostic biomarkersprostate cancerspatial transcriptomics

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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.