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Prediction of Clinically Significant Prostate Cancer by a Specific Collagen-related Transcriptome, Proteome, and
Isabel Heidegger1, Maria Frantzi2, Stefan Salcher3
1Department of Urology, Medical University of Innsbruck, Innsbruck, Austria.
European Urology Oncology
|June 9, 2024
Summary
Collagen signatures in prostate cancer (PCa) tissue and urine accurately detect clinically significant PCa (csPCa). These findings, particularly from urine analysis, show promise for improving PCa diagnosis and reducing unnecessary biopsies.
Area of Science:
- Oncology
- Biochemistry
- Genomics
Background:
- Collagen density is linked to poor outcomes in various cancers, but its role in prostate cancer (PCa) is not well understood.
- Clinically significant PCa (csPCa) detection relies on accurate diagnostic markers.
Purpose of the Study:
- To investigate collagen-related alterations in transcriptome, proteome, and urinome for csPCa detection.
- To evaluate the diagnostic performance of collagen signatures against established markers like prostate-specific antigen (PSA) and multiparametric magnetic resonance imaging (mpMRI).
Main Methods:
- Analysis of PCa transcriptome (n=1393), proteome (n=104), and urinome (n=923) data focusing on 55 collagen-related genes.
- Utilized single-cell RNA sequencing to identify cellular sources of collagen transcripts.
- Employed statistical evaluations, clustering, and machine learning models to identify csPCa signatures.
Main Results:
- Differential expression of 30 collagen genes and 34 proteins was observed in csPCa compared to benign or low-grade tissues.
- A collagen-high cancer cluster showed distinct cellular and molecular features, including fibroblast infiltration and enhanced signaling pathways.
- Collagen-based machine learning models outperformed PSA and age, demonstrating performance comparable to mpMRI in predicting csPCa.
- A urinome-based collagen model identified csPCa in 4 out of 5 cases with equivocal PI-RADS 3 lesions.
Conclusions:
- Collagen-related signatures in tissue and urine accurately predict csPCa.
- These signatures offer superior accuracy to PSA and age for csPCa detection.
- Collagen signatures, especially from urine, show potential as a liquid biopsy tool to reduce unnecessary biopsies and improve diagnostic precision for PCa risk stratification.
