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Multimodal Biomarkers That Predict the Presence of Gleason Pattern 4: Potential Impact for Active Surveillance
D M Berman1,2, A Y Lee3, R Lesurf3,4
1Queen's University Cancer Research Institute, Kingston, Ontario, Canada.
The Journal of Urology
|May 1, 2023
Summary
New multimodal biomarkers accurately distinguish clinically significant prostate cancer (grade group ≥2) from indolent types. These molecular tools enhance active surveillance protocols by improving cancer grading and patient selection.
Area of Science:
- Oncology
- Molecular Diagnostics
- Genomics
Background:
- Active surveillance protocols for prostate cancer are challenged by latent grade group ≥2 disease.
- Current molecular biomarkers for active surveillance primarily utilize RNA or protein data.
Purpose of the Study:
- To develop and validate multimodal molecular biomarkers (mRNA, DNA methylation, DNA copy number) for improved differentiation of grade group 1 from grade group ≥2 prostate cancers.
- To enhance the accuracy of active surveillance protocols by refining patient selection.
Main Methods:
- Trained and validated two distinct classifiers, PRONTO-e and PRONTO-m, using training (n=333) and validation (n=202) cohorts of low- and intermediate-risk prostate cancer patients.
- Profiled mRNA abundance, DNA copy number alterations, and DNA methylation sites.
- Evaluated classifier performance in predicting pathological grade group ≥2 in radical prostatectomy specimens.
Main Results:
- PRONTO-e (353 mRNA and copy number features) and PRONTO-m (94 multimodal features) demonstrated high accuracy in independent validation.
- PRONTO-e achieved a true-positive rate of 0.81 and false-positive rate of 0.43; PRONTO-m achieved 0.76 and 0.26, respectively.
- Both classifiers outperformed the CAPRA risk calculator in identifying upgrading cases and were resistant to sampling error.
Conclusions:
- Developed and validated two novel grade group classifiers integrating RNA and DNA features with superior accuracy.
- These classifiers hold potential to refine active surveillance selection in biopsy samples, thereby extending treatment-free survival and surveillance intervals.
