Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer
Abstract
:1. Introduction
2. Discussion
2.1. 8th AJCC Changes for Prostate Cancer Staging
2.2. Molecular Biomarkers and Gene Alterations in Prostate Cancer
2.3. Novel Biomarkers Integrated into Risk Assessment Models for Prostate Cancer Screening and Prognostication
2.3.1. Prolaris
2.3.2. 4K-score and European Randomized Study of Screening for Prostate Cancer Rotterdam Prostate Cancer Risk Calculator (ERSPC RPCRC)
2.3.3. PCA3
2.3.4. SelectMDx
2.4. What Strategies Can Avoid Unnecessary MRI, Biopsies, and Diagnosis of Low Risk Prostate Cancer?
2.5. Biomarkers to Guide Decision for Active Surveillance
2.6. Biomarkers to Predict Recurrence after Radical Prostatectomy
2.7. Future Potential Perspectives
3. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Test | Type of Tissue | Genes/Biomarkers Encoded | Tool in Risk Assessment | Utility | Result |
---|---|---|---|---|---|
Prolaris | Biopsy | 31 CCP + 15 reference genes | Combined with age, PSA, clinical stage, % positive cores, Gleason score, AUA risk category | Decision making: Active surveillance vs. Treatment | Higher score implies higher risk of cancer progression/independent predictor of prostate cancer death. |
Radical Prostatectomy | Combined with PSA, Gleason score, pathologic features of surgical specimen. | Prognostication/Need for adjuvant therapy | Predicts 10-year risk of BCR after radical prostatectomy | ||
4-K Score | Blood | 4 biomarkers: free PSA, total PSA, intact PSA, and human glandular kallikrein 2 (hk2) | Combined with ERSPC RPCRC risk calculator | Screening | Predicts presence of clinically significant prostate cancer |
PCA3 | Urine after DRE | Prostate Cancer Antigen 3 | Combined with PSA, DRE, and risk calculator | Screening | Predicts presence of clinically significant prostate cancer: (a) On initial biopsy (b) Avoids unnecessary re-biopsy in patients with an initial negative biopsy. |
Select MDx | Urine after DRE | HOXC6 and DLX1 genes | Combined with MRI, PSA, DRE, prostate volume, age, family history | Screening | Predicts presence of clinically significant prostate cancer: (a) Avoids detection of low risk prostate cancer (b) Avoids unnecessary re-biopsy |
Stockholm-3 Model (S3M) | 232 genetic polymorphisms + protein biomarkers (fPSA, iPSA) | Combined with age, DRE | Screening + patient selection: which patients deserve MRI +/− Biopsy. | Predicts presence of clinically significant prostate cancer (a) Avoids detection of low risk prostate cancer (b) Avoids unnecessary MRI +/- Biopsy | |
Oncotype Dx | Prostate biopsy | 17 gene assay | Combined with CAPRA score | Decision making: Active surveillance vs. Treatment | Predicts high risk (stage & grade) disease upon eventual radical prostatectomy |
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Saoud, R.; Heidar, N.A.; Cimadamore, A.; Paner, G.P. Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer. Cells 2020, 9, 2116. https://doi.org/10.3390/cells9092116
Saoud R, Heidar NA, Cimadamore A, Paner GP. Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer. Cells. 2020; 9(9):2116. https://doi.org/10.3390/cells9092116
Chicago/Turabian StyleSaoud, Ragheed, Nassib Abou Heidar, Alessia Cimadamore, and Gladell P. Paner. 2020. "Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer" Cells 9, no. 9: 2116. https://doi.org/10.3390/cells9092116