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AUA2022 PRESENTATION: Urological Care for the Advanced Practice Provider Program. Prostate Cancer Biomarkers: What to Choose and When to Use
By: Rachel Hastings, MS, PA-C | Posted on: 01 Oct 2022
Learning Objective
At the conclusion of the activity, participants will be able to identify biomarkers used for initial diagnosis, risk stratification, posttreatment, and advanced disease.
Introduction
In recent years we have seen great strides in the diagnosis and treatment of prostate cancer. As we look to the future, we hope to decrease overdiagnosis and treatment of insignificant cancer, improve detection of clinically significant disease, and further risk stratify patients for appropriate treatment by incorporating the use of biomarkers and new imaging studies.
Until now, PSA has had the greatest impact on diagnosis as well as management, but PSA lacks specificity and relying on PSA alone has been proven to lead to overdiagnosis and overtreatment while still missing significant disease.1 Although we have risk stratification tools and risk calculators incorporating Gleason score/grade and clinical stage, many prostate cancers are multifocal, and may carry a remarkable amount of heterogeneity within or between tumor foci.2 Novel imaging studies and biomarkers will help at all stages of our clinical pathway from initial screening to risk stratification of localized disease as well as serve as prognostic indicators for posttreatment failures and advanced disease.
Biomarker Characterization
A biomarker is a biological molecule that can be objectively measured and evaluated as a sign of a normal or abnormal biological process and pathogenic condition/disease. Currently, we have both urine and blood-based biomarkers for initial screening. There are tissue-based biomarkers available for assessment of treatment escalation or de-escalation following diagnosis, as well as circulating tumor tests and imaging tests for ongoing surveillance. All of these tests are increasingly incorporated into our clinical care paradigm, but how can we use them most effectively?
Biomarkers for Screening and Early Detection
PSA limitations drive our need for more tools aimed at reducing unnecessary biopsies without sacrificing early detection of clinically significant prostate cancer.
In this space, we have both urine- and blood-based biomarkers. These markers help guide screening and detection of clinically significant prostate cancer (Table 1).3-8
Biomarkers for Repeat Biopsy
Biomarkers and imaging studies that help guide decision making regarding repeat biopsy include MRI, ConfirmMDX, PCA3, MyProstateScore, Prostate Health Index, and 4K (Table 2).
As Tables 1 and 2 illustrate, biomarkers in these spaces perform similarly and our choice depends on need, cost, convenience (home vs nursing visit vs provider visit), and patient and practitioner preference. Considerations also include lacking head-to-head studies, interpretation variability based on cutoff values and patient/clinician education, evaluation when on a 5-alpha reductase inhibitors, and validation of translation to improved outcomes. National Comprehensive Cancer Network® (NCCN®) and American Urological Association guidelines do not recommend these tests as first-line screening but state they may be used for patients who require further delineation of risk.9
Table 1. Biomarkers for screening and early detection
Test | Source | Components | NPV | Notes |
---|---|---|---|---|
PSA | Blood | Lacks specificity; can also use fPSA, PSA, DT | ||
PHI | Blood | ProPSA and free PSA | 94% | Reduces unnecessary biopsy; active surveillance monitoring; prediction of csPCa |
4K | Blood | PSA, fPSA, and human kallikrein 2 along with clinical factors | 96% | Reduces unnecessary biopsy; Probability (0%–100%) of csPCa on biopsy |
SelectMDx | Urine (post-DRE) | Gene panel along with clinical factors | 95% for GG2; 99% for GG4 and greater | |
ExoDx™ | Urine | Gene panel of exosomal RNA (ERG, PCA3, and SPDEF) | 95% for GG2; 97% for GG3 and greater | No DRE or clinical factors but does need to be first void; improved identification of high-grade disease |
csPCa, clinically significant prostate cancer. DRE, digital rectal examination. DT, doubling time. fPSA, free PSA. GG, Grade Group. MDx, SelectMDx. PHI, Prostate Health Index. |
Table 2. Biomarkers for repeat biopsy
Test | Source | Components | NPV | Notes |
---|---|---|---|---|
ConfirmMDX | Tissue | Hypermethylation of GSTP1, APC and RASSF1 | 95% | Evaluates for field effect on biopsy |
PCA3 | Urine (post-DRE) | Non-coding mRNA | No correlate with PSA or prostate volume | |
MPS | Urine (post-DRE) | PCA3 and T2:ERG | 98% | Score from 0-11 grouped into low, intermediate, and high categories; prediction for risk of PCa and csPCa |
PHI | Blood | ProPSA and free PSA | 94% | Creates composite score to indicate likelihood of PCa |
4K | Blood | Free PSA, total PSA and human kallikrein 2 along with clinical factors | 96% | Probability (0%-100%) of csPCa on biopsy |
csPCa=clinically significant prostate cancer. DRE=digital rectal examination. MPS=MyProstateScore. PCa=prostate cancer. PHI=Prostate Health Index. |
Biomarkers for Risk Stratification
For patients with localized prostate cancer, current risk stratification methods include PSA kinetics/levels, Gleason score and nomograms/models (Memorial Sloan Kettering Cancer Center, Cancer of the Prostate Risk Assessment), but as we lean further into the space of personalized medicine, genomics may have the potential to further or more accurately delineate risk. This input can potentially impact treatment decision making as well as oncologic outcomes.
In the pretreatment space we have tissue-based biomarkers to help patients decide between active surveillance and treatment, as well as those who may benefit from treatment escalation, ie the addition of androgen deprivation therapy to radiation (Table 3).
These biomarkers can help guide short-term surveillance/treatment, but studies are still ongoing regarding the long-term oncologic benefit. We have seen promise not only in regard to survival but in minimizing treatment related side effects, and this becomes increasingly important as our patients are at younger ages at diagnosis and treatment. Ultimately, the overall clinical picture is more important than any 1 test. Prostate cancer is known to be multifocal as well as heterogeneous. These tissue-based biomarkers sample the highest volume and Grade Group (GG) of disease, but that may not necessarily correlate to the foci that have the most potential for disease progression. Therefore, these results certainly are helpful but likely incomplete.
Tissue-based biomarkers are ideally suited for low and favorable intermediate-risk patients following biopsy and post-radical prostatectomy (RP) patients with pT2 positive margins, pT3, and/or rising PSAs. As experience grows, these tests are increasingly being incorporated into treatment guidelines as they are proving to be beneficial in risk stratification.11-17
Imaging
Currently MRI plays an important role in initial screening (who to biopsy) and active surveillance, as well as monitoring/screening for metastatic disease. MRI allows for a more accurate, targeted biopsy, a practice proven to increase detection of GG2 or greater, but limitations or barriers include negative predictive value (NPV) variation between both radiologists and centers, time, cost, and accessibility. More data are needed on how to integrate biomarkers with MRI.18
Prostate-specific membrane antigen positron emission tomography can be used for initial staging of high-risk disease as well as for biochemical recurrence and for metastatic disease monitoring. Many patients who were M0 by traditional imaging modalities will now be M1. It remains unclear, however, how this will change our treatment paradigms and whether it will ultimately lead to improved outcomes.
Table 3. Biomarkers for risk stratification
Name | Methodology | Indications | Reported Outcomes |
---|---|---|---|
Prolaris | 31 Cell cycle genes | Pretreatment post-RP | Reported on 10-point scale; gives a score % within the patient’s NCCN risk group while providing % risk of 10-yr disease specific mortality and distant mets |
Decipher | 22 RNA markers | Pretreatment post-RP | Independent of clinical and demographic data; provides % risk of distant metastases in 5, 10 yrs; 15-yr disease specific mortality; risk of adverse pathology at RP |
Oncotype | 12 Cancer genes over 4 different pathways | Pretreatment | Numerical score combined with NCCN risk groupings to report comprehensive risk score shown as a % risk of prostate cancer death within 10 yrs, metastasis within 10 yrs and risk of adverse pathology on RP |
RP, radical prostatectomy. |
As prostate-specific membrane antigen positron emission tomography is incorporated into our clinical pathway, we must remember to integrate the entire clinical picture into our decision making as we again see sensitivity variation dependent on PSA, variability between centers, false positives, etc.19,20
Biomarkers for Post-Operation/Treatment
Just as in the pretreatment setting, tissue-based tests such as Prolaris, Oncotype and Decipher as well as imaging studies can have a valuable role in the management of patients following primary treatment (Table 3). In the posttreatment setting, these tests are useful for guiding posttreatment surveillance as well as initiation of adjuvant/salvage treatments.13-17
Biomarkers for Advanced Disease
It is imperative to get an accurate and detailed history on prostate cancer patients as many may qualify for germline testing. Germline testing is recommended for all patients with metastatic disease and should be considered for patients with localized/regional disease but increased risk factors (strong family history, intraductal/cribriform). It has become known that up to 20% of these patients will have unique treatment options based on the testing such as PARP inhibitor or immune checkpoint inhibitor.21
In addition, there has been recent robust interest in emerging biomarkers such as circulating tumor cells for castrate-resistant prostate cancer.
Conclusion
Further characterization of prostate cancer is increasingly important as we strive for more personalized care for our patients. Selection of appropriate biomarkers can be highly nuanced and must be dependent on the clinical picture. Given the complex and heterogenous nature of prostate cancer, 1 biomarker cannot answer all our questions. As always, more research on incorporating our current biomarkers as well as new research is needed. It is important to incorporate these tests into your practice and engage in clinical trials when available. In the early detection pathways, focus is on how these tests can be used with imaging studies and how they perform in diverse populations. Further studies will help guide how to implement our tissue-based tests to aid in treatment decisions for active surveillance or stratification/treatment of intermediate-risk disease. We have seen tremendous recent growth in utilization and development of biomarkers, imaging, and germline testing in the post-primary treatment setting, and as more studies emerge we will further our ability to stratify patients requiring treatment escalation and tailor more personalized treatment options. In the future, biomarkers will continue to enhance our ability to diagnosis and treat patients with prostate cancer above and beyond our current standard diagnostic and prognostic tools.
- Thompson IM, Ankerst DP, Chi C, et al. Operating characteristics of prostate specific antigen in men with an initial PSA level of 3.0 ng/ml or lower. JAMA. 2005;294(1):66-70.
- LØvf M, Zhao S, Axcrona U, et al. Multifocal primary prostate cancer exhibits high degree of genomic heterogeneity. Eur Urol. 2019;75(3):498-505.
- Parekh DJ, Punnen S, Sjoberg DD, et al. A multi-institutional prospective trial in the USA confirms that the 4K score accurately identifies men with high grade prostate cancer. Eur Urol. 2015;68(3);464-470.
- Kim JH, Hong SK. Clinical utility of current biomarkers for prostate cancer detection. Investig Clin Urol. 2021;62(1):1-13.
- Loeb S, Sanda MG, Broyles DL, et al. The prostate health index selectively identifies clinically significant prostate cancer. J Urol. 2015;193(4):1163-1169.
- Haese A, Trooskens G, Steyaert S, et al. Multicenter optimization and validation of a 2-gene mRNA urine test for detection of clinically significant prostate cancer before initial prostate biopsy. J Urol. 2019;202(2):256-263.
- Margolis E, Brown G, Partin A, et al. Predicting high-grade prostate cancer at initial biopsy: clinical performance of the ExoDx (EPI) prostate intelliscore test in three independent prospective studies. Prostate Cancer Prostatic Dis. 2022;25(2):296-301.
- McKiernan J, Noerholm M, Tadigotla V, et al. A urine-based exosomal gene expression test stratifies risk of high-grade prostate cancer in men with prior negative prostate biopsy undergoing repeat biopsy. BMC Urol. 2020;20(1):138.
- NCC Network. Prostate cancer early detection guidelines; Available at https://www.nccn.org/guidelines/guidelines-detail?category=2&id=1460.
- Sathianathen NJ, Kuntz KM, Alarid-Escudero F, et al. Incorporating biomarkers into the primary prostate biopsy setting: a cost-effectiveness analysis. J Urol. 2018;200(6):1215-1220.
- Kim HL, Li P, Huang HC, et al. Validation of the decipher test for predicting adverse pathology in candidates for prostate cancer active surveillance. Prostate Cancer Prostatic Dis. 2019;22(3):399-405.
- Herlemann A, Huang HC, Alam R et al. Decipher identifies men with otherwise clinically favorable-intermediate risk disease who may not be good candidates for active surveillance. Prostate Cancer Prostatic Dis. 2020;23(1):136-143.
- Jairath NK, Dal Pra A, Vince R, et al. A systematic review of the evidence for the decipher genomic classifier in prostate cancer. Eur Urol. 2021;79(3):374-383.
- Ross AE, Feng FY, Ghadessi M, et al. A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy. Prostate Cancer Prostatic Dis. 2014;17(1):64-69.
- Freedland SJ, Choeurng V, Howard L, et al. Utilization of a genomic classifier for prediction of metastasis following salvage radiation therapy after radical prostatectomy. Eur Urol. 2016;70(4):588-596.
- Klein EA, Cooperberg MR, Magi-Galluzzi C, et al. A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling. Eur Urol. 2014;66(3):550-560.
- Van Den Eeden SK, Lu R, Zhang N, et al. A biopsy-based 17-gene genomic prostate score as a predictor of metastases and prostate cancer death in surgically treated men with clinically localized disease. Eur Urol. 2018;73(1):129-138.
- Westphalen AC, McCulloch CE, Anaokar JM, et al. Variability of the positive predictive value of PI-RADS for prostate MRI across 26 centers: experience of the Society of Abdominal Radiology Prostate Cancer Disease-focused panel. Radiology. 2020;296(1):76-84.
- Sonni I, Eiber M, Fendler WP, et al. Impact of 68Ga-PSMA-11 PET/CT on staging and management of prostate cancer patients in various clinical settings: a prospective single-center study. J Nucl Med. 2020;61(8):1153-1160.
- Fendler WP, Ferdinandus J, Czernin J, et al. Impact of 68Ga-PSMA-11 PET on the management of recurrent prostate cancer in a prospective single-arm clinical trial. J Nucl Med. 2020;61(12):1793-1799.
- Thoma C. Targeting DNA repair defects in prostate cancer. Nat Rev Urol. 2020;17(8):432.
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