Prostate Cancer Biomarkers in 2022: Where Do We Stand, and Where Are We Going?

By: Jeffrey J. Tosoian, MD, MPH | Posted on: 01 Apr 2022

In patients with moderately elevated prostate specific antigen (PSA; ie 3–10 ng/ml), the current diagnostic pathway suggests that clinicians offer magnetic resonance imaging (MRI), if available, and consider biomarker testing to better define risk of clinically significant (Grade Group ≥2) prostate cancer prior to biopsy.¹

Box. Bringing biomarkers to practice: key measures for clinical application

Performance measures like sensitivity, specificity and predictive values are all important for characterizing the potential use of clinical tests. The application of these and other measures to prostate cancer diagnosis have been previously discussed in detail.⁶ In men presenting with moderately elevated PSA, the limitations of PSA drive our clinical need to reduce unnecessary biopsies (ie negative, GG1) without sacrificing consistent early detection of higher-risk cancers. In this diagnostic landscape, 2 performance measures are particularly critical.

NPV: For each individual patient, a high NPV is essential. In an example, 98% NPV means that a patient testing negative has only a 2% likelihood of detecting GG ≥2 cancer on biopsy. This level of certainty will allow the vast majority patients and clinicians to confidently avoid biopsy. By contrast, 90% NPV implies a 10% likelihood of GG ≥2 cancer persists after a negative test, which may not be sufficient to forgo further evaluation. It is worth being familiar with the NPV of existing tests to ensure that a negative test will provide sufficiently low risk for a given patient to comfortably defer biopsy. Notably, predictive values vary by outcome prevalence in the testing population, so risk characteristics of validation data should be aligned with the proposed test setting.

Sensitivity: As clinicians considering practice-wide testing, sensitivity takes on particular importance. Sensitivity reflects the proportion of patients with GG ≥2 cancer that will have a positive test result–and would therefore be correctly directed to biopsy. By contrast, 100% minus sensitivity is the proportion of patients with GG ≥2 cancer that will have a false-negative test and would therefore be incorrectly counseled to forgo biopsy (ie resulting in a missed diagnosis). Practice-wide use of a test with 85% sensitivity means that 15% of biopsy-detectable GG ≥2 cancers presenting to clinic would go undetected, while a test with 95% sensitivity would fail to detect only 5%. Unlike predictive values, sensitivity and specificity are intrinsic measures of each test and can be considered across various clinical settings.

The relative merits of MRI and biomarker testing can be debated indefinitely, and the likely reality is that a clinical role exists for both tools. Unlike biomarker tests, MRI allows clinicians to target visible lesions at biopsy, a practice shown to increase detection of GG ≥2 cancer relative to systematic biopsy.² By contrast, variability of MRI interpretation across practice settings is problematic when considering population-wide adoption of MRI.³ While pooled data reflect a negative predictive value (NPV) of 90.8% for MRI at experienced academic centers, NPVs at individual sites were as low as 62%, and there were insufficient data from nonacademic settings for analysis–a consistent limitation of the MRI literature.^3,4

Considered with other practical limitations of MRI (eg access; time, labor, and cost of testing), objectively measured biomarkers obtainable in clinic could be more practical for initial testing after PSA. While several biomarkers are commercially available for use in this setting, initial validation studies had notable deficiencies in reporting transparency and methodologies for guiding clinical use (eg threshold validation).⁵ The net result was a body of biomarker data that showed consistent improvement relative to PSA, but that in many cases failed to provide clear, validated, evidence-based applications for clinical use.^5,6

Where We Stand

A recent review from Eyrich et al assessed validation data for commercially available biomarker assays, with a focus on test sensitivity and specificity for GG ≥2 cancer (table 1).⁶ Limitations notwithstanding, the data reflect multiple biomarker tests capable of ruling out the need for 30%–50% of unnecessary biopsies (ie negative, GG1), while maintaining high sensitivity–in some cases exceeding 95%. The box summarizes performance measures critical to determining how biomarker tests could best fit within your clinical practice.

Table 1. Commercially available prostate cancer biomarker tests⁶

Biomarker Test	Components	Clinical Factors	Specimen
4Kscore	PSA, fPSA, iPSA, hK2	Age, prior biopsy, ± digital rectal examination	Blood
Prostate Health Index (phi)	PSA, proPSA, fPSA	None	Blood
SelectMDx	HOXC6, DLX1, PSA	Age, digital rectal examination, prostate vol	Urine
ExoDx Prostate Intelliscore (EPI)	PCA3, ERG, SPDEF	None	Urine
MyProstateScore (MPS)	PCA3, T2:ERG, PSA	None	Urine

Encouragingly, the past year has witnessed an increase in coordinated efforts to provide actionable, data-driven applications of biomarker tests in pertinent clinical scenarios. In addition to initial and repeat biopsy populations, recent analyses have assessed biomarker use in settings and populations in great need of additional tools: during the course of active surveillance, following equivocal MRI, and in African American men underrepresented in most validation data.⁷ Most importantly, at least two prospective clinical trials are underway to better define the optimal combined use of biomarkers and MRI.^8,9

“The relative merits of MRI and biomarker testing can be debated indefinitely, and the likely reality is that a clinical role exists for both tools.”

Table 2. The evolution of biomarkers in localized prostate cancer

Generation	Biological Specificity	Example(s)
First	Prostatic epithelium	PSA
Second	Prostate cancer	Kallikrein-family proteins, ETS-related transcription factors, PCA3
Third	High-grade prostate cancer	SChLAP1, PCATs
After early use of serum PAP in metastatic prostate cancer, PSA emerged as a “first generation” biomarker to aid in detecting localized disease. The limitations of PSA are rooted in its biological specificity for prostatic epithelial cells rather than prostate cancer cells. Thus, a second generation of biomarkers emerged, characterized by increased specificity for cancer. Commercially available tests based on these markers have consistently outperformed PSA yet remain imperfect markers of clinically significant, higher-grade cancers. In light of this, a third generation of biomarkers–with biological specificity for high-grade, potentially lethal cancer–offers extraordinary promise.¹⁰ Building on recent discovery, ongoing efforts between our team at Vanderbilt University Medical Center, the University of Michigan and collaborating National Cancer Institute–Early Detection Research Network centers are aimed at driving this next step toward diagnostic certainty.

Where We Are Going

In addition to mounting evidence for existing tests, there is reason to believe that the next generation of prostate cancer biomarkers could provide a level of precision capable of transforming the diagnostic pathway (table 2). With a universal goal to minimize harm due to prostate cancer, further developing data-driven guidelines for biomarker testing is critical. As these data continue to mature, there is hope that the practical limitations of diagnostic MRI can be improved in parallel. Moreover, a local coverage determination planned for release in 2022 should help clarify reimbursement policies for diagnostic biomarker testing in the U.S. Arming clinicians with multiple evidence-based applications of diagnostic tools will ultimately provide the best outcomes for our patients.

Carroll P, Parsons J, Box G et al: NCCN Clinical Practice Guidelines in Oncology: Prostate Cancer Early Detection. 2021; v2.2021. Available at https://www.nccn.org/professionals/physician_gls/pdf/prostate_detection.pdf. Accessed January 3, 2022.
Ahdoot M, Wilbur AR, Reese SE et al: MRI-targeted, systematic, and combined biopsy for prostate cancer diagnosis. N Engl J Med 2020; 382: 917.
Sathianathen NJ, Omer A, Harriss E et al: Negative predictive value of multiparametric magnetic resonance imaging in the detection of clinically significant prostate cancer in the prostate imaging reporting and data system era: a systematic review and meta-analysis. Eur Urol 2020; 78: 402.
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: 76.
Narayan VM: A critical appraisal of biomarkers in prostate cancer. World J Urol 2020; 38: 547.
Eyrich NW, Morgan TM and Tosoian JJ: Biomarkers for detection of clinically significant prostate cancer: contemporary clinical data and future directions. Transl Androl Urol 2021; 10: 3091.
AUA Annual Meeting Program Abstracts 2021. J Urol 2021; 206: e1–e1181. Available at https://www.auajournals.org/toc/juro/206/Supplement+3. Accessed January 20, 2022.
EDRN Prostate MRI Biomarker Study (P-MRI). ClinicalTrials.gov. Available at https://clinicaltrials.gov/ct2/show/NCT03784924. Accessed January 22, 2022.
Predicting Prostate Biopsy Results With Biomarkers and mpMRI (ProBioM). ClinicalTrials.gov. Available at https://clinicaltrials.gov/show/NCT03730324. Accessed January 22, 2022.
Prensner JR, Iyer MK, Sahu A et al: The long noncoding RNA SChLAP1 promotes aggressive prostate cancer and antagonizes the SWI/SNF complex. Nat Genet 2013; 45: 1392.