Biomarkers are molecules that can be used in various PCa scenarios, based on the presence of specific cell types, proteins, metabolites, RNA, DNA mutations, polymorphisms, or epigenetic modifications [
28]. Their implementation in PCa has rapidly expanded in the last decade. We previously have described the role of biomarkers in active surveillance [
29] and predicting metastatic disease in prostate cancer [
30]. While PSA is a widely used tumor marker in this context, it is not cancer-specific, so elevated PSA levels can often be due to other conditions such as benign prostatic hyperplasia or inflammatory/infectious processes of the prostate. In this context, other molecular markers have been sought for use in PCa, leading to the study of genomic markers.
There are three scenarios in which biomarkers can be used in prostate cancer: in early detection, recent diagnosis, and post-treatment. For these purposes, biomarkers can assess patients who will require biopsy, select patients for active surveillance or radical therapies, and can be used for adjuvant therapies after curative therapies in patients at high risk of progression.
In this review, we will focus mainly on their utility in evaluating BCR post RP. The following biomarkers will be addressed in this review:
1.4.1. Prolaris (Myriad Genetics, Salt Lake City, UT, USA):
A genomic expression marker that evaluates 31 cell cycle progression (CCP) genes and 15 housekeeping genes, both in pre-biopsy and post-RP specimens. This biomarker was initially developed for breast cancer studies, later being validated for PCa. The test is performed on prostate biopsies for patients with recent PCa diagnosis (Prolaris biopsy test) and on post-RP specimens (Prolaris post-prostatectomy test). The latter reports the risk of biochemical recurrence at 10 years [
31]. The CCP score is an indicator of proliferative index, which reports a range from 0 to 10. A higher score indicates a more aggressive cancer and a higher risk of disease progression. A one-unit increase is reflected in a doubling of the gene expression level, suggesting a more aggressive tumor [
31].
The utility of Prolaris was first reported in a retrospective [
32], where there were two cohorts, on one side 366 patients underwent RP and on the other hand, 337 underwent conservative management with transurethral resection of the prostate (TUR-P). The primary endpoint was to evaluate the time to biochemical recurrence for the post-RP cohort and the time to cancer death for the post-TUR-P cohort. In this study, it was found that the CCP score was associated with a higher risk of BCR (HR 1.77, 95% CI 1.40-2.22, p<0.001) in the post-RP cohort and PCSM in the TUR-P cohort (HR 2.57, 95%CI 1.93-3.43, p<0.001) [
32]. A study by Koch et al. showed that men with higher CCP scores who had BCR post RP had a higher risk of systemic disease, suggesting that this patient population could benefit from early adjuvant therapy [
33].
The Prolaris post-prostatectomy test was subsequently validated in another independent cohort of 413 men in 2013. In this study, it was demonstrated that when clinical-pathological factors are controlled, the CCP score was a strong predictor of BCR (HR 2.1, 95%CI 1.6 to 2.9, p<0.001). Based on these findings, Prolaris can be used to select patients who are post-RP candidates for adjuvant therapy [
34].
Several studies have demonstrated an association with BCR and PCSM, rather than a recommendation for specific treatments. Brishoff et al. [
35], retrospectively applied this score to needle biopsies of men undergoing RP and demonstrated that Prolaris is an independent predictor of biochemical recurrence (HR per score unit 1.47, 95%CI 1.23-1.76, p<0.001) and metastatic progression (HR per score unit 4.19, 95%CI 2.08-8.45, p<0.001) [
35].
Regarding the use of this biomarker to change treatment behavior in PCa, the PROCEDE-1000 study, a prospective registry with nearly 1,600 participants, showed that the CCP score resulted in a treatment change for 47.8% of patients [
36]. More specifically, treatment was escalated in 25% of cases and de-escalated in 75%.
Despite this, there are still no prospective data showing clinical superiority when changes in behavior are guided by this specific test [
36]. In the latest updates of the clinical guidelines, the EAU [
23] mentions that this test still lacks sufficient evidence to be used routinely in the BCR scenario, however, it suggests its use in the decision to perform active surveillance (AS) or to intensify therapies with androgen deprivation therapy (ADT) in PCa. In the case of the NCCN [
18], the Panel recommends it in a similar context. According to the above, further randomized prospective studies are required to recommend this biomarker in the BCR scenario.
1.4.2. Oncotype Dx Prostate (Genomic Health, Redwood City, CA, USA):
Marker that uses 12 genes related to cancer in 4 biological pathways (stromal response, androgen signaling, proliferation, and cellular organization) and 5 guardian genes to predict aggressiveness based on pathological findings in radical prostatectomy. The test provides the Genomic Prostate Score (GPS) on a scale of 0 to 100, which corresponds to an increased risk of adverse pathology post RP.
This test was originally used in the context of breast cancer and was later adapted for PCa, and was approved for use in this scenario in 2013. Unlike other biomarkers that are only associated with long-term clinical outcomes, GPS can also predict adverse tumor pathology (extraprostatic extension, positive surgical margins, and seminal vesicle invasion).
In a study by Cullen et al. [
37], 431 post-RP biopsies were analyzed to assess the relationship between GPS score and oncological outcomes. It was found that GPS was a predictor of BCR (for each 20-unit increase in GPS, HR 2.73, 95% CI 1.84-3.96, p<0.001) as well as a significant predictor of metastasis-free survival (HR/20 units 3.83, 95% CI 1.13-12.60, p=0.032) in univariate analysis. Furthermore, GPS was found to be associated with adverse pathology (primary Gleason 4 or any pattern 5 and/or pT3) after adjusting for NCCN risk (OR/20 3.23, 95% CI 2.14-4.97, p<0.001).
Covas et al. [
38] evaluated 749 patients who underwent the Oncotype DX assay followed by radical prostatectomy (RP), demonstrating a significant association between GPS and adverse pathology post-RP. In a multivariate analysis, for every 20-point change in GPS, GPS was an independent factor for extraprostatic extension (OR 1.8, 95% CI, 1.4-2.3) and seminal vesicle invasion (OR 2.1, 95% CI 1.3-3.4).
Regarding clinical decision change based on the use of Oncotype DX, Badani et al. conducted a prospective study of 158 men with very low to low-intermediate risk, resulting in a change in clinical management in 18% of cases. Specifically, AS increased from 41 to 51%, RP decreased from 21 to 19%, and EBRT decreased by 33% [
39].
The NCCN [
18] and EAU [
23] guidelines recommend this biomarker in specific situations as mentioned earlier for Prolaris. However, the American Society of Clinical Oncology (ASCO) [
40] guidelines discourage its routine use, recommending it only when its results, combined with other clinical factors, may lead to a change in clinical behavior. Similarly to Prolaris, its use in BCR is not recommended by ASCO, and further prospective studies are needed to demonstrate the consequences of its use regarding oncological outcomes.
1.4.3. Decipher (Genome Dx Biosciences based in Vancouver, BC, Canada, and Mayo Clinic):
a 22-gene genomic classifier initially developed for the post-RP setting. It applies a whole-transcriptome microarray analysis using a random forest algorithm based on the expression of 22 RNA biomarkers related to androgen receptor signaling, cell proliferation, differentiation, motility, and immune modulation.
The Decipher score ranges from 0 to 1, with higher values indicating more aggressive disease, with cutoff points of 0.45 and 0.60 to categorize patients as low, intermediate, and high risk. Decipher was approved in the United States to assess the risk of BCR or clinical progression (metastasis) in post-RP patients with adverse pathology (pT3 and/or positive margins or biochemical failure) or for PSA recurrence during follow-up [
41,
42].
Decipher has been applied in scenarios where management change is possible, including low-risk disease (conservative therapy vs. radical treatment), intermediate disease (to guide the addition of androgen deprivation therapy to radiotherapy), post-RP scenario (to guide adjuvant radiotherapy), post-RP recurrence (to guide the addition of androgen deprivation therapy with salvage radiotherapy), and more advanced scenarios (hormone-sensitive metastatic and non-metastatic hormone-resistant), where low GC values predict a more favorable prognosis and may change the addition of intensifying treatment [
43].
In a systematic review, it was demonstrated that in patients with high-risk disease in GC with BCR, the biomarker proved to be an independently associated factor in developing metastatic disease and PCSM [
43]. A prospective study revealed that within patients with high GC risk, those who underwent adjuvant radiotherapy had a lower PSA recurrence at 2 years compared to those who did not receive adjuvant radiotherapy (3% vs 25%, p=0.013). However, there were no differences at 2 years between those who underwent observation versus those who received adjuvant radiotherapy within patients with low-intermediate GC risk (3% versus 0.5%, p=0.77) [
44].
The studies conducted by Berlin et al. [
45] and the post hoc analyses of the phase 3 randomized RTOG 9601 study [
46] confirmed that patients could safely avoid intensified treatment with ADT in the BCR scenario: both studies demonstrated that the Decipher biomarker was associated with distant metastasis or cancer-specific mortality. In the RTOG 9601 study, 486 BCR patients were evaluated [
47]. Multivariate analysis showed that the GC score (as a continuous variable per 0.1 unit) was independently associated with a higher risk of distant metastasis (HR 1.17, 95% CI 1.05-1.32, p=0.006), PCSM (HR 1.39, 95% CI 1.20-1.63, p<0.001), and OS (HR 1.17, 95% CI 1.06-1.29, p=0.002). In this same study, it was found that patients with a low GC score apparently would not benefit from intensified treatments. In this context, the results demonstrate that the GC score could identify BCR patients, regardless of PSA level, who would or would not benefit from salvage EBRT (sEBRT) + ADT versus sEBRT alone.
In a meta-analysis by Spratt et al., the 10-year cumulative incidence of metastasis was evaluated according to GC risk categories post-RP, resulting in 5.5%, 15.0%, and 26.7% for low, intermediate, and high risk, respectively (p<0.001) [
48]. Dal Prana et al. evaluated samples from 226 post-RP patients to determine the association of GC with 5-year freedom from biochemical progression [
49]. Patients with high-risk GC had a 5-year freedom from biochemical survivor rate of 45% (95% CI 32-59%) versus 71% (95% CI 64-78%) in the low-intermediate GC group.
Regarding the use of Decipher to change management in BCR patients, the PRO-ACT study prospectively evaluated the decision changes of 15 community urologists before and after using Decipher [
50]. It was observed that there was a management change to adjuvant EBRT (aEBRT) in 30% of cases, and 42% of patients who were initially recommended adjuvant therapy were reassigned to observation. The decision change in adjuvant therapy use with Decipher in this study was statistically significant (p<0.001). Another study that evaluated this aspect was PRO-IMPACT, which showed similar results [
51]. In this prospective study of 265 post-RP patients, adjuvant therapy use was evaluated. After the use of Decipher testing, 18% of treatment recommendations changed to aEBRT and 32% to salvage therapy. In both groups, Decipher testing was associated with a significant decrease in decisional conflicts for both patients and physicians (p<0.001). Marascio et al. [
44] also prospectively evaluated outcomes in BCR patients who received post-RP EBRT based on adverse pathological presentations, finding that the GC changed management in 39% of patients. Those with high genomic risk were recommended for aEBRT, and in these patients, the 2-year BCR rates in those who followed the oncology committee's recommendations were 3% compared to 25% in those who did not (p=0.01). On the other hand, those with low-intermediate genomic risk were all recommended for observation with sEBRT as needed. In these patients, the 2-year BCR rates were 3% and 0.5% for those who underwent aEBRT (p=0.77).
There are no prospective studies that have evaluated the effect of management changes on patient outcomes. However, Den et al. [
52] demonstrated in a prospective study that among patients with intermediate to high GC who underwent early sEBRT (PSA ≤0.2 ng/mL) versus those who did not, the 8-year cumulative metastatic disease rates were 3% versus 23%. These rates were not different in low GC patients with early sEBRT use. Additionally, Feng et al. [
47] using data from the RTOG 9601 study, showed that patients with low GC scores had minimal benefit in adding hormonal therapy alongside early sEBRT, with a 0.4% reduction in metastasis at 12 years. Meanwhile, for patients with intermediate or high GC scores, the effect was substantial, with an 11.2% reduction in 12-year metastasis rate by adding hormonal therapy to sEBRT.
In clinical guidelines, in addition to the recommendations mentioned earlier where other biomarkers previously addressed in this review could be used, in the case of Decipher, there are some additional recommendations. The NCCN [
18] indicates that it can be used in patients with adverse post-RP presentations to evaluate adjuvant treatment and may be considered as part of counseling for risk stratification in patients with BCR post-RP. Both the AUA [
24] and EAU [
23] allude to the need for further studies to recommend it, but see that in the future it may contribute to decision-making regarding ADT intensification to salvage radiotherapy, or to the decision to initiate EBRT in the context of BCR.
In the future, genetic markers like Decipher could be routinely used to guide adjuvant use in high-risk BCR patients, as although there is currently no consensus on this, it seems that this could help reduce the risk of overtreatment and avoid delaying therapies that could benefit patients in this scenario.
Table 1 summarizes the ability of predict BCR of different biomarkers presented previously and compares it with PSMA PET. In addition, it shows the ability to change treatment and recommended clinical guidelines on biomarkers and PET-PSMA.