Evaluation of blood and urine based biomarkers for detection of clinically-significant prostate cancer.

BACKGROUND: Recognizing the limitations of prostate-specific antigen (PSA) screening and the morbidity of prostate biopsies, several blood- and urine-based biomarkers have been proposed for pre-biopsy risk stratification. These assays aim to reduce the frequency of unnecessary biopsies (i.e., negative or Grade Group 1 [GG1]) while maintaining highly sensitive detection of clinically significant cancer (GG ≥ 2) prostate cancer. METHODS: We reviewed the literature describing the use of currently available blood- and urine-based biomarkers for detection of GG ≥ 2 cancer, including the Prostate Health Index (PHI), 4Kscore, MyProstateScore (MPS), SelectMDx, ExoDx Prostate Intelliscore (EPI), and IsoPSA. To facilitate clinical application, we focused on the use of biomarkers as a post-PSA secondary test prior to biopsy, as proposed in clinical guidelines. Our outcomes included test performance measures-sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV)-as well as clinical outcomes resulting from biomarker use (i.e., unnecessary biopsies avoided, GG ≥ 2 cancers missed). RESULTS: Contemporary validation data (2015-2023) reveal that currently available biomarkers provide ~15-50% specificity at a sensitivity of 90-95% for GG ≥ 2 PCa. Clinically, this indicates that secondary use of biomarker testing in men with elevated PSA could allow for avoidance of up to 15-50% of unnecessary prostate biopsies, while preserving detection of 90-95% of GG ≥ 2 cancers that would be detected under the traditional "biopsy all" approach. CONCLUSIONS: The contemporary literature further supports the proposed role of post-PSA biomarker testing to reduce the use of invasive biopsy while maintaining highly sensitive detection of GG ≥ 2 cancer. Questions remain regarding the optimal application of biomarkers in combination or in sequence with mpMRI.

Integrative multi-region molecular profiling of primary prostate cancer in men with synchronous lymph node metastasis.

Localized prostate cancer is frequently composed of multiple spatially distinct tumors with significant inter- and intra-tumoral molecular heterogeneity. This genomic diversity gives rise to many competing clones that may drive the biological trajectory of the disease. Previous large-scale sequencing efforts have focused on the evolutionary process in metastatic prostate cancer, revealing a potential clonal progression to castration resistance. However, the clonal origin of synchronous lymph node (LN) metastases in primary disease is still unknown. Here, we perform multi-region, targeted next generation sequencing and construct phylogenetic trees in men with prostate cancer with synchronous LN metastasis to better define the pathologic and molecular features of primary disease most likely to spread to the LNs. Collectively, we demonstrate that a combination of histopathologic and molecular factors, including tumor grade, presence of extra-prostatic extension, cellular morphology, and oncogenic genomic alterations are associated with synchronous LN metastasis.

Development and Validation of an 18-Gene Urine Test for High-Grade Prostate Cancer.

Importance: Benefits of prostate cancer (PCa) screening with prostate-specific antigen (PSA) alone are largely offset by excess negative biopsies and overdetection of indolent cancers resulting from the poor specificity of PSA for high-grade PCa (ie, grade group [GG] 2 or greater). Objective: To develop a multiplex urinary panel for high-grade PCa and validate its external performance relative to current guideline-endorsed biomarkers. Design, Setting, and Participants: RNA sequencing analysis of 58 724 genes identified 54 markers of PCa, including 17 markers uniquely overexpressed by high-grade cancers. Gene expression and clinical factors were modeled in a new urinary test for high-grade PCa (MyProstateScore 2.0 [MPS2]). Optimal models were developed in parallel without prostate volume (MPS2) and with prostate volume (MPS2+). The locked models underwent blinded external validation in a prospective National Cancer Institute trial cohort. Data were collected from January 2008 to December 2020, and data were analyzed from November 2022 to November 2023. Exposure: Protocolized blood and urine collection and transrectal ultrasound-guided systematic prostate biopsy. Main Outcomes and Measures: Multiple biomarker tests were assessed in the validation cohort, including serum PSA alone, the Prostate Cancer Prevention Trial risk calculator, and the Prostate Health Index (PHI) as well as derived multiplex 2-gene and 3-gene models, the original 2-gene MPS test, and the 18-gene MPS2 models. Under a testing approach with 95% sensitivity for PCa of GG 2 or greater, measures of diagnostic accuracy and clinical consequences of testing were calculated. Cancers of GG 3 or greater were assessed secondarily. Results: Of 761 men included in the development cohort, the median (IQR) age was 63 (58-68) years, and the median (IQR) PSA level was 5.6 (4.6-7.2) ng/mL; of 743 men included in the validation cohort, the median (IQR) age was 62 (57-68) years, and the median (IQR) PSA level was 5.6 (4.1-8.0) ng/mL. In the validation cohort, 151 (20.3%) had high-grade PCa on biopsy. Area under the receiver operating characteristic curve values were 0.60 using PSA alone, 0.66 using the risk calculator, 0.77 using PHI, 0.76 using the derived multiplex 2-gene model, 0.72 using the derived multiplex 3-gene model, and 0.74 using the original MPS model compared with 0.81 using the MPS2 model and 0.82 using the MPS2+ model. At 95% sensitivity, the MPS2 model would have reduced unnecessary biopsies performed in the initial biopsy population (range for other tests, 15% to 30%; range for MPS2, 35% to 42%) and repeat biopsy population (range for other tests, 9% to 21%; range for MPS2, 46% to 51%). Across pertinent subgroups, the MPS2 models had negative predictive values of 95% to 99% for cancers of GG 2 or greater and of 99% for cancers of GG 3 or greater. Conclusions and Relevance: In this study, a new 18-gene PCa test had higher diagnostic accuracy for high-grade PCa relative to existing biomarker tests. Clinically, use of this test would have meaningfully reduced unnecessary biopsies performed while maintaining highly sensitive detection of high-grade cancers. These data support use of this new PCa biomarker test in patients with elevated PSA levels to reduce the potential harms of PCa screening while preserving its long-term benefits.

Clinical consequences of a genetic predisposition toward higher benign prostate-specific antigen levels.

BACKGROUND: Prostate-specific antigen (PSA) levels are influenced by genetic variation unrelated to prostate cancer risk. Whether a genetic predisposition to a higher PSA level predisposes to a diagnostic work-up for prostate cancer is not known. METHODS: Participants were 3110 men of African and European ancestries ages 45-70, without prostate cancer and with a baseline PSA < 4 ng/mL, undergoing routine clinical PSA screening. The exposure was a polygenic score (PGS) comprising 111 single nucleotide polymorphisms associated with PSA level, but not prostate cancer. We tested whether the PGS was associated with a: 1) PSA value > 4 ng/mL, 2) International Classification of Diseases (ICD) code for an elevated PSA, 3) encounter with a urologist, or 4) prostate biopsy. Multivariable Cox proportional hazards models were adjusted for age and genetic principal components. Analyses were stratified by age (45-59 years, and 60-70 years old). Association estimates are per standard deviation change in the PGS. FINDINGS: The median age was 56.6 years, and 2118 (68%) participants were 45-59 years. The median (IQR) baseline PSA level was 1.0 (0.6-1.7) ng/mL. Among men ages 45-59, the PGS was associated with a PSA > 4 (hazard ratio [HR] = 1.35 [95% CI, 1.17-1.57], p = 4.5 × 10-5), an ICD code for elevated PSA (HR = 1.30 [1.12-1.52], p = 8.0 × 10-4), a urological evaluation (HR = 1.34 [1.14-1.57], p = 4.8 × 10-4), and undergoing a prostate biopsy (HR = 1.35 [1.11-1.64], p = 0.002). Among men ages 60-70, association effect sizes were smaller and not significant. INTERPRETATION: A predisposition toward higher PSA levels was associated with clinical evaluations of an elevated PSA among men ages 45-59 years. FUNDING: National Institutes of Health (NIH).

Use of Active Surveillance vs Definitive Treatment Among Men With Low- and Favorable Intermediate-Risk Prostate Cancer in the US Between 2010 and 2018.

This cross-sectional study of data from the Surveillance, Epidemiology and End Results database assesses temporal trends in the use of active surveillance and watchful waiting vs definitive treatment in men with low- and favorable intermediate­risk prostate cancer in the US between 2010 and 2018.

A Polygenic Risk Score for Prostate Cancer Risk Prediction.

This retrospective cohort study compares 2 risk calculator systems that compute the probabilities of finding high-grade or any cancer on biopsy results in men undergoing a first prostate biopsy.

Optimizing detection of clinically significant prostate cancer through nomograms incorporating mri, clinical features, and advanced serum biomarkers in biopsy naïve men.

PURPOSE: To develop nomograms that predict the detection of clinically significant prostate cancer (csPCa, defined as ≥GG2 [Grade Group 2]) at diagnostic biopsy based on multiparametric prostate MRI (mpMRI), serum biomarkers, and patient clinicodemographic features. MATERIALS AND METHODS: Nomograms were developed from a cohort of biopsy-naïve men presenting to our 11-hospital system with prostate specific antigen (PSA) of 2-20 ng/mL who underwent pre-biopsy mpMRI from March 2018-June 2021 (n = 1494). The outcomes were the presence of csPCa and high-grade prostate cancer (defined as ≥GG3 prostate cancer). Using significant variables on multivariable logistic regression, individual nomograms were developed for men with total PSA, % free PSA, or prostate health index (PHI) when available. The nomograms were both internally validated and evaluated in an independent cohort of 366 men presenting to our hospital system from July 2021-February 2022. RESULTS: 1031 of 1494 men (69%) underwent biopsy after initial evaluation with mpMRI, 493 (47.8%) of whom were found to have ≥GG2 PCa, and 271 (26.3%) were found to have ≥GG3 PCa. Age, race, highest PIRADS score, prostate health index when available, % free PSA when available, and PSA density were significant predictors of ≥GG2 and ≥GG3 PCa on multivariable analysis and were used for nomogram generation. Accuracy of nomograms in both the training cohort and independent cohort were high, with areas under the curves (AUC) of ≥0.885 in the training cohort and ≥0.896 in the independent validation cohort. In our independent validation cohort, our model for ≥GG2 prostate cancer with PHI saved 39.1% of biopsies (143/366) while only missing 0.8% of csPCa (1/124) with a biopsy threshold of 20% probability of csPCa. CONCLUSIONS: Here we developed nomograms combining serum testing and mpMRI to help clinicians risk stratify patients with elevated PSA of 2-20 ng/mL who are being considered for biopsy. Our nomograms are available at https://rossnm1.shinyapps.io/MynMRIskCalculator/ to aid with biopsy decisions.

Combined Use of Magnetic Resonance Imaging and Biomarker Testing to Detect Clinically Significant Prostate Cancer.

We performed a narrative review of studies that produced clinically applicable data by examining the combined use of at least one biomarker test and multiparametric MRI to predict GG ≥2 prostate cancer on biopsy and by reporting the resultant clinical outcomes (i.e, the proportion of biopsies avoided and GG ≥2 cancers missed) following the application of various testing strategies incorporating these diagnostic tests.

MyProstateScore in men considering repeat biopsy: validation of a simple testing approach.

BACKGROUND: Men with persistent risk of Grade Group (GG) ≥ 2 cancer after a negative biopsy present a unique clinical challenge. The validated MyProstateScore test is clinically-available for pre-biopsy risk stratification. In biopsy-naïve patients, we recently validated a straightforward testing approach to rule-out GG ≥ 2 cancer with 98% negative predictive value (NPV) and 97% sensitivity. In the current study, we established a practical MPS-based testing approach in men with a previous negative biopsy being considered for repeat biopsy. METHODS: Patients provided post-digital rectal examination urine prior to repeat biopsy. MyProstateScore was calculated using the validated, locked model including urinary PCA3 and TMPRSS2:ERG scores with serum PSA. In a clinically-appropriate primary (i.e., training) cohort, we identified a lower (rule-out) threshold approximating 90% sensitivity and an upper (rule-in) threshold approximating 80% specificity for GG ≥ 2 cancer. These thresholds were applied to an external validation cohort, and performance measures and clinical outcomes associated with their use were calculated. RESULTS: MyProstateScore thresholds of 15 and 40 met pre-defined performance criteria in the primary cohort (422 patients; median PSA 6.4, IQR 4.3-9.1). In the 268-patient validation cohort, 25 men (9.3%) had GG ≥ 2 cancer on repeat biopsy. The rule-out threshold of 15 provided 100% NPV and sensitivity for GG ≥ 2 cancer and would have prevented 23% of unnecessary biopsies. Use of MyProstateScore >40 to rule-in biopsy would have prevented 67% of biopsies while maintaining 95% NPV. In the validation cohort, the prevalence of GG ≥ 2 cancer was 0% for MyProstateScore 0-15, 6.5% for MyProstateScore 15-40, and 19% for MyProstateScore >40. CONCLUSIONS: In patients who previously underwent a negative prostate biopsy, the MyProstateScore values of 15 and 40 yielded clinically-actionable rule-in and rule-out risk groups. Using this straightforward testing approach, MyProstateScore can meaningfully inform patients and physicians weighing the need for repeat biopsy.

Prospective comparison of restriction spectrum imaging and non-invasive biomarkers to predict upgrading on active surveillance prostate biopsy.

BACKGROUND: Protocol-based active surveillance (AS) biopsies have led to poor compliance. To move to risk-based protocols, more accurate imaging biomarkers are needed to predict upgrading on AS prostate biopsy. We compared restriction spectrum imaging (RSI-MRI) generated signal maps as a biomarker to other available non-invasive biomarkers to predict upgrading or reclassification on an AS biopsy. METHODS: We prospectively enrolled men on prostate cancer AS undergoing repeat biopsy from January 2016 to June 2019 to obtain an MRI and biomarkers to predict upgrading. Subjects underwent a prostate multiparametric MRI and a short duration, diffusion-weighted enhanced MRI called RSI to generate a restricted signal map along with evaluation of 30 biomarkers (14 clinico-epidemiologic features, 9 molecular biomarkers, and 7 radiologic-associated features). Our primary outcome was upgrading or reclassification on subsequent AS prostate biopsy. Statistical analysis included operating characteristic improvement using AUROC and AUPRC. RESULTS: The individual biomarker with the highest area under the receiver operator characteristic curve (AUC) was RSI-MRI (AUC = 0.84; 95% CI: 0.71-0.96). The best non-imaging biomarker was prostate volume-corrected Prostate Health Index density (PHI, AUC = 0.68; 95% CI: 0.53-0.82). Non-imaging biomarkers had a negligible effect on predicting upgrading at the next biopsy but did improve predictions of overall time to progression in AS. CONCLUSIONS: RSI-MRI, PIRADS, and PHI could improve the predictive ability to detect upgrading in AS. The strongest predictor of clinically significant prostate cancer on AS biopsy was RSI-MRI signal output.

Active Surveillance for Intermediate-risk Prostate Cancer: A Systematic Review, Meta-analysis, and Metaregression.

CONTEXT: Active surveillance (AS) is increasingly selected among patients with localized, intermediate-risk (IR) prostate cancer (PCa). However, the safety and optimal candidate selection for those with IR PCa remain uncertain. OBJECTIVE: To evaluate treatment-free survival and oncologic outcomes in patients with IR PCa managed with AS and to compare with AS outcomes in low-risk (LR) PCa patients. EVIDENCE ACQUISITION: A literature search was conducted through February 2022 using PubMed/Medline, Embase, and Web of Science databases. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were followed to identify eligible studies. The coprimary outcomes were treatment-free, metastasis-free, cancer-specific, and overall survival. A subgroup analysis was planned a priori to explore AS outcomes when limiting inclusion to IR patients with a Gleason grade (GG) of ≤2. EVIDENCE SYNTHESIS: A total of 25 studies including 29 673 unselected IR patients met our inclusion criteria. The 10-yr treatment-free, metastasis-free, cancer-specific, and overall survival ranged from 19.4% to 69%, 80.8% to 99%, 88.2% to 99%, and 59.4% to 83.9%, respectively. IR patients had similar treatment-free survival to LR patients (risk ratio [RR] 1.16, 95% confidence interval (CI), 0.99-1.36, p = 0.07), but significantly higher risks of metastasis (RR 5.79, 95% CI, 4.61-7.29, p < 0.001), death from PCa (RR 3.93, 95% CI, 2.93-5.27, p < 0.001), and all-cause death (RR 1.44, 95% CI, 1.11-1.86, p = 0.005). In a subgroup analysis of studies including patients with GG ≤2 only (n = 4), treatment-free survival (RR 1.03, 95% CI, 0.62-1.71, p = 0.91) and metastasis-free survival (RR 2.09, 95% CI, 0.75-5.82, p = 0.16) were similar between LR and IR patients. Treatment-free survival was significantly reduced in subgroups of patients with unfavorable IR disease and increased cancer length on biopsy. CONCLUSIONS: The present systematic review and meta-analysis highlight the need to optimize patient selection for those with IR features. Our findings support limiting the inclusion of IR patients in AS to those with low-volume GG 2 tumor. PATIENT SUMMARY: Active surveillance is increasingly used in patients with localized, intermediate-risk (IR) prostate cancer. In this population, we have reported higher risks of metastasis and cancer mortality in unselected patients than in patients with low-risk features, underscoring the need to optimize the selection of patients with IR features.