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.

Association between body mass index and localized prostate cancer management and disease-specific quality of life.

Purpose: The purpose of this work is to describe the association between body mass index (BMI) and (1) management option for localized prostate cancer (PCa) and (2) disease-specific quality of life (ds-QoL) after treatment or active surveillance. Subjects/patients and methods: We analysed data from men with localized PCa managed with radical prostatectomy (RP), radiation therapy (RT), or active surveillance (AS) in a prospective, population-based cohort study. We evaluated the association between BMI and management option with multivariable multinomial logistic regression analysis. The association between BMI and ds-QoL was assessed using multivariable longitudinal linear regression. Regression models were adjusted for baseline domain scores, demographics, and clinicopathologic characteristics. Results: A total of 2378 men were included (medians [quartiles]: age 64 [59-69] years; BMI 27 kg/m2; 77% were non-Hispanic white); 29% were obese (BMI ≥ 30). Accounting for demographic and clinicopathologic features, BMI ≥ 28 kg/m2 was inversely associated with the likelihood of receiving RP (compared with RT) and became statistically significant at BMI ≥ 33 kg/m2 (maximum adjusted relative risk ratio = 0.80, 95% CI 0.67 to 0.95, p = 0.013 for BMI ≥ 33 vs. 25). Conversely, BMI was not significantly associated with the likelihood of receiving AS compared with RT. After stratification by management option, obese men who underwent definitive treatment were not found to have clinically worse ds-QoL. Obese men initially on AS appeared to have worse urinary incontinence than nonobese men, but this was not significant on an as-treated sensitivity analysis. Conclusions: Among men with localized PCa, those with BMI ≥ 33 kg/m2 were less likely to receive surgery than radiation. Obesity was not associated with ds-QoL in men undergoing definitive treatment, nor in men who remained on AS.

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.

Exploring the molecular basis for substrate specificity in homologous macrolide biosynthetic cytochromes P450.

Cytochromes P450 (P450s) are nature's catalysts of choice for performing demanding and physiologically vital oxidation reactions. Biochemical characterization of these enzymes over the past decades has provided detailed mechanistic insight and highlighted the diversity of substrates P450s accommodate and the spectrum of oxidative transformations they catalyze. Previously, we discovered that the bacterial P450 MycCI from the mycinamicin biosynthetic pathway in Micromonospora griseorubida possesses an unusually broad substrate scope, whereas the homologous P450 from tylosin-producing Streptomyces fradiae (TylHI) exhibits a high degree of specificity for its native substrate. Here, using biochemical, structural, and computational approaches, we aimed to understand the molecular basis for the disparate reactivity profiles of these two P450s. Turnover and equilibrium binding experiments with substrate analogs revealed that TylHI strictly prefers 16-membered ring macrolides bearing the deoxyamino sugar mycaminose. To help rationalize these results, we solved the X-ray crystal structure of TylHI in complex with its native substrate at 1.99-Å resolution and assayed several site-directed mutants. We also conducted molecular dynamics simulations of TylHI and MycCI and biochemically characterized a third P450 homolog from the chalcomycin biosynthetic pathway in Streptomyces bikiniensis These studies provided a basis for constructing P450 chimeras to gain further insight into the features dictating the differences in reaction profile among these structurally and functionally related enzymes, ultimately unveiling the central roles of key loop regions in influencing substrate binding and turnover. Our work highlights the complex nature of P450/substrate interactions and raises interesting questions regarding the evolution of functional diversity among biosynthetic enzymes.