Assessment of prostate cancer progression using a translational needle photoacoustic sensing probe: Preliminary study with intact human prostates ex-vivo.

In our previous studies, we demonstrated the ability of an interstitial all-optical needle photoacoustic (PA) sensing probe and PA spectral analysis (PASA) to assess the aggressiveness of prostate cancer. In this clinical translation investigation, we integrated the optical components of the needle PA sensing probe into a 18G steel needle. The translational needle PA sensing probe was evaluated using intact human prostates in a simulated ultrasound-guided transperineal prostate biopsy. PA signals were acquired at 1220 nm, 1370 nm, 800 nm and 266 nm at each interstitial measurement location and quantified by PASA within the frequency range of 8-28 MHz. The measurement locations were stained for establishing spatial correlations between the quantitative measurements and the histological diagnosing. Most of the quantitative PA assessments reveal statistically significant differences between the benign and cancerous regions. Multivariate analysis combining the PASA quantifications shows an accuracy close to 90% in differentiating the benign and cancerous regions in the prostates.

Association Between Combined TMPRSS2:ERG and PCA3 RNA Urinary Testing and Detection of Aggressive Prostate Cancer.

IMPORTANCE: Potential survival benefits from treating aggressive (Gleason score, ≥7) early-stage prostate cancer are undermined by harms from unnecessary prostate biopsy and overdiagnosis of indolent disease. OBJECTIVE: To evaluate the a priori primary hypothesis that combined measurement of PCA3 and TMPRSS2:ERG (T2:ERG) RNA in the urine after digital rectal examination would improve specificity over measurement of prostate-specific antigen alone for detecting cancer with Gleason score of 7 or higher. As a secondary objective, to evaluate the potential effect of such urine RNA testing on health care costs. DESIGN, SETTING, AND PARTICIPANTS: Prospective, multicenter diagnostic evaluation and validation in academic and community-based ambulatory urology clinics. Participants were a referred sample of men presenting for first-time prostate biopsy without preexisting prostate cancer: 516 eligible participants from among 748 prospective cohort participants in the developmental cohort and 561 eligible participants from 928 in the validation cohort. INTERVENTIONS/EXPOSURES: Urinary PCA3 and T2:ERG RNA measurement before prostate biopsy. MAIN OUTCOMES AND MEASURES: Presence of prostate cancer having Gleason score of 7 or higher on prostate biopsy. Pathology testing was blinded to urine assay results. In the developmental cohort, a multiplex decision algorithm was constructed using urine RNA assays to optimize specificity while maintaining 95% sensitivity for predicting aggressive prostate cancer at initial biopsy. Findings were validated in a separate multicenter cohort via prespecified analysis, blinded per prospective-specimen-collection, retrospective-blinded-evaluation (PRoBE) criteria. Cost effects of the urinary testing strategy were evaluated by modeling observed biopsy results and previously reported treatment outcomes. RESULTS: Among the 516 men in the developmental cohort (mean age, 62 years; range, 33-85 years) combining testing of urinary T2:ERG and PCA3 at thresholds that preserved 95% sensitivity for detecting aggressive prostate cancer improved specificity from 18% to 39%. Among the 561 men in the validation cohort (mean age, 62 years; range, 27-86 years), analysis confirmed improvement in specificity (from 17% to 33%; lower bound of 1-sided 95% CI, 0.73%; prespecified 1-sided P = .04), while high sensitivity (93%) was preserved for aggressive prostate cancer detection. Forty-two percent of unnecessary prostate biopsies would have been averted by using the urine assay results to select men for biopsy. Cost analysis suggested that this urinary testing algorithm to restrict prostate biopsy has greater potential cost-benefit in younger men. CONCLUSIONS AND RELEVANCE: Combined urinary testing for T2:ERG and PCA3 can avert unnecessary biopsy while retaining robust sensitivity for detecting aggressive prostate cancer with consequent potential health care cost savings.

Urine TMPRSS2:ERG Plus PCA3 for Individualized Prostate Cancer Risk Assessment.

BACKGROUND: TMPRSS2:ERG (T2:ERG) and prostate cancer antigen 3 (PCA3) are the most advanced urine-based prostate cancer (PCa) early detection biomarkers. OBJECTIVE: Validate logistic regression models, termed Mi-Prostate Score (MiPS), that incorporate serum prostate-specific antigen (PSA; or the multivariate Prostate Cancer Prevention Trial risk calculator version 1.0 [PCPTrc]) and urine T2:ERG and PCA3 scores for predicting PCa and high-grade PCa on biopsy. DESIGN, SETTING, AND PARTICIPANTS: T2:ERG and PCA3 scores were generated using clinical-grade transcription-mediated amplification assays. Pretrained MiPS models were applied to a validation cohort of whole urine samples prospectively collected after digital rectal examination from 1244 men presenting for biopsy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Area under the curve (AUC) was used to compare the performance of serum PSA (or the PCPTrc) alone and MiPS models. Decision curve analysis (DCA) was used to assess clinical benefit. RESULTS AND LIMITATIONS: Among informative validation cohort samples (n=1225 [98%], 80% from patients presenting for initial biopsy), models incorporating T2:ERG had significantly greater AUC than PSA (or PCPTrc) for predicting PCa (PSA: 0.693 vs 0.585; PCPTrc: 0.718 vs 0.639; both p<0.001) or high-grade (Gleason score >6) PCa on biopsy (PSA: 0.729 vs 0.651, p<0.001; PCPTrc: 0.754 vs 0.707, p=0.006). MiPS models incorporating T2:ERG score had significantly greater AUC (all p<0.001) than models incorporating only PCA3 plus PSA (or PCPTrc or high-grade cancer PCPTrc [PCPThg]). DCA demonstrated net benefit of the MiPS_PCPTrc (or MiPS_PCPThg) model compared with the PCPTrc (or PCPThg) across relevant threshold probabilities. CONCLUSIONS: Incorporating urine T2:ERG and PCA3 scores improves the performance of serum PSA (or PCPTrc) for predicting PCa and high-grade PCa on biopsy. PATIENT SUMMARY: Incorporation of two prostate cancer (PCa)-specific biomarkers (TMPRSS2:ERG and PCA3) measured in the urine improved on serum prostate-specific antigen (or a multivariate risk calculator) for predicting the presence of PCa and high-grade PCa on biopsy. A combined test, Mi-Prostate Score, uses models validated in this study and is clinically available to provide individualized risk estimates.

Multicenter Evaluation of the Prostate Health Index to Detect Aggressive Prostate Cancer in Biopsy Naïve Men.

PURPOSE: We evaluated the ability of PHI to discriminate aggressive prostate cancer from indolent or no cancer in a biopsy naïve population. MATERIALS AND METHODS: Two independent prospective cohorts of 561 and 395 subjects, respectively, with no prior prostate biopsy who were enrolled at different clinical sites were used to validate the results. We compared the diagnostic specificity of PHI to prebiopsy total and percent free prostate specific antigen using prostate biopsy results. We also determined the optimal PHI threshold to discriminate aggressive prostate cancer (Gleason score 7 or greater) from indolent or no prostate cancer (Gleason score 6 or less). RESULTS: In the primary cohort higher PHI values were significantly associated with Gleason score 7 or greater. The AUC to detect aggressive prostate cancer was 0.815. At 95% sensitivity PHI specificity was 36.0% vs 17.2% and 19.4% for total and percent free prostate specific antigen, respectively. At 95% sensitivity for detecting aggressive prostate cancer the optimal PHI cutoff was 24, which would help avoid 41% of unnecessary biopsies. A cutoff of 24 led to 36% biopsies avoided with few aggressive cancers missed. These results were confirmed in the validation cohort. CONCLUSIONS: The PHI detected aggressive prostate cancer with better specificity than total and percent free prostate specific antigen in a biopsy naïve population. It could be a useful tool to decrease unnecessary prostate biopsies.

Deep sequencing reveals distinct patterns of DNA methylation in prostate cancer.

Beginning with precursor lesions, aberrant DNA methylation marks the entire spectrum of prostate cancer progression. We mapped the global DNA methylation patterns in select prostate tissues and cell lines using MethylPlex-next-generation sequencing (M-NGS). Hidden Markov model-based next-generation sequence analysis identified ∼68,000 methylated regions per sample. While global CpG island (CGI) methylation was not differential between benign adjacent and cancer samples, overall promoter CGI methylation significantly increased from ~12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues, respectively (P-value < 2 × 10(-16)). We found distinct patterns of promoter methylation around transcription start sites, where methylation occurred not only on the CGIs, but also on flanking regions and CGI sparse promoters. Among the 6691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer-specific, including numerous novel DMRs. A novel cancer-specific DMR in the WFDC2 promoter showed frequent methylation in cancer (17/22 tissues, 6/6 cell lines), but not in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested an epigenetic mechanism for alternate transcription start site utilization, and these modifications segregated into distinct regions when present on the same promoter. Finally, we observed differences in repeat element methylation, particularly LINE-1, between ERG gene fusion-positive and -negative cancers, and we confirmed this observation using pyrosequencing on a tissue panel. This comprehensive methylome map will further our understanding of epigenetic regulation in prostate cancer progression.