Wei, John T.

7 Background: Improved prognostic biomarkers are needed for localized prostate cancer. We undertook an unbiased large-scale analysis of genes associated with metastatic progression and validated the prognostic ability of the top candidate gene. Methods: Prostate cancer samples from prostatectomy patients were analyzed for gene expression using a clinical-grade, high-density Affymetrix GeneChip platform, encompassing >1 million genomic loci and assessed in a CLIA-certified laboratory. Nomination of prognostic candidate genes was performed on a discovery cohort (n=545) and validated on 3 independent cohorts (n=463). Multivariate analyses were performed for the primary endpoint of metastasis. The top prostate-specific gene was further evaluated in 208 additional tumor samples with a novel RNA in-situ hybridization (ISH) assay and in urine samples from 230 patients using PCR. Results: Of all known genes, the long noncoding RNA SChLAP1 ranked first for elevated expression in patients with metastatic progression by receiver-operator-curve analyses. Validation in three independent cohorts confirmed the prognostic value of SChLAP1. On multivariate modeling, SChLAP1 expression independently predicted metastasis within 10 years (odds ratio (OR) = 2.45, 95% confidence interval (CI) 1.70 – 3.53), death within 10 years (OR = 1.93, 95% CI 1.31 – 2.85), and biochemical recurrence within 5 years (OR = 1.76, 95% CI 1.28 – 2.41) with ORs comparable to Gleason score. Evaluation of SChLAP1 expression by RNA ISH confirmed a significant association with disease recurrence (OR = 1.99, 95% CI 1.06 – 3.73). Evaluation of urine SChLAP1 levels demonstrated increased expression in patients at higher risk for disease progression. Conclusions: We perform the largest high-throughput, unbiased study of prostate cancer prognostic biomarkers to date and discover SChLAP1 as a top gene predictive of metastatic progression. We validate SChLAP1 extensively with a clinical-grade assay. We show feasibility of a RNA ISH assay and a non-invasive urine test for SChLAP1. Our results, spanning 1,446 patients from 6 independent patient cohorts, suggest that SChLAP1 represents a very promising biomarker for aggressive clinical course.

Objective To examine the use of the Prostate Health Index ( PHI ) as a continuous variable in multivariable risk assessment for aggressive prostate cancer in a large multicentre US study. Materials and Methods The study population included 728 men, with prostate‐specific antigen ( PSA ) levels of 2–10 ng/ mL and a negative digital rectal examination, enrolled in a prospective, multi‐site early detection trial. The primary endpoint was aggressive prostate cancer, defined as biopsy Gleason score ≥7. First, we evaluated whether the addition of PHI improves the performance of currently available risk calculators (the Prostate Cancer Prevention Trial [ PCPT ] and European Randomised Study of Screening for Prostate Cancer [ ERSPC ] risk calculators). We also designed and internally validated a new PHI ‐based multivariable predictive model, and created a nomogram. Results Of 728 men undergoing biopsy, 118 (16.2%) had aggressive prostate cancer. The PHI predicted the risk of aggressive prostate cancer across the spectrum of values. Adding PHI significantly improved the predictive accuracy of the PCPT and ERSPC risk calculators for aggressive disease. A new model was created using age, previous biopsy, prostate volume, PSA and PHI , with an area under the curve of 0.746. The bootstrap‐corrected model showed good calibration with observed risk for aggressive prostate cancer and had net benefit on decision‐curve analysis. Conclusion Using PHI as part of multivariable risk assessment leads to a significant improvement in the detection of aggressive prostate cancer, potentially reducing harms from unnecessary prostate biopsy and overdiagnosis.