An intra-tumoral niche maintains and differentiates stem-like CD8 T cells.

Tumour-infiltrating lymphocytes are associated with a survival benefit in several tumour types and with the response to immunotherapy1-8. However, the reason some tumours have high CD8 T cell infiltration while others do not remains unclear. Here we investigate the requirements for maintaining a CD8 T cell response against human cancer. We find that CD8 T cells within tumours consist of distinct populations of terminally differentiated and stem-like cells. On proliferation, stem-like CD8 T cells give rise to more terminally differentiated, effector-molecule-expressing daughter cells. For many T cells to infiltrate the tumour, it is critical that this effector differentiation process occur. In addition, we show that these stem-like T cells reside in dense antigen-presenting-cell niches within the tumour, and that tumours that fail to form these structures are not extensively infiltrated by T cells. Patients with progressive disease lack these immune niches, suggesting that niche breakdown may be a key mechanism of immune escape.

Covariate adjustment in continuous biomarker assessment.

Continuous biomarkers are common for disease screening and diagnosis. To reach a dichotomous clinical decision, a threshold would be imposed to distinguish subjects with disease from nondiseased individuals. Among various performance metrics, specificity at a controlled sensitivity level (or vice versa) is often desirable because it directly targets the clinical utility of the intended clinical test. Meanwhile, covariates, such as age, race, as well as sample collection conditions, could impact the biomarker distribution and may also confound the association between biomarker and disease status. Therefore, covariate adjustment is important in such biomarker evaluation. Most existing covariate adjustment methods do not specifically target the desired sensitivity/specificity level, but rather do so for the entire biomarker distribution. As such, they might be more prone to model misspecification. In this paper, we suggest a parsimonious quantile regression model for the diseased population, only locally at the controlled sensitivity level, and assess specificity with covariate-specific control of the sensitivity. Variance estimates are obtained from a sample-based approach and bootstrap. Furthermore, our proposed local model extends readily to a global one for covariate adjustment for the receiver operating characteristic (ROC) curve over the sensitivity continuum. We demonstrate computational efficiency of this proposed method and restore the inherent monotonicity in the estimated covariate-adjusted ROC curve. The asymptotic properties of the proposed estimators are established. Simulation studies show favorable performance of the proposal. Finally, we illustrate our method in biomarker evaluation for aggressive prostate cancer.

Covariate-specific evaluation of continuous biomarker.

Diagnostic tests usually need to operate at a high sensitivity or specificity level in practice. Accordingly, specificity at the controlled sensitivity, or vice versa, is a clinically sensible performance metric for evaluating continuous biomarkers. Meanwhile, the performance of a biomarker may vary across sub-populations as defined by covariates, and covariate-specific evaluation can be informative. In this article, we develop a novel modeling and estimation method for covariate-specific specificity at a controlled sensitivity level. Unlike existing methods which typically adopt elaborate models of covariate effects over the entire biomarker distribution, our approach models covariate effects locally at a specific sensitivity level of interest. We also extend our proposed model to handle the whole continuum of sensitivities via dynamic regression and derive covariate-specific ROC curves. We provide the variance estimation through bootstrapping. The asymptotic properties are established. We conduct extensive simulation studies to evaluate the performance of our proposed methods in comparison with existing methods, and further illustrate the applications in two clinical studies for aggressive prostate cancer.

Interval estimation for operating characteristic of continuous biomarkers with controlled sensitivity or specificity.

The receiver operating characteristic (ROC) curve provides a comprehensive performance assessment of a continuous biomarker over the full threshold spectrum. Nevertheless, a medical test often dictates to operate at a certain high level of sensitivity or specificity. A diagnostic accuracy metric directly targeting the clinical utility is specificity at the controlled sensitivity level, or vice versa. While the empirical point estimation is readily adopted in practice, the nonparametric interval estimation is challenged by the fact that the variance involves density functions due to estimated threshold. In addition, even with a fixed threshold, many standard confidence intervals including the Wald interval for binomial proportion could have erratic behaviors. In this article, we are motivated by the superior performance of the score interval for binomial proportion and propose a novel extension for the biomarker problem. Meanwhile, we develop exact bootstrap and establish consistency of the bootstrap variance estimator. Both single-biomarker evaluation and two-biomarker comparison are investigated. Extensive simulation studies were conducted, demonstrating competitive performance of our proposals. An illustration with aggressive prostate cancer diagnosis is provided.

Invariant NKT cell-augmented GM-CSF-secreting tumor vaccine is effective in advanced prostate cancer model.

Invariant natural killer T cells (iNKT cells) express a semi-invariant T cell receptor that recognizes certain glycolipids (including α-galactosylceramide, αGC) bound to CD1d, and can induce potent antitumor responses. Here, we assessed whether αGC could enhance the efficacy of a GM-CSF-producing tumor cell vaccine in the transgenic SV40 T antigen-driven TRAMP prostate cancer model. In healthy mice, we initially found that optimal T cell responses were obtained with αGC-pulsed TRAMP-C2 cells secreting GM-CSF and milk fat globule epidermal growth factor protein-8 (MFG-E8) with an RGD to RGE mutation (GM-CSF/RGE TRAMP-C2), combined with systemic low dose IL-12. In a therapeutic model, transgenic TRAMP mice were then castrated at ~ 20 weeks, followed by treatment with the combination vaccine. Untreated mice succumbed to tumor by ~ 40 weeks, but survival was markedly prolonged by vaccine treatment, with most mice surviving past 80 weeks. Prostates in the treated mice were heavily infiltrated with T cells and iNKT cells, which both secreted IFNγ in response to tumor cells. The vaccine was not effective if the αGC, IL-12, or GM-CSF secretion was eliminated. Finally, immunized mice were fully resistant to challenge with TRAMP-C2 cells. Together these findings support further development of therapeutic vaccines that exploit iNKT cell activation.

Prospective Multicenter Comparison of Open and Robotic Radical Prostatectomy: The PROST-QA/RP2 Consortium.

PURPOSE: Our goal was to evaluate the comparative effectiveness of robot-assisted laparoscopic prostatectomy (RALP) and open radical prostatectomy (ORP) in a multicenter study. MATERIALS AND METHODS: We evaluated men with localized prostate cancer at 11 high-volume academic medical centers in the United States from the PROST-QA (2003-2006) and the PROST-QA/RP2 cohorts (2010-2013) with a pre-specified goal of comparing RALP (549) and ORP (545). We measured longitudinal patient-reported health-related quality of life (HRQOL) at pre-treatment and at 2, 6, 12, and 24 months, and pathological and perioperative outcomes/complications. RESULTS: Demographics, cancer characteristics, and margin status were similar between surgical approaches. ORP subjects were more likely to undergo lymphadenectomy (89% vs 47%; p <0.01) and nerve sparing (94% vs 89%; p <0.01). RALP vs ORP subjects experienced less mean intraoperative blood loss (192 vs 805 mL; p <0.01), shorter mean hospital stay (1.6 vs 2.1 days; p <0.01), and fewer blood transfusions (1% vs 4%; p <0.01), wound infections (2% vs 4%; p=0.02), other infections (1% vs 4%; p <0.01), deep venous thromboses (0.5% vs 2%; p=0.04), and bladder neck contractures requiring dilation (1.6% vs 8.3%; p <0.01). RALP subjects reported less pain (p=0.04), less activity interference (p <0.01) and higher incision satisfaction (p <0.01). Surgical approach (RALP vs ORP) was not a significant predictor of longitudinal HRQOL change in any HRQOL domain. CONCLUSIONS: In high-volume academic centers, RALP and ORP patients may expect similar long-term HRQOL outcomes. Overall, RALP patients have less pain, shorter hospital stays, and fewer post-surgical complications such as blood transfusions, infections, deep venous thromboses, and bladder neck contractures.

Impact of Prostate Health Index Results for Prediction of Biopsy Grade Reclassification During Active Surveillance.

PURPOSE: We assessed whether Prostate Health Index results improve prediction of grade reclassification for men on active surveillance. METHODS AND MATERIALS: We identified men in Canary Prostate Active Surveillance Study with Grade Group 1 cancer. Outcome was grade reclassification to Grade Group 2+ cancer. We considered decision rules to maximize specificity with sensitivity set at 95%. We derived rules based on clinical data (R1) vs clinical data+Prostate Health Index (R3). We considered an "or"-logic rule combining clinical score and Prostate Health Index (R4), and a "2-step" rule using clinical data followed by risk stratification based on Prostate Health Index (R2). Rules were applied to a validation set, where values of R2-R4 vs R1 for specificity and sensitivity were evaluated. RESULTS: We included 1,532 biopsies (n = 610 discovery; n = 922 validation) among 1,142 men. Grade reclassification was seen in 27% of biopsies (23% discovery, 29% validation). Among the discovery set, at 95% sensitivity, R2 yielded highest specificity at 27% vs 17% for R1. In the validation set, R3 had best performance vs R1 with Δsensitivity = -4% and Δspecificity = +6%. There was slight improvement for R3 vs R1 for confirmatory biopsy (AUC 0.745 vs R1 0.724, ΔAUC 0.021, 95% CI 0.002-0.041) but not for subsequent biopsies (ΔAUC -0.012, 95% CI -0.031-0.006). R3 did not have better discrimination vs R1 among the biopsy cohort overall (ΔAUC 0.007, 95% CI -0.007-0.020). CONCLUSIONS: Among active surveillance patients, using Prostate Health Index with clinical data modestly improved prediction of grade reclassification on confirmatory biopsy and did not improve prediction on subsequent biopsies.

LINEAR BIOMARKER COMBINATION FOR CONSTRAINED CLASSIFICATION.

Multiple biomarkers are often combined to improve disease diagnosis. The uniformly optimal combination, i.e., with respect to all reasonable performance metrics, unfortunately requires excessive distributional modeling, to which the estimation can be sensitive. An alternative strategy is rather to pursue local optimality with respect to a specific performance metric. Nevertheless, existing methods may not target clinical utility of the intended medical test, which usually needs to operate above a certain sensitivity or specificity level, or do not have their statistical properties well studied and understood. In this article, we develop and investigate a linear combination method to maximize the clinical utility empirically for such a constrained classification. The combination coefficient is shown to have cube root asymptotics. The convergence rate and limiting distribution of the predictive performance are subsequently established, exhibiting robustness of the method in comparison with others. An algorithm with sound statistical justification is devised for efficient and high-quality computation. Simulations corroborate the theoretical results, and demonstrate good statistical and computational performance. Illustration with a clinical study on aggressive prostate cancer detection is provided.

Disparities in magnetic resonance imaging of the prostate for traditionally underserved patients with prostate cancer.

BACKGROUND: Prebiopsy magnetic resonance imaging (MRI) of the prostate improves detection of significant tumors, while decreasing detection of less-aggressive tumors. Therefore, its use has been increasing over time. In this study, the use of prebiopsy MRI among Medicare beneficiaries with prostate cancer was examined. It was hypothesized that patients of color and those in isolated areas would be less likely to undergo this approach for cancer detection. METHODS: Using cancer registry data from the Surveillance, Epidemiology, and End Results (SEER) program linked to billing claims for fee-for-service Medicare beneficiaries, men with nonmetastatic prostate cancer were identified from 2010 through 2015 with prostate-specific antigen (PSA) <30 ng/mL. Outcome was prebiopsy MRI of the prostate performed within 6 months before diagnosis (ie, Current Procedural Terminology 72197). Exposures were patient race/ethnicity and rural/urban status. Multivariable regression estimated the odds of prebiopsy prostate MRI. Post hoc analyses examined associations with the registry-level proportion of non-Hispanic Black patients and MRI use, as well as disparities in MRI use in registries with data on more frequent use of prostate MRI. RESULTS: There were 50,719 men identified with prostate cancer (mean age, 72.1 years). Overall, 964 men (1.9% of cohort) had a prebiopsy MRI. Eighty percent of patients with prebiopsy MRI lived in California, New Jersey, or Connecticut. Non-Hispanic Black men (0.6% vs 2.1% non-Hispanic White; odds ratio [OR], 0.28; 95% CI, 0.19-0.40) and men in less urban areas (1.1% vs 2.2% large metro; OR, 0.65; 95% CI, 0.44-0.97) were less likely to have prebiopsy MRI of the prostate. CONCLUSIONS: Non-Hispanic Black patients with prostate cancer and those in less urban areas were less likely to have prebiopsy MRI of the prostate during its initial adoption as a tool for improving prostate cancer detection.

Circulating microRNAs in plasma among men with low-grade and high-grade prostate cancer at prostate biopsy.

BACKGROUND: MicroRNAs (miRNAs or miR-) have been linked to factors associated with aggressive prostate cancer such as biochemical recurrence and metastasis. We investigated whether circulating miRNAs in plasma could be used as diagnostic biomarkers for more aggressive prostate cancer at prostate biopsy. METHODS: Men, aged 40 years and above, newly diagnosed with prostate cancer were categorized into two risk groups, low-grade (Gleason score, 6 or 7 [3 + 4] and serum prostate-specific antigen [PSA], <20 ng/mL) and high-grade (Gleason score, ≥7 (4 + 3) and serum PSA, ≥20 ng/mL) prostate cancers. The limma R package was used to compare the expression of miRNAs in plasma between the two risk groups, adjusting for age. RESULTS: There were 66 men, aged 46-86 years, included: 40 men with low-grade and 26 men with high-grade prostate cancers. There were lower expressions of miR-28, miR-100, miR-942, and miR-28-3p, and higher expressions of miR-708, miR-1298, miR-886-3p, miR-374, miR-376c, miR-202, miR-128a, and miR-185 in high-grade compared to low-grade prostate cancer cases at biopsy, after adjusting for age (P < 0.05). These differences were no longer statistically significant after adjusting the P values for multiple comparisons. CONCLUSION: There was no circulating miRNA associated with high-grade prostate cancer at biopsy after adjusting for age and multiple comparisons. Nevertheless, relationships between these circulating miRNAs and high-grade prostate cancer were observed, which suggest them as promising prostate cancer biomarkers. Further investigation in a larger cohort may provide insight into their diagnostic potential for aggressive prostate cancer.

A four-group urine risk classifier for predicting outcomes in patients with prostate cancer.

OBJECTIVES: To develop a risk classifier using urine-derived extracellular vesicle (EV)-RNA capable of providing diagnostic information on disease status prior to biopsy, and prognostic information for men on active surveillance (AS). PATIENTS AND METHODS: Post-digital rectal examination urine-derived EV-RNA expression profiles (n = 535, multiple centres) were interrogated with a curated NanoString panel. A LASSO-based continuation ratio model was built to generate four prostate urine risk (PUR) signatures for predicting the probability of normal tissue (PUR-1), D'Amico low-risk (PUR-2), intermediate-risk (PUR-3), and high-risk (PUR-4) prostate cancer. This model was applied to a test cohort (n = 177) for diagnostic evaluation, and to an AS sub-cohort (n = 87) for prognostic evaluation. RESULTS: Each PUR signature was significantly associated with its corresponding clinical category (P < 0.001). PUR-4 status predicted the presence of clinically significant intermediate- or high-risk disease (area under the curve = 0.77, 95% confidence interval [CI] 0.70-0.84). Application of PUR provided a net benefit over current clinical practice. In an AS sub-cohort (n = 87), groups defined by PUR status and proportion of PUR-4 had a significant association with time to progression (interquartile range hazard ratio [HR] 2.86, 95% CI 1.83-4.47; P < 0.001). PUR-4, when used continuously, dichotomized patient groups with differential progression rates of 10% and 60% 5 years after urine collection (HR 8.23, 95% CI 3.26-20.81; P < 0.001). CONCLUSION: Urine-derived EV-RNA can provide diagnostic information on aggressive prostate cancer prior to biopsy, and prognostic information for men on AS. PUR represents a new and versatile biomarker that could result in substantial alterations to current treatment of patients with prostate cancer.

Assigning value to preparation for prostate cancer decision making: a willingness to pay analysis.

BACKGROUND: The Personal Patient Profile-Prostate (P3P) is a web-based decision support system for men newly diagnosed with localized prostate cancer that has demonstrated efficacy in reducing decisional conflict. Our objective was to estimate willingness-to-pay (WTP) for men's decisional preparation activities. METHODS: In a multicenter, randomized trial of P3P, usual care group participants received typical preparation for decision making plus referral to publicly-available, educational websites. Intervention group participants received the same, plus online P3P educational media specific to the user's personal preferences and values, and a communication coaching component tailored to race\ethnicity, age and language. WTP data were collected one week after physician consultation. An iterative bidding direct contingent valuation survey format was used, randomly assigning participants to high or low starting values (SV). Tobit models were used to explore associations between SV-adjusted WTP and age, education, marital and work-status, insurance, decision-control preference and decision-making stage. RESULTS: Of 392 participants enrolled, 141 P3P and 107 usual care (UC) provided a WTP value. Men were willing to pay a median $25 (IQR $10-100) for P3P in addition to usual care preparation materials. In the final multivariable tobit regression model, SV, marital status, stage of decision making and income were significantly associated with WTP for P3P. Decision control preference was considered marginally significant (p = 0.11). Men were WTP a median $30 (IQR $10-$200) for usual care material alone. In the final multivariable model, SV, education, and stage of decision making were significantly associated with WTP in usual care. CONCLUSION: WTP was similar for UC and for the addition of P3P to UC decision preparation. The WTP values were associated with demographic and preference variables. Findings can help focus decision support on future patients who would benefit most: those without strong support systems, at earlier stages of decision making, and open to a shared-decision style. TRIAL REGISTRATION: NCT NCT01844999 . Registered May 3, 2013.

Decision Support with the Personal Patient Profile-Prostate: A Multicenter Randomized Trial.

PURPOSE: We evaluated the efficacy of the web based P3P (Personal Patient Profile-Prostate) decision aid vs usual care with regard to decisional conflict in men with localized prostate cancer. MATERIALS AND METHODS: A randomized (1:1), controlled, parallel group, nonblinded trial was performed in 4 regions of the United States. Eligible men had clinically localized prostate cancer and an upcoming consultation, and they spoke and read English or Spanish. Participants answered questionnaires to report decision making stage, personal characteristics, concerns and preferences plus baseline symptoms and decisional conflict. A randomization algorithm allocated participants to receive tailored education and communication coaching, generic teaching sheets and external websites plus a 1-page summary to clinicians (intervention) or the links plus materials provided in clinic (usual care). Conflict outcomes and the number of consultations were measured at 1 month. Univariate and multivariable models were used to analyze outcomes. RESULTS: A total of 392 men were randomized, including 198 to intervention and 194 to usual care, of whom 152 and 153, respectively, returned 1-month outcomes. The mean ± SD 1-month decisional conflict scale (score range 0 to 100) was 10.9 ± 16.7 for intervention and 9.9 ± 18.0 for usual care. The multivariable model revealed significantly reduced conflict in the intervention group (-5.00, 95% CI -9.40--0.59). Other predictors of conflict included income, marital or partner status, decision status, number of consultations, clinical site and D'Amico risk classification. CONCLUSIONS: In this multicenter trial the decision aid significantly reduced decisional conflict. Other variables impacted conflict and modified the effect of the decision aid, notably risk classification, consultations and resources. P3P is an effective adjunct for shared decision making in men with localized prostate cancer.

Clinically Localized Prostate Cancer: AUA/ASTRO/SUO Guideline. Part II: Recommended Approaches and Details of Specific Care Options.

PURPOSE: This guideline is structured to provide a clinical framework stratified by cancer severity to facilitate care decisions and guide the specifics of implementing the selected management options. The summary presented herein represents Part II of the two-part series dedicated to Clinically Localized Prostate Cancer: AUA/ASTRO/SUO Guideline discussing risk stratification and care options by cancer severity. Please refer to Part I for discussion of specific care options and outcome expectations and management. MATERIALS AND METHODS: The systematic review utilized in the creation of this guideline was completed by the Agency for Healthcare Research and Quality and through additional supplementation by ECRI Institute. This review included articles published between January 2007 and March 2014 with an update search conducted through August 2016. When sufficient evidence existed, the body of evidence for a particular treatment was assigned a strength rating of A (high), B (moderate), or C (low) for support of Strong, Moderate, or Conditional Recommendations. Additional information is provided as Clinical Principles and Expert Opinions (table 2 in supplementary unabridged guideline, http://jurology.com/). RESULTS: The AUA (American Urological Association), ASTRO, and SUO (Society of Urologic Oncology) formulated an evidence-based guideline based on a risk stratified clinical framework for the management of localized prostate cancer. CONCLUSIONS: This guideline attempts to improve a clinician's ability to treat patients diagnosed with localized prostate cancer, but higher quality evidence in future trials will be essential to improve the level of care for these patients. In all cases, patient preferences should be considered when choosing a management strategy.

Clinically Localized Prostate Cancer: AUA/ASTRO/SUO Guideline. Part I: Risk Stratification, Shared Decision Making, and Care Options.

PURPOSE: This guideline is structured to provide a clinical framework stratified by cancer severity to facilitate care decisions and guide the specifics of implementing the selected management options. The summary presented represents Part I of the two-part series dedicated to Clinically Localized Prostate Cancer: AUA/ASTRO/SUO Guideline discussing risk stratification and care options by cancer severity. MATERIALS AND METHODS: The systematic review utilized in the creation of this guideline was completed by the Agency for Healthcare Research and Quality and through additional supplementation by ECRI Institute. This review included articles published between January 2007 and March 2014 with an update search conducted through August 2016. When sufficient evidence existed, the body of evidence for a particular treatment was assigned a strength rating of A (high), B (moderate), or C (low) for support of Strong, Moderate, or Conditional Recommendations. Additional information is provided as Clinical Principles and Expert Opinions (table 2 in supplementary unabridged guideline, http://jurology.com/). RESULTS: The AUA (American Urological Association), ASTRO, and SUO (Society of Urologic Oncology) formulated an evidence-based guideline based on a risk stratified clinical framework for the management of localized prostate cancer. CONCLUSIONS: This guideline attempts to improve a clinician's ability to treat patients diagnosed with localized prostate cancer, but higher quality evidence in future trials will be essential to improve the level of care for these patients. In all cases, patient preferences should be considered when choosing a management strategy.

Detection of prostate cancer-specific transcripts in extracellular vesicles isolated from post-DRE urine.

BACKGROUND: The measurement of gene expression in post-digital rectal examination (DRE) urine specimens provides a non-invasive method to determine a patient's risk of prostate cancer. Many currently available assays use whole urine or cell pellets for the analysis of prostate cancer-associated genes, although the use of extracellular vesicles (EVs) has also recently been of interest. We investigated the expression of prostate-, kidney-, and bladder-specific transcripts and known prostate cancer biomarkers in urine EVs. METHODS: Cell pellets and EVs were recovered from post-DRE urine specimens, with the total RNA yield and quality determined by Bioanalyzer. The levels of prostate, kidney, and bladder-associated transcripts in EVs were assessed by TaqMan qPCR and targeted sequencing. RESULTS: RNA was more consistently recovered from the urine EV specimens, with over 80% of the patients demonstrating higher RNA yields in the EV fraction as compared to urine cell pellets. The median EV RNA yield of 36.4 ng was significantly higher than the median urine cell pellet RNA yield of 4.8 ng. Analysis of the post-DRE urine EVs indicated that prostate-specific transcripts were more abundant than kidney- or bladder-specific transcripts. Additionally, patients with prostate cancer had significantly higher levels of the prostate cancer-associated genes PCA3 and ERG. CONCLUSIONS: Post-DRE urine EVs are a viable source of prostate-derived RNAs for biomarker discovery and prostate cancer status can be distinguished from analysis of these specimens. Continued analysis of urine EVs offers the potential discovery of novel biomarkers for pre-biopsy prostate cancer detection.

Clinical Use of Expanded Prostate Cancer Index Composite for Clinical Practice to Assess Patient Reported Prostate Cancer Quality of Life Following Robot-Assisted Radical Prostatectomy.

PURPOSE: EPIC-CP (Expanded Prostate Cancer Index Composite for Clinical Practice) is a short questionnaire that comprehensively measures patient reported health related quality of life at the point of care. We evaluated the feasibility of using EPIC-CP in the routine clinical care of patients with prostate cancer without research infrastructure. We compared longitudinal patient and practitioner reported prostate cancer outcomes. MATERIALS AND METHODS: We reviewed health related quality of life outcomes in 482 patients who underwent radical prostatectomy at our institution from 2010 to 2014. EPIC-CP was administered and interpreted in routine clinical practice without research personnel. We compared practitioner documented rates of incontinence pad use and functional erections to patient reported rates using EPIC-CP. RESULTS: A total of 708 EPIC-CP questionnaires were completed. Mean urinary incontinence domain scores were significantly higher (worse) than baseline (mean ± SD 0.6 ± 0.2) 3 and 6 months after treatment (mean 3.1 ± 2.3 and 2.2 ± 2.1, respectively, each p <0.05) but they returned to baseline at 12 months (mean 1.6 ± 1.7, p >0.05). Mean sexual domain scores were significantly worse than baseline (mean 2.4 ± 2.8) at all posttreatment time points (each p <0.05). Practitioners significantly overestimated incontinence pad-free rates at 3 months (48% vs 39%) and functional erection rates at 3 months (18% vs 12%), 6 months (38% vs 23%) and 12 months (45% vs 23%, each p <0.05). CONCLUSIONS: EPIC-CP is feasible to use in the routine clinical care of patients with prostate cancer without requiring a research infrastructure. Using EPIC-CP in clinical practice may help practitioners objectively assess and appropriately manage posttreatment side effects in patients with prostate cancer.

Relief of Urinary Symptom Burden after Primary Prostate Cancer Treatment.

PURPOSE: Harms of prostate cancer treatment on urinary health related quality of life have been thoroughly studied. In this study we evaluated not only the harms but also the potential benefits of prostate cancer treatment in relieving the pretreatment urinary symptom burden. MATERIALS AND METHODS: In American (1,021) and Spanish (539) multicenter prospective cohorts of men with localized prostate cancer we evaluated the effects of radical prostatectomy, external radiotherapy or brachytherapy in relieving pretreatment urinary symptoms and in inducing urinary symptoms de novo, measured by changes in urinary medication use and patient reported urinary bother. RESULTS: Urinary symptom burden improved in 23% and worsened in 28% of subjects after prostate cancer treatment in the American cohort. Urinary medication use rates before treatment and 2 years after treatment were 15% and 6% with radical prostatectomy, 22% and 26% with external radiotherapy, and 19% and 46% with brachytherapy, respectively. Pretreatment urinary medication use (OR 1.4, 95% CI 1.0-2.0, p = 0.04) and pretreatment moderate lower urinary tract symptoms (OR 2.8, 95% CI 2.2-3.6) predicted prostate cancer treatment associated relief of baseline urinary symptom burden. Subjects with pretreatment lower urinary tract symptoms who underwent radical prostatectomy experienced the greatest relief of pretreatment symptoms (OR 4.3, 95% CI 3.0-6.1), despite the development of deleterious de novo urinary incontinence in some men. The magnitude of pretreatment urinary symptom burden and beneficial effect of cancer treatment on those symptoms were verified in the Spanish cohort. CONCLUSIONS: Men with pretreatment lower urinary tract symptoms may experience benefit rather than harm in overall urinary outcome from primary prostate cancer treatment. Practitioners should consider the full spectrum of urinary symptom burden evident before prostate cancer treatment in treatment decisions.

Evaluation of a 24-gene signature for prognosis of metastatic events and prostate cancer-specific mortality.

OBJECTIVES: To determine the prognostic potential of a 24-gene signature, Sig24, for identifying patients with prostate cancer who are at risk of developing metastases or of prostate cancer-specific mortality (PCSM) after radical prostatectomy (RP). PATIENTS AND METHODS: Sig24 scores were calculated from previously collected gene expression microarray data from the Cleveland Clinic and Mayo Clinic (I and II). The performance of Sig24 was determined using time-dependent c-index analysis, Cox proportional hazards regression and Kaplan-Meier survival analysis. RESULTS: Higher Sig24 scores were significantly associated with higher pathological Gleason scores in all three cohorts. Analysis of the Mayo Clinic II cohort, which included time-to-event information, indicated that patients with high Sig24 scores also had a higher risk of developing metastasis (hazard ratio [HR] 3.78, 95% confidence interval [CI]: 1.96-7.29; P < 0.001) or of PCSM (HR 6.54, 95% CI: 2.16-19.83; P < 0.001). CONCLUSIONS: The findings of the present study show the applicability of Sig24 for the prognosis of metastasis or PCSM after RP. Future studies investigating the combination of Sig24 with available prognostic tests may provide new approaches to improve risk stratification for patients with prostate cancer.

Androgens alter T-cell immunity by inhibiting T-helper 1 differentiation.

The hormonal milieu influences immune tolerance and the immune response against viruses and cancer, but the direct effect of androgens on cellular immunity remains largely uncharacterized. We therefore sought to evaluate the effect of androgens on murine and human T cells in vivo and in vitro. We found that murine androgen deprivation in vivo elicited RNA expression patterns conducive to IFN signaling and T-cell differentiation. Interrogation of mechanism showed that testosterone regulates T-helper 1 (Th1) differentiation by inhibiting IL-12-induced Stat4 phosphorylation: in murine models, we determined that androgen receptor binds a conserved region within the phosphatase, Ptpn1, and consequent up-regulation of Ptpn1 then inhibits IL-12 signaling in CD4 T cells. The clinical relevance of this mechanism, whereby the androgen milieu modulates CD4 T-cell differentiation, was ascertained as we found that androgen deprivation reduced expression of Ptpn1 in CD4 cells from patients undergoing androgen deprivation therapy for prostate cancer. Our findings, which demonstrate a clinically relevant mechanism by which androgens inhibit Th1 differentiation of CD4 T cells, provide rationale for targeting androgens to enhance CD4-mediated immune responses in cancer or, conversely, for modulating androgens to mitigate CD4 responses in disorders of autoimmunity.