Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk patient population

Comprehensive Determination of Prostate Tumor ETS Gene Status in Clinical Samples Using the CLIA Decipher Assay

ETS family gene fusions are common in prostate cancer and molecularly define a tumor subset. ERG is the most commonly rearranged, leading to its overexpression, followed by ETV1, ETV4, and ETV5, and these alterations are generally mutually exclusive. We validated the Decipher prostate cancer assay to detect ETS alterations in a Clinical Laboratory Improvement Amendments-accredited laboratory. Benchmarking against ERG immunohistochemistry and ETV1/4/5 RNA in situ hybridization, we examined the accuracy, precision, and reproducibility of gene expression ETS models using formalin-fixed, paraffin-embedded samples. The m-ERG model achieved an area under curve of 95%, with 93% sensitivity and 98% specificity to predict ERG immunohistochemistry status. The m-ETV1, -ETV4, and -ETV5 models achieved areas under curve of 98%, 88%, and 99%, respectively. The models had 100% robustness for ETS status, and scores were highly correlated across sample replicates. Models predicted 41.5% of a prospective radical prostatectomy cohort (n = 4036) to be ERG⁺, 6.3% ETV1⁺, 1% ETV4⁺, and 0.4% ETV5⁺. Of prostate tumor biopsy samples (n = 509), 41.2% were ERG⁺, 8.6% ETV1⁺, 0.4% ETV4⁺, and none ETV5⁺. Higher Decipher risk status tumors were more likely to be ETS⁺ (ERG or ETV1/4/5) in the radical prostatectomy and the biopsy cohorts (P < 0.05). These results support the utility of microarray-based ETS status prediction models for molecular classification of prostate tumors.

A reported 20-gene expression signature to predict lymph node-positive disease at radical cystectomy for muscle-invasive bladder cancer is clinically not applicable

Background

Neoadjuvant chemotherapy (NAC) for muscle-invasive bladder cancer (MIBC) provides a small but significant survival benefit. Nevertheless, controversies on applying NAC remain because the limited benefit must be weight against chemotherapy-related toxicity and the delay of definitive local treatment. Therefore, there is a clear clinical need for tools to guide treatment decisions on NAC in MIBC. Here, we aimed to validate a previously reported 20-gene expression signature that predicted lymph node-positive disease at radical cystectomy in clinically node-negative MIBC patients, which would be a justification for upfront chemotherapy.

Methods

We studied diagnostic transurethral resection of bladder tumors (dTURBT) of 150 MIBC patients (urothelial carcinoma) who were subsequently treated by radical cystectomy and pelvic lymph node dissection. RNA was isolated and the expression level of the 20 genes was determined on a qRT-PCR platform. Normalized Ct values were used to calculate a risk score to predict the presence of node-positive disease. The Cancer Genome Atlas (TCGA) RNA expression data was analyzed to subsequently validate the results.

Results

In a univariate regression analysis, none of the 20 genes significantly correlated with node-positive disease. The area under the curve of the risk score calculated by the 20-gene expression signature was 0.54 (95% Confidence Interval: 0.44-0.65) versus 0.67 for the model published by Smith et al. Node-negative patients had a significantly lower tumor grade at TURBT (p = 0.03), a lower pT stage (p<0.01) and less frequent lymphovascular invasion (13% versus 38%, p<0.01) at radical cystectomy than node-positive patients. In addition, in the TCGA data, none of the 20 genes was differentially expressed in node-negative versus node-positive patients.

Conclusions

We conclude that a 20-gene expression signature developed for nodal staging of MIBC at radical cystectomy could not be validated on a qRT-PCR platform in a large cohort of dTURBT specimens.

Stromal Gene Expression is Predictive for Metastatic Primary Prostate Cancer

BACKGROUND

Clinical grading systems using clinical features alongside nomograms lack precision in guiding treatment decisions in prostate cancer (PCa). There is a critical need for identification of biomarkers that can more accurately stratify patients with primary PCa.

OBJECTIVE

To identify a robust prognostic signature to better distinguish indolent from aggressive prostate cancer (PCa).

DESIGN, SETTING, AND PARTICIPANTS

To develop the signature, whole-genome and whole-transcriptome sequencing was conducted on five PCa patient-derived xenograft (PDX) models collected from independent foci of a single primary tumor and exhibiting variable metastatic phenotypes. Multiple independent clinical cohorts including an intermediate-risk cohort were used to validate the biomarkers.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The outcome measurement defining aggressive PCa was metastasis following radical prostatectomy. A generalized linear model with lasso regularization was used to build a 93-gene stroma-derived metastasis signature (SDMS). The SDMS association with metastasis was assessed using a Wilcoxon rank-sum test. Performance was evaluated using the area under the curve (AUC) for the receiver operating characteristic, and Kaplan-Meier curves. Univariable and multivariable regression models were used to compare the SDMS alongside clinicopathological variables and reported signatures. AUC was assessed to determine if SDMS is additive or synergistic to previously reported signatures.

RESULTS AND LIMITATIONS

A close association between stromal gene expression and metastatic phenotype was observed. Accordingly, the SDMS was modeled and validated in multiple independent clinical cohorts. Patients with higher SDMS scores were found to have worse prognosis. Furthermore, SDMS was an independent prognostic factor, can stratify risk in intermediate-risk PCa, and can improve the performance of other previously reported signatures.

CONCLUSIONS

Profiling of stromal gene expression led to development of an SDMS that was validated as independently prognostic for the metastatic potential of prostate tumors.

PATIENT SUMMARY

Our stroma-derived metastasis signature can predict the metastatic potential of early stage disease and will strengthen decisions regarding selection of active surveillance versus surgery and/or radiation therapy for prostate cancer patients. Furthermore, profiling of stroma cells should be more consistent than profiling of diverse cellular populations of heterogeneous tumors.

Genomic tests to guide prostate cancer management following diagnosis

INTRODUCTION

Prostate cancer (PCa) is a common cancer in men, but variable clinical behaviors make its management challenging. Risk stratification is a key issue in disease management. Patient-tailored strategies are strongly advocated to reduce unnecessary treatment while maximizing the oncological outcomes of patient who need active treatment in the primary, adjuvant or salvage setting. Recently, tissue-based biomarkers or genomic tests have become available to improve the clinical decision-making. Areas covered: In this review, the authors present recent evidence about these tissue-based biomarkers, discussing the application of each of them in the clinical setting, focusing on the tests aimed to provide a better risk stratification and to guide decision-making after the diagnosis of PCa (i.e. OncotypeDX^Ⓡ, Prolaris^Ⓡ, ProMark^Ⓡ, Ki-67, Decipher^Ⓡ, PTEN, PORTOS, AR-V7 and DNA repair gene mutations). Expert commentary: Even if the clinicopathologic features are still the most frequently-used predictors of disease progression, these tools can be helpful in decision-making at every stage of the PCa management. Actually, OncotypeDX^Ⓡ, Prolaris^Ⓡ and Decipher^Ⓡ are recommended in the clinical setting by guidelines at different steps of PCa management. Consequently, further studies are indispensable to better tailor the right therapy for the right patient and at the right time.

Clinically available RNA profiling tests of prostate tumors: utility and comparison

In the postscreening era, physicians are in need of methods to discriminate aggressive from nonaggressive prostate cancer (PCa) to reduce overdiagnosis and overtreatment. However, studies have shown that prognoses (e.g., progression and mortality) differ even among individuals with similar clinical and pathological characteristics. Existing risk classifiers (TMN grading system, Gleason score, etc.) are not accurately enough to represent the biological features of PCa. Using new genomic technologies, novel biomarkers and classifiers have been developed and shown to add value to clinical or pathological risk factors for predicting aggressive disease. Among them, RNA testing (gene expression analysis) is useful because it can not only reflect genetic variations but also reflect epigenetic regulations. Commercially available RNA profiling tests (Oncotype Dx, Prolaris, and Decipher) have demonstrated strong abilities to discriminate PCa with poor prognosis from less aggressive diseases. For instance, these RNA profiling tests can predict disease progression in active surveillance patients or early recurrence after radical treatments. These tests may offer more dependable methods for PCa prognosis prediction to make more accurate and personal medical 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.

Low PCA3 expression is a marker of poor differentiation in localized prostate tumors: exploratory analysis from 12,076 patients

Background

Prostate cancer antigen 3 (PCA3) is a prostate cancer diagnostic biomarker that has been clinically validated. The limitations of the diagnostic role of PCA3 in initial biopsy and the prognostic role are not well established. Here, we elucidate the limitations of tissue PCA3 to predict high grade tumors in initial biopsy.

Results

PCA3 has a bimodal distribution in both biopsy and radical prostatectomy (RP) tissues, where low PCA3 expression was significantly associated with high grade disease (p<0.001). PCA3 had a poor performance of predicting high grade disease in initial biopsy (GS≥8) with 55% sensitivity and high false negative rates; 42% of high Gleason (≥8) samples had low PCA3. In RP, low PCA3 is associated with adverse pathological features, clinical recurrence outcome and greater probability of metastatic progression (p<0.001).

Materials and Methods

A total of 1,694 expression profiles from biopsy and 10,382 from RP patients with high risk tumors were obtained from the Decipher Genomic Resource Information Database (GRIDTM)prostate cancer database. The primary clinical endpoint was distant metastasis-free survival for RP and high Gleason grade for biopsy. Logistic regression analyses and Cox proportional hazards models were used to evaluate the association of PCA3 with clinical variables and risk of metastasis.

Conclusions

There is high prevalence of high grade tumors with low PCA3 expression in the biopsy setting. Therefore, urologists should be warned that using PCA3 as stand-alone test may lead to high rate of under-diagnosis of high grade disease in initial biopsy setting.

Prostatic compensation of the vitamin D axis in African American men

BACKGROUND. African American (AA) men are disproportionately affected by both prostate cancer (PCa) and vitamin D deficiency compared with European American (EA) men. Vitamin D deficiency is linked to increased PCa aggressiveness and mortality. Therefore, it has been hypothesized that vitamin D deficiency may contribute to the PCa disparity between AA and EA men. METHODS. We studied a cross sectional group of 60 PCa patients (AA, n = 31; EA, n = 29) who underwent radical prostatectomy. Vitamin D metabolites 25-hydroxyvitamin D (25(OH)D) and 1,25-dihydroxyvitamin D (1,25(OH)₂D) were measured in the serum and tissue by uHPLC-MS-MS. Tissue was laser capture microdissected, and gene expression was quantified by microarray. DNA isolated from whole blood was genotyped for West African ancestry markers and vitamin D-related SNPs. RESULTS. Serum concentrations of 25(OH)D were lower in AAs, but concentrations of 1,25(OH)₂D in the prostate tissue were higher compared with EAs. Expression of the vitamin D receptor was higher in prostate tissue from AAs. Expression of the extracellular receptor of vitamin D binding protein, LRP2, was positively associated with West African ancestry and inversely associated with tissue 25(OH)D concentrations in AAs. CONCLUSIONS. The relationships between vitamin D binding protein LRP2 and vitamin D metabolites suggest that the prohormone is actively transported into the prostate, followed by intraprostatic conversion to the active hormone, rather than passive diffusion. These findings support the presence of a compensatory response in prostate tissue to vitamin D deficiency in AAs and reveal a previously unknown complexity involving tissue distribution of vitamin D metabolites. FUNDING. Department of Defense Prostate Cancer Research Program Idea Award for Disparities Research PC121923 (LN and RK) and the NIH 1R01MD007105 (RK).

Epigenomic Regulation of Androgen Receptor Signaling: Potential Role in Prostate Cancer Therapy

Androgen receptor (AR) signaling remains the major oncogenic pathway in prostate cancer (PCa). Androgen-deprivation therapy (ADT) is the principle treatment for locally advanced and metastatic disease. However, a significant number of patients acquire treatment resistance leading to castration resistant prostate cancer (CRPC). Epigenetics, the study of heritable and reversible changes in gene expression without alterations in DNA sequences, is a crucial regulatory step in AR signaling. We and others, recently described the technological advance Chem-seq, a method to identify the interaction between a drug and the genome. This has permitted better understanding of the underlying regulatory mechanisms of AR during carcinogenesis and revealed the importance of epigenetic modifiers. In screening for new epigenomic modifiying drugs, we identified SD-70, and found that this demethylase inhibitor is effective in CRPC cells in combination with current therapies. The aim of this review is to explore the role of epigenetic modifications as biomarkers for detection, prognosis, and risk evaluation of PCa. Furthermore, we also provide an update of the recent findings on the epigenetic key processes (DNA methylation, chromatin modifications and alterations in noncoding RNA profiles) involved in AR expression and their possible role as therapeutic targets.

Active Surveillance of Prostate Cancer: Use, Outcomes, Imaging, and Diagnostic Tools

Active surveillance (AS) has emerged as a standard management option for men with very low-risk and low-risk prostate cancer, and contemporary data indicate that use of AS is increasing in the United States and abroad. In the favorable-risk population, reports from multiple prospective cohorts indicate a less than 1% likelihood of metastatic disease and prostate cancer-specific mortality over intermediate-term follow-up (median 5-6 years). Higher-risk men participating in AS appear to be at increased risk of adverse outcomes, but these populations have not been adequately studied to this point. Although monitoring on AS largely relies on serial prostate biopsy, a procedure associated with considerable morbidity, there is a need for improved diagnostic tools for patient selection and monitoring. Revisions from the 2014 International Society of Urologic Pathology consensus conference have yielded a more intuitive reporting system and detailed reporting of low-intermediate grade tumors, which should facilitate the practice of AS. Meanwhile, emerging modalities such as multiparametric magnetic resonance imaging and tissue-based molecular testing have shown prognostic value in some populations. At this time, however, these instruments have not been sufficiently studied to consider their routine, standardized use in the AS setting. Future studies should seek to identify those platforms most informative in the AS population and propose a strategy by which promising diagnostic tools can be safely and efficiently incorporated into clinical practice.

Utilization of individualized prostate cancer and genomic biomarkers for the practicing urologist

Prostate cancer encompasses a complex heterogeneous disease spectrum. Physicians and patients are faced with the ambiguity of who should be screened, biopsied, rebiopsied, treated, or provided with adjuvant therapy. Personalized outcomes and treatments are especially important given the varied nature of the disease, plethora of treatment options, risks of morbidity, and quality of life. Today's practicing urologist has a multitude of tests from which to choose, creating the difficult task of appropriate use. This review focuses on two blood-, one urine-, and five genomic-based tests, which, when used in the appropriate clinical setting, can facilitate the patient-physician decision-making process.

The Use of Biomarkers in Prostate Cancer Screening and Treatment

Prostate cancer screening and diagnosis has been guided by prostate-specific antigen levels for the past 25 years, but with the most recent US Preventive Services Task Force screening recommendations, as well as concerns regarding overdiagnosis and overtreatment, a new wave of prostate cancer biomarkers has recently emerged. These assays allow the testing of urine, serum, or prostate tissue for molecular signs of prostate cancer, and provide information regarding both diagnosis and prognosis. In this review, we discuss 12 commercially available biomarker assays approved for the diagnosis and treatment of prostate cancer. The results of clinical validation studies and clinical decision-making studies are presented. This information is designed to assist urologists in making clinical decisions with respect to ordering and interpreting these tests for different patients. There are numerous fluid and biopsy-based genomic tests available for prostate cancer patients that provide the physician and patient with different information about risk of future disease and treatment outcomes. It is important that providers be able to recommend the appropriate test for each individual patient; this decision is based on tissue availability and prognostic information desired. Future studies will continue to emphasize the important role of genomic biomarkers in making individualized treatment decisions for prostate cancer patients.

MicroRNA-194 Promotes Prostate Cancer Metastasis by Inhibiting SOCS2

Serum levels of miR-194 have been reported to predict prostate cancer recurrence after surgery, but its functional contributions to this disease have not been studied. Herein, it is demonstrated that miR-194 is a driver of prostate cancer metastasis. Prostate tissue levels of miR-194 were associated with disease aggressiveness and poor outcome. Ectopic delivery of miR-194 stimulated migration, invasion, and epithelial-mesenchymal transition in human prostate cancer cell lines, and stable overexpression of miR-194 enhanced metastasis of intravenous and intraprostatic tumor xenografts. Conversely, inhibition of miR-194 activity suppressed the invasive capacity of prostate cancer cell lines in vitro and in vivo Mechanistic investigations identified the ubiquitin ligase suppressor of cytokine signaling 2 (SOCS2) as a direct, biologically relevant target of miR-194 in prostate cancer. Low levels of SOCS2 correlated strongly with disease recurrence and metastasis in clinical specimens. SOCS2 downregulation recapitulated miR-194-driven metastatic phenotypes, whereas overexpression of a nontargetable SOCS2 reduced miR-194-stimulated invasion. Targeting of SOCS2 by miR-194 resulted in derepression of the oncogenic kinases FLT3 and JAK2, leading to enhanced ERK and STAT3 signaling. Pharmacologic inhibition of ERK and JAK/STAT pathways reversed miR-194-driven phenotypes. The GATA2 transcription factor was identified as an upstream regulator of miR-194, consistent with a strong concordance between GATA2 and miR-194 levels in clinical specimens. Overall, these results offer new insights into the molecular mechanisms of metastatic progression in prostate cancer. Cancer Res; 77(4); 1021-34. ©2016 AACR.

Clinical Utility of Biomarkers in Localized Prostate Cancer

A new generation of prostate cancer (PCa) biomarkers has emerged, including diagnostic serum and urine markers aimed at refining the identification high-grade tumors and tissue-based gene expression assays offering prognostic and predictive clinical information. Such tests seek to improve treatment-related decisions at multiple decision points, including initial diagnosis and following initial primary therapy. In this review, we aim to contextualize the body of evidence surrounding these emerging tests, with attention on studies addressing clinical utility.

How Precisely Can Prostate Cancer Be Managed?

Progress has been made in applying genetic information to disease management in the postgenomic era, and precision medicine is emerging in prostate cancer management. The prostate health index, the 4-kallikrein (4K) score, and the PCA3, TMPRSS2-ERG, and Prostarix tests have potential for refining prostate cancer screening in conjunction with traditional prostate-specific antigen testing. The Confirm MDx and PCA3 tests have shown promise in identifying men who need be rebiopsied after a primary negative biopsy. Oncotype DX, Prolaris, the biopsy-based Decipher prostate cancer test, and ProMark may improve predictive risk stratification in addition to the traditional Gleason score and tumor stage. Decipher and Prolaris may predict biochemical recurrence and metastasis after radical prostatectomy and possibly help identify patients who need adjuvant therapy. Androgen receptor splice variant 7 appears effective in guiding the selection of second hormonal manipulation with abiraterone or enzalutamide versus chemotherapy when treating metastatic castration-resistant prostate cancer.

Molecular Signature to Risk-Stratify Prostate Cancer of Intermediate Risk

A new 30-gene signature has been described that separates prostate cancers of Gleason score ≤6 from those of Gleason score ≥8. It provides independent prognostic information for prostate cancers of intermediate risk (Gleason score of 7), which has the potential to stratify these patients into different risk groups. Clin Cancer Res; 23(1); 6-8. ©2016 AACRSee related article by Sinnott et al., p. 81.

New developments in prostate cancer biomarkers

PURPOSE OF REVIEW

The initial management of localized prostate cancer is increasingly complex with the identification of a growing number of prognostic subgroups. Molecular and genetic biomarkers have been proposed to help clinicians and patients navigate treatment decisions.

RECENT FINDINGS

Three commercially available tests, the Genomic Prostate score, Cell Cycle Progression score, and Genomic Classifier appear to currently have the most supporting data for their use in localized prostate cancer. All three have been shown to identify men at higher risk for poor outcome following radical prostatectomy in retrospective studies whereas the first two have also shown promise in addressing which men might be appropriate for active surveillance. Only the Genomic Classifier has data supporting its use as a predictive marker in addition to a prognostic marker.

SUMMARY

Over the past several years, the management of localized prostate cancer has seen the development of several novel biomarkers aimed at improving decision making. Although a lack of prospective validation makes it challenging to know how best to change management based on the results from any of the tests, the growing body of retrospective data suggests significant promise in this arena.

Development and validation of a 24-gene predictor of response to postoperative radiotherapy in prostate cancer: a matched, retrospective analysis

BACKGROUND

Postoperative radiotherapy has an important role in the treatment of prostate cancer, but personalised patient selection could improve outcomes and spare unnecessary toxicity. We aimed to develop and validate a gene expression signature to predict which patients would benefit most from postoperative radiotherapy.

METHODS

Patients were eligible for this matched, retrospective study if they were included in one of five published US studies (cohort, case-cohort, and case-control studies) of patients with prostate adenocarcinoma who had radical prostatectomy (with or without postoperative radiotherapy) and had gene expression analysis of the tumour, with long-term follow-up and complete clinicopathological data. Additional treatment after surgery was at the treating physician's discretion. In each cohort, patients who had postoperative radiotherapy were matched with patients who had not had radiotherapy using Gleason score, prostate-specific antigen concentration, surgical margin status, extracapsular extension, seminal vesicle invasion, lymph node invasion, and androgen deprivation therapy. We constructed a matched training cohort using patients from one study in which we developed a 24-gene Post-Operative Radiation Therapy Outcomes Score (PORTOS). We generated a pooled matched validation cohort using patients from the remaining four studies. The primary endpoint was the development of distant metastasis.

FINDINGS

In the training cohort (n=196), among patients with a high PORTOS (n=39), those who had radiotherapy had a lower incidence of distant metastasis than did patients who did not have radiotherapy, with a 10-year metastasis rate of 5% (95% CI 0-14) in patients who had radiotherapy (n=20) and 63% (34-80) in patients who did not have radiotherapy (n=19; hazard ratio [HR] 0·12 [95% CI 0·03-0·41], p<0·0001), whereas among patients with a low PORTOS (n=157), those who had postoperative radiotherapy (n=78) had a greater incidence of distant metastasis at 10 years than did their untreated counterparts (n=79; 57% [44-67] vs 31% [20-41]; HR 2·5 [1·6-4·1], p<0·0001), with a significant treatment interaction (p_interaction<0·0001). The finding that PORTOS could predict outcome due to radiotherapy treatment was confirmed in the validation cohort (n=330), which showed that patients who had radiotherapy had a lower incidence of distant metastasis compared with those who did not have radiotherapy, but only in the high PORTOS group (high PORTOS [n=82]: 4% [95% CI 0-10] in the radiotherapy group [n=57] vs 35% [95% CI 7-54] in the no radiotherapy group [n=25] had metastasis at 10 years; HR 0·15 [95% CI 0·04-0·60], p=0·0020; low PORTOS [n=248]: 32% [95% CI 19-43] in the radiotherapy group [n=108] vs 32% [95% CI 22-40] in the no radiotherapy group [n=140]; HR 0·92 [95% CI 0·56-1·51], p=0·76), with a significant interaction (p_interaction=0·016). The conventional prognostic tools Decipher, CAPRA-S, and microarray version of the cell cycle progression signature did not predict response to radiotherapy (p_interaction>0·05 for all).

INTERPRETATION

Patients with a high PORTOS who had postoperative radiotherapy were less likely to have metastasis at 10 years than those who did not have radiotherapy, suggesting that treatment with postoperative radiotherapy should be considered in this subgroup. PORTOS should be investigated further in additional independent cohorts.

FUNDING

None.

Prognostic outlier genes for enhanced prostate cancer treatment

AIM

To review the current landscape of outlier genes in the field of prostate cancer.

METHODS

A comprehensive review was performed.

RESULTS

Prostate cancer continues to be a significant worldwide health issue. In the era of personalized medicine, more emphasis is being placed on the ability to determine the timing, intensity and type of treatment, according to each patient's unique disease. Several commercial tests are available to determine the risk of aggressive prostate cancer based on genomic biomarkers and gene expression. Outlier genes represent a form of cancer classification that focuses on bimodal expression of a gene in a specific subset of patients. Outlier genes identified in prostate cancer include TMPRSS2-ERG, SPINK1, ScHLAP1, NVL, SMC4 and SQLE.

CONCLUSION

Classifying patient prostate cancers by outlier genes may allow for individualized cancer therapies and improved cancer therapy outcomes.

Recent progress and perspectives on prostate cancer biomarkers

The application of prostate-specific antigen (PSA) in prostate cancer (PC) screening, diagnosis, and prognosis has improved the clinical management of PC patients. However, the PSA assay has been faced with criticism due to its potential association with over-diagnosis and subsequent overtreatment of patients with indolent disease. The United States Preventive Services Task Force incited much debate over PSA-based screening in 2012 by recommending against this approach. However, the PSA assay remains the first-line tool for the early detection of PC. This debate highlights the unmet need for non-invasive PC biomarkers with greater sensitivity and specificity that are capable of distinguishing aggressive disease from indolent disease, predicting treatment response, and guiding treatment decisions. Recent investigations into putative PC biomarkers have focused on PSA isoform assays (prostate health index, 4-kallikurein panel), PC-associated genes in the urine (PCA3 and TMPRSS2-ERG), glycan-associated biomarkers (S2, 3PSA, GCNT1, and tri- and tetra-antennary serum N-glycans), and circulating tumor cells. Although substantial efforts to identify novel PC biomarkers that might replace PSA have been put forth, the majority of the putative PC biomarkers reported in the last few years are still under investigation or validation. This review provides an overview of the current state of PC biomarker research and focuses on a few promising PC biomarkers in development.

Prediction of prostate cancer recurrence using quantitative phase imaging: Validation on a general population

Prediction of biochemical recurrence risk of prostate cancer following radical prostatectomy is critical for determining whether the patient would benefit from adjuvant treatments. Various nomograms exist today for identifying individuals at higher risk for recurrence; however, an optimistic under-estimation of recurrence risk is a common problem associated with these methods. We previously showed that anisotropy of light scattering measured using quantitative phase imaging, in the stromal layer adjacent to cancerous glands, is predictive of recurrence. That nested-case controlled study consisted of specimens specifically chosen such that the current prognostic methods fail. Here we report on validating the utility of optical anisotropy for prediction of prostate cancer recurrence in a general population of 192 patients, with 17% probability of recurrence. Our results show that our method can identify recurrent cases with 73% sensitivity and 72% specificity, which is comparable to that of CAPRA-S, a current state of the art method, in the same population. However, our results show that optical anisotropy outperforms CAPRA-S for patients with Gleason grades 7-10. In essence, we demonstrate that anisotropy is a better biomarker for identifying high-risk cases, while Gleason grade is better suited for selecting non-recurrence. Therefore, we propose that anisotropy and current techniques be used together to maximize prediction accuracy.

Patient-Level DNA Damage and Repair Pathway Profiles and Prognosis After Prostatectomy for High-Risk Prostate Cancer

IMPORTANCE

A substantial number of patients diagnosed with high-risk prostate cancer are at risk for metastatic progression after primary treatment. Better biomarkers are needed to identify patients at the highest risk to guide therapy intensification.

OBJECTIVE

To create a DNA damage and repair (DDR) pathway profiling method for use as a prognostic signature biomarker in high-risk prostate cancer.

DESIGN, SETTING, AND PARTICIPANTS

A cohort of 1090 patients with high-risk prostate cancer who underwent prostatectomy and were treated at 3 different academic institutions were divided into a training cohort (n = 545) and 3 pooled validation cohorts (n = 232, 130, and 183) assembled for case-control or case-cohort studies. Profiling of 9 DDR pathways using 17 gene sets for GSEA (Gene Set Enrichment Analysis) of high-density microarray gene expression data from formalin-fixed paraffin-embedded prostatectomy samples with median 10.3 years follow-up was performed. Prognostic signature development from DDR pathway profiles was studied, and DDR pathway gene mutation in published cohorts was analyzed.

MAIN OUTCOMES AND MEASURES

Biochemical recurrence-free, metastasis-free, and overall survival.

RESULTS

Across the training cohort and pooled validation cohorts, 1090 men were studied; mean (SD) age at diagnosis was 65.3 (6.4) years. We found that there are distinct clusters of DDR pathways within the cohort, and DDR pathway enrichment is only weakly correlated with clinical variables such as age (Spearman ρ [ρ], range, -0.07 to 0.24), Gleason score (ρ, range, 0.03 to 0.20), prostate-specific antigen level (ρ, range, -0.07 to 0.10), while 13 of 17 DDR gene sets are strongly correlated with androgen receptor pathway enrichment (ρ, range, 0.33 to 0.82). In published cohorts, DDR pathway genes are rarely mutated. A DDR pathway profile prognostic signature built in the training cohort was significantly associated with biochemical recurrence-free, metastasis-free, and overall survival in the pooled validation cohorts independent of standard clinicopathological variables. The prognostic performance of the signature for metastasis-free survival appears to be stronger in the younger patients (HR, 1.67; 95% CI, 1.12-2.50) than in the older patients (HR, 0.77; 95% CI, 0.29-2.07) on multivariate Cox analysis.

CONCLUSIONS AND RELEVANCE

DNA damage and repair pathway profiling revealed patient-level variations and the DDR pathways are rarely affected by mutation. A DDR pathway signature showed strong prognostic performance with the long-term outcomes of metastasis-free and overall survival that may be useful for risk stratification of high-risk prostate cancer patients.

Decipher correlation patterns post prostatectomy: initial experience from 2 342 prospective patients

Background:

Currently, there are multiple commercially available RNA-based biomarkers that are Medicare approved and suggested for use by the National Comprehensive Cancer Network guidelines. There is uncertainty as to which patients benefit from genomic testing and for whom these tests should be ordered. Here, we examined the correlation patterns of Decipher assay to understand the relationship between the Decipher and patient tumor characteristics.

Methods:

De-identified Decipher test results (including Decipher risk scores and clinicopathologic data) from 2 342 consecutive radical prostatectomy (RP) patients tested between January and September 2015 were analyzed. For clinical testing, tumor specimen from the highest Gleason grade was sampled using a 1.5 mm tissue punch. Decipher scores were calculated based on a previously locked model. Correlations between Decipher score and clinicopathologic variables were computed using Spearman's rank correlation. Mixed-effect linear models were used to study the association of practice type and Decipher score. The significance level was 0.05 for all tests.

Results:

Decipher score had a positive correlation with pathologic Gleason score (PGS; r=0.37, 95% confidence interval (CI) 0.34−0.41), pathologic T-stage (r=0.31, 95% CI 0.28−0.35), CAPRA-S (r=0.32, 95% CI 0.28−0.37) and patient age (r=0.09, 95% CI 0.05-0.13). Decipher reclassified 52%, 76% and 40% of patients in CAPRA-S low-, intermediate- and high-risk groups, respectively. We detected a 28% incidence of high-risk disease through the Decipher score in pT2 patients and 7% low risk in pT3b/pT4, PGS 8−10 patients. There was no significant difference in the Decipher score between patients from community centers and those from academic centers (P=0.82).

Conclusions:

Although Decipher correlated with baseline tumor characteristics for over 2 000 patients, there was significant reclassification of tumor aggressiveness as compared to clinical parameters alone. Utilization of the Decipher genomic classifier can have major implications in assessment of postoperative risk that may impact physician-patient decision making and ultimately patient management.

Molecular Analysis of Low Grade Prostate Cancer Using a Genomic Classifier of Metastatic Potential

PURPOSE

We determined how frequently histological Gleason 3 + 3 = 6 tumors have the molecular characteristics of disease with metastatic potential.

MATERIALS AND METHODS

We analyzed prostatectomy tissue from 337 patients with Gleason 3 + 3 disease. All tissue was re-reviewed in blinded fashion by genitourinary pathologists using 2005 ISUP (International Society of Urological Pathology) Gleason grading criteria. A previously validated Decipher® metastasis signature was calculated in each case based on a locked model. To compare patient characteristics across pathological Gleason score categories we used the Fisher exact test or the ANOVA F test. The distribution of Decipher scores among different clinicopathological groups was compared with the Wilcoxon rank sum test. The association of Decipher score with adverse pathology features was examined using logistic regression models. The significance level of all statistical tests was 0.05.

RESULTS

Of men with Gleason 3 + 3 = 6 disease only 269 (80%) had a low Decipher score with intermediate and high scores in 43 (13%) and 25 (7%), respectively. Decipher scores were significantly higher among pathological Gleason 3 + 3 = 6 specimens from cases with adverse pathological features such as extraprostatic extension, seminal vesicle involvement or positive margins (p <0.001). The median Decipher score in patients with margin negative pT2 disease was 0.23 (IQR 0.09-0.42) compared to 0.30 (IQR 0.17-0.42) in patients with pT3 disease or positive margins (p = 0.005).

CONCLUSIONS

Using a robust and validated prognostic signature we found that a small but not insignificant proportion of histological Gleason 6 tumors harbored molecular characteristics of aggressive cancer. Molecular profiling of such tumors at diagnosis may better select patients for active surveillance at diagnosis and trigger appropriate intervention during followup.

High Dimensional Variable Selection with Error Control

Background. The iterative sure independence screening (ISIS) is a popular method in selecting important variables while maintaining most of the informative variables relevant to the outcome in high throughput data. However, it not only is computationally intensive but also may cause high false discovery rate (FDR). We propose to use the FDR as a screening method to reduce the high dimension to a lower dimension as well as controlling the FDR with three popular variable selection methods: LASSO, SCAD, and MCP. Method. The three methods with the proposed screenings were applied to prostate cancer data with presence of metastasis as the outcome. Results. Simulations showed that the three variable selection methods with the proposed screenings controlled the predefined FDR and produced high area under the receiver operating characteristic curve (AUROC) scores. In applying these methods to the prostate cancer example, LASSO and MCP selected 12 and 8 genes and produced AUROC scores of 0.746 and 0.764, respectively. Conclusions. We demonstrated that the variable selection methods with the sequential use of FDR and ISIS not only controlled the predefined FDR in the final models but also had relatively high AUROC scores.

Prostate cancer radiomics and the promise of radiogenomics

Prostate cancer exhibits intra-tumoral heterogeneity that we hypothesize to be the leading confounding factor contributing to the underperformance of the current pre-treatment clinical-pathological and genomic assessment. These limitations impose an urgent need to develop better computational tools to identify men with low risk of prostate cancer versus others that may be at risk for developing metastatic cancer. The patient stratification will directly translate to patient treatments, wherein decisions regarding active surveillance or intensified therapy are made. Multiparametric MRI (mpMRI) provides the platform to investigate tumor heterogeneity by mapping the individual tumor habitats. We hypothesize that quantitative assessment (radiomics) of these habitats results in distinct combinations of descriptors that reveal regions with different physiologies and phenotypes. Radiogenomics, a discipline connecting tumor morphology described by radiomic and its genome described by the genomic data, has the potential to derive "radio phenotypes" that both correlate to and complement existing validated genomic risk stratification biomarkers. In this article we first describe the radiomic pipeline, tailored for analysis of prostate mpMRI, and in the process we introduce our particular implementations of radiomics modules. We also summarize the efforts in the radiomics field related to prostate cancer diagnosis and assessment of aggressiveness. Finally, we describe our results from radiogenomic analysis, based on mpMRI-Ultrasound (MRI-US) biopsies and discuss the potential of future applications of this technique. The mpMRI radiomics data indicate that the platform would significantly improve the biopsy targeting of prostate habitats through better recognition of indolent versus aggressive disease, thereby facilitating a more personalized approach to prostate cancer management. The expectation to non-invasively identify habitats with high probability of housing aggressive cancers would result in directed biopsies that are more informative and actionable. Conversely, providing evidence for lack of disease would reduce the incidence of non-informative biopsies. In radiotherapy of prostate cancer, dose escalation has been shown to reduce biochemical failure. Dose escalation only to determinate prostate habitats has the potential to improve tumor control with less toxicity than when the entire prostate is dose escalated.

Prostate cancer biomarkers: Are we hitting the mark?

Purpose

Localised prostate cancer diagnosis and management is increasingly complex due to its heterogeneous progression and prognostic subgroups. Pitfalls in current screening and diagnosis have prompted the search for accurate and invasive molecular and genetic biomarkers for prostate cancer. Such tools may be able to distinguish clinically significant cancers from less aggressive variants to assist with prostate cancer risk stratification and guide decisions and healthcare algorithms. We aimed to provide a comprehensive review of the current prostate cancer biomarkers available and in development.

Methods

MEDLINE and EMBASE databases searches were conducted to identify articles pertaining to the use of novel biomarkers for prostate cancer.

Results

A growing number of novel biomarkers are currently under investigation. Such markers include urinary biomarkers, serology-based markers or pathological tissue assessments of molecular and genetic markers. While limited clinical data is present for analysis, early results appear promising. Specifically, a combination of serum and urinary biomarkers (Serum PSA + Urinary PCA3 + Urinary TMPRSS2-ERG fusion) appears to provide superior sensitivity and specificity profiles compared to traditional diagnostic approaches (AUC 0.88).

Conclusion

The accurate diagnosis and risk stratification of prostate cancer is critical to ensure appropriate intervention. The development of non-invasive biomarkers can add to the information provided by current screening practices and allows for individualised risk stratification of patients. The use of these biomarkers appears to increase the sensitivity and specificity of diagnosis of prostate cancer. Further studies are necessary to define the appropriate use and time points of each biomarker and their effect on the management algorithm of prostate cancer.

Multi-institutional Analysis Shows that Low PCAT-14 Expression Associates with Poor Outcomes in Prostate Cancer

BACKGROUND

Long noncoding RNAs (lncRNAs) are an emerging class of relatively underexplored oncogenic molecules with biological and clinical significance. Current inadequacies for stratifying patients with aggressive disease presents a strong rationale to systematically identify lncRNAs as clinical predictors in localized prostate cancer.

OBJECTIVE

To identify RNA biomarkers associated with aggressive prostate cancer.

DESIGN, SETTING, AND PARTICIPANTS

Radical prostatectomy microarray and clinical data was obtained from 910 patients in three published institutional cohorts: Mayo Clinic I (N=545, median follow-up 13.8 yr), Mayo Clinic II (N=235, median follow-up 6.7 yr), and Thomas Jefferson University (N=130, median follow-up 9.6 yr).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary clinical endpoint was distant metastasis-free survival. Secondary endpoints include prostate cancer-specific survival and overall survival. Univariate and multivariate Cox regression were used to evaluate the association of lncRNA expression and these endpoints.

RESULTS AND LIMITATIONS

An integrative analysis revealed Prostate Cancer Associated Transcript-14 (PCAT-14) as the most prevalent lncRNA that is aberrantly expressed in prostate cancer patients. Down-regulation of PCAT-14 expression significantly associated with Gleason score and a greater probability of metastatic progression, overall survival, and prostate cancer-specific mortality across multiple independent datasets and ethnicities. Low PCAT-14 expression was implicated with genes involved in biological processes promoting aggressive disease. In-vitro analysis confirmed that low PCAT-14 expression increased migration while overexpressing PCAT-14 reduced cellular growth, migration, and invasion.

CONCLUSIONS

We discovered that androgen-regulated PCAT-14 is overexpressed in prostate cancer, suppresses invasive phenotypes, and lower expression is significantly prognostic for multiple clinical endpoints supporting its significance for predicting metastatic disease that could be used to improve patient management.

PATIENT SUMMARY

We discovered that aberrant prostate cancer associated transcript-14 expression during prostate cancer progression is prevalent across cancer patients. Prostate cancer associated transcript-14 is also prognostic for metastatic disease and survival highlighting its importance for stratifying patients that could benefit from treatment intensification.

Reconsidering adjuvant versus salvage radiation therapy for prostate cancer in the genomics era

Aim: We developed a decision analysis framework to simulate the clinical choice of early adjuvant versus delayed salvage radiation therapy after radical prostatectomy. Materials & methods: We designed a Markov decision analysis model to represent two alternative treatment approaches for prostate cancer after prostatectomy over a 10-year time horizon. The model contained individualized inputs including genomic classifier score. Sensitivity analyses were performed to evaluate model results. Results: Observation with delayed salvage radiation is preferred according to the base case, with greater average length and quality of life. However, adjuvant therapy is preferred over observation with salvage when genomics-based estimates of recurrence are high. Conclusion: Model results were sensitive to genomics-based estimates of cancer recurrence and to nonprostate cancer mortality.

Evaluation of a genomic classifier in radical prostatectomy patients with lymph node metastasis

Objective

To evaluate the performance of the Decipher test in predicting lymph node invasion (LNI) on radical prostatectomy (RP) specimens.

Methods

We identified 1,987 consecutive patients with RP who received the Decipher test between February and August 2015 (contemporary cohort). In the contemporary cohort, only the Decipher score from RP specimens was available for analysis. In addition, we identified a consecutive cohort of patients treated with RP between 2006 and 2012 at the University of California, San Diego, with LNI upon pathologic examination (retrospective cohort). The retrospective cohort yielded seven, 22, and 18 tissue specimens from prostate biopsy, RP, and lymph nodes (LNs) for individual patients, respectively. Univariable and multivariable logistic regression analyses were used to evaluate the performance of Decipher in the contemporary cohort with LNI as the endpoint. In the retrospective cohort, concordance of risk groups was assessed using validated cut-points for low (<0.45), intermediate (0.45–0.60), and high (>0.60) Decipher scores.

Results

In the contemporary cohort, 51 (2.6%) patients had LNI. Decipher had an odds ratio of 1.73 (95% confidence interval, 1.46–2.05) and 1.42 (95% confidence interval, 1.19–1.7) per 10% increase in score on univariable and multivariable (adjusting for pathologic Gleason score, extraprostatic extension, and seminal vesicle invasion), respectively. No significant difference in the clinical and pathologic characteristics between the LN positive patients of contemporary and retrospective cohorts was observed (all P>0.05). Accordingly, among LN-positive patients in the contemporary cohort and retrospective cohort, 80% and 77% had Decipher high risk scores (P=1). In the retrospective cohort, prostate biopsy cores with the highest Gleason grade and percentage of tumor involvement had 86% Decipher risk concordance with both RP and LN specimens.

Conclusion

Decipher scores were highly concordant between pre- and post-surgical specimens. Further, Decipher scores from RP tissue were predictive of LNI at RP. If validated in a larger cohort of prostate biopsy specimens for prediction of adverse pathology at RP, Decipher may be useful for improved pre-operative staging.

SPINK1 Defines a Molecular Subtype of Prostate Cancer in Men with More Rapid Progression in an at Risk, Natural History Radical Prostatectomy Cohort

PURPOSE

Prostate cancer is clinically and molecularly heterogeneous. We determined the prognosis of men with ERG-ETS fusions and SPINK1 over expression.

MATERIALS AND METHODS

Men were identified with intermediate or high risk localized prostate cancer treated with radical prostatectomy and no therapy before metastasis. A case-cohort design sampled a cohort (262) enriched with metastasis from the entire cohort and a cohort (213) enriched with metastasis from patients with biochemical recurrence. We analyzed transcriptomic profiles and subtyped tumors as m-ERG⁺, m-ETS⁺, m-SPINK1⁺ or Triple Negative (m-ERG^─/m-ETS^─/m-SPINK1^─), and multivariable logistic regression analyses, Kaplan-Meier and multivariable Cox models were used to evaluate subtypes as predictors of clinical outcomes.

RESULTS

Overall 36%, 13%, 11% and 40% of prostate cancer was classified as m-ERG⁺, m-ETS⁺, m-SPINK1⁺ and Triple Negative, respectively. Univariable analysis demonstrated that m-SPINK1⁺ tumors were more common in African-American men (OR 5, 95% CI 1.6-16) but less commonly associated with positive surgical margins (OR 0.16, 95% CI 0.03-0.69) compared to the m-ERG⁺ group. Compared to the Triple Negative group, m-SPINK1⁺ showed similar associations with race and surgical margins in univariable and multivariable analyses across the entire cohort. Survival analyses did not show significant differences among m-ERG⁺, m-ETS⁺ and Triple Negative cases. m-SPINK1⁺ independently predicted prostate cancer specific mortality after metastasis (HR 2.48, 95% CI 0.96-6.4) and biochemical recurrence (HR 3, 95% CI 1.1-8).

CONCLUSIONS

SPINK1 over expression is associated with prostate cancer specific mortality in at risk men with biochemical and clinical recurrence after prostatectomy. ERG-ETS alterations are not prognostic for outcome.

Subclassification of high-risk clinically organ-confined prostate cancer for early cancer-specific mortality after radical prostatectomy

OBJECTIVE

High-risk clinically localized prostate cancer is seen in a highly heterogeneous population with a wide variation of clinical aggressiveness and a novel subclassification for the better prediction of clinical outcomes is needed. The aim of this study is to validate a modified D'Amico risk criteria for substratification of high-risk prostate cancer with regard to the prediction of biochemical recurrence, clinical progression-free survival or prostate cancer-specific mortality after radical prostatectomy.

METHODS

We conducted a retrospective multicenter cohort study including 461 clinically organ-confined (cT1-2), D'Amico high-risk prostate cancer patients who underwent radical prostatectomy with pelvic lymph node dissection. The modified criteria subclassified D'Amico high-risk patients into high-risk (n = 189, single high-risk parameter and two low-risk parameters) and very high-risk (n = 272, at least one more intermediate or high-risk parameter in addition to the qualifying high-risk parameter) groups. Biochemical recurrence-free survival, clinical progression-free survival, prostate cancer-specific mortality and overall survival were analyzed.

RESULTS

The very high-risk group, compared with high-risk group, had significantly poorer biochemical recurrence (5- and 10-year biochemical recurrence-free rates: 52.8 vs 73.9% and 42.1 vs 61.7%, respectively, P < 0.0001), clinical progression-free survival (5- and 10-year survivals: 91.8 vs 98.2% and 80.5 vs 98.2%, respectively, P = 0.0013) and prostate cancer-specific mortality (5- and 10-year mortalities: 2.5 vs 0.0% and 6.7 vs 0.0%, respectively, P = 0.0124).

CONCLUSION

D'Amico high-risk patients can achieve very favorable outcomes unless they are classified as very high risk. Our novel subclassification method is very simple and useful for better patient counseling and decision-making in the pretreatment setting.

The Present and Future of Biomarkers in Prostate Cancer: Proteomics, Genomics, and Immunology Advancements

Prostate cancer (PC) is the second most common form of cancer in men worldwide. Biomarkers have emerged as essential tools for treatment and assessment since the variability of disease behavior, the cost and diversity of treatments, and the related impairment of quality of life have given rise to a need for a personalized approach. High-throughput technology platforms in proteomics and genomics have accelerated the development of biomarkers. Furthermore, recent successes of several new agents in PC, including immunotherapy, have stimulated the search for predictors of response and resistance and have improved the understanding of the biological mechanisms at work. This review provides an overview of currently established biomarkers in PC, as well as a selection of the most promising biomarkers within these particular fields of development.

Efficacy of post-operative radiation in a prostatectomy cohort adjusted for clinical and genomic risk

BACKGROUND

To date, there have been no published trials examining the impact of salvage radiation therapy (SRT) in the post-operative setting for prostate cancer (PCa). We conducted a retrospective, comparative study of post-operative radiation following radical prostatectomy (RP) for men with pT3 disease or positive margins (adverse pathological features, APF).

METHODS

422 PCa men treated at four institutions with RP and having APF were analyzed with a primary end point of metastasis. Adjuvant radiation treatment (ART, n=111), minimal residual disease (MRD) SRT (n=70) and SRT (n=83) were defined by PSA levels of <0.2, 0.2-0.49 and ⩾0.5 ng ml(-1), respectively, before radiation therapy (RT) initiation. Remaining 157 men who did not receive additional therapy before metastasis formed the no RT arm. Clinical-genomic risk was assessed by Cancer of the Prostate Risk Assessment Post-Surgical (CAPRA-S) and Decipher. Cox regression was used to evaluate the impact of treatment on outcome.

RESULTS

During the study follow-up, 37 men developed metastasis with a median follow-up of 8 years. Both CAPRA-S and Decipher had independent predictive value on multivariable analysis for metastasis (P<0.05). Adjusting for clinical-genomic risk, SRT and no RT had hazard ratios of 4.31 (95% confidence interval, 1.20-15.47) and 5.42 (95% confidence interval, 1.59-18.44) for metastasis compared with ART, respectively. No significant difference was observed between MRD-SRT and ART (P=0.28). Men with low-to-intermediate CAPRA-S and low Decipher value have a low rate of metastatic events regardless of treatment selection. In contrast, men with high CAPRA-S and Decipher benefit from ART, however the cumulative incidence of metastasis remains high.

CONCLUSIONS

The decision as to the timing and need for additional local therapy following RP is nuanced and requires providers and patients to balance risks of morbidity with improved oncological outcomes. Post-RP treatment can be safely avoided for men who are low risk by clinical-genomic risk, whereas those at high risk should favor enrollment in clinical trials.

Genomic and epigenomic analysis of high-risk prostate cancer reveals changes in hydroxymethylation and TET1

The clinical heterogeneity of prostate cancer (PCa) makes it difficult to identify those patients that could benefit from more aggressive treatments. As a contribution to a better understanding of the genomic changes in the primary tumor that are associated with the development of high-risk disease, we performed exome sequencing and copy number determination of a clinically homogeneous cohort of 47 high-risk PCas. We confirmed recurrent mutations in SPOP, PTEN and TP53 among the 850 point mutations we detected. In seven cases, we discovered genomic aberrations in the TET1 (Ten-Eleven Translocation 1) gene which encodes a DNA hydroxymethylase than can modify methylated cytosines in genomic DNA and thus is linked with gene expression changes. TET1 protein levels were reduced in tumor versus non-tumor prostate tissue in 39 of 40 cases. The clinical relevance of changes in TET1 levels was demonstrated in an independent PCa cohort, in which low TET1 mRNA levels were significantly associated with worse metastases-free survival. We also demonstrate a strong reduction in hydroxymethylated DNA in tumor tissue in 27 of 41 cases. Furthermore, we report the first exploratory (h)MeDIP-Seq analyses of eight high-risk PCa samples. This reveals a large heterogeneity in hydroxymethylation changes in tumor versus non-tumor genomes which can be linked with cell polarity.

Incorporation of tissue-based genomic biomarkers into localized prostate cancer clinics

Localized prostate cancer (PCa) is a clinically heterogeneous disease, which presents with variability in patient outcomes within the same risk stratification (low, intermediate or high) and even within the same Gleason scores. Genomic tools have been developed with the purpose of stratifying patients affected by this disease to help physicians personalize therapies and follow-up schemes. This review focuses on these tissue-based tools. At present, four genomic tools are commercially available: Decipher™, Oncotype DX®, Prolaris® and ProMark®. Decipher™ is a tool based on 22 genes and evaluates the risk of adverse outcomes (metastasis) after radical prostatectomy (RP). Oncotype DX® is based on 17 genes and focuses on the ability to predict outcomes (adverse pathology) in very low-low and low-intermediate PCa patients, while Prolaris® is built on a panel of 46 genes and is validated to evaluate outcomes for patients at low risk as well as patients who are affected by high risk PCa and post-RP. Finally, ProMark® is based on a multiplexed proteomics assay and predicts PCa aggressiveness in patients found with similar features to Oncotype DX®. These biomarkers can be helpful for post-biopsy decision-making in low risk patients and post-radical prostatectomy in selected risk groups. Further studies are needed to investigate the clinical benefit of these new technologies, the financial ramifications and how they should be utilized in clinics.

Application of a Clinical Whole-Transcriptome Assay for Staging and Prognosis of Prostate Cancer Diagnosed in Needle Core Biopsy Specimens

Molecular and genomic analysis of microscopic quantities of tumor from formalin-fixed, paraffin-embedded biopsy specimens has many unique challenges. Herein, we evaluated the feasibility of obtaining transcriptome-wide RNA expression to measure prognostic classifiers in diagnostic prostate needle core biopsy specimens. One-hundred fifty-eight samples from diagnostic needle core biopsy specimens (BX) and radical prostatectomies (RPs) were collected from 33 patients at three hospitals; each patient provided up to six tumor and benign samples. Genome-wide transcriptomic profiles were generated using Affymetrix Human Exon arrays for comparison of gene expression alterations and prognostic signatures between the BX and RP samples. A sufficient amount of RNA (>100 ng) was obtained from all RP specimens (n = 77) and from 72 of 81 of BX specimens. Of transcriptomic features detected in RP, 95% were detectable in BX tissues and demonstrated a high correlation (r = 0.96). Likewise, an expression signature pattern validated on RPs (Decipher prognostic test) showed correlation between BX and RP (r = 0.70). Of matched BX and RP pairs, 25% showed discordant molecular subtypes. Genome-wide exon arrays yielded data of comparable quality from biopsy and RP tissues. The high concordance of tumor-associated gene expression changes between BX and RP samples provides evidence for the adequate performance of the assay platform with samples from prostate needle biopsy specimens with limited tumor volume.

Multidisciplinary intervention of early, lethal metastatic prostate cancer: Report from the 2015 Coffey-Holden Prostate Cancer Academy Meeting

BACKGROUND

The 2015 Coffey-Holden Prostate Cancer Academy Meeting, themed: "Multidisciplinary Intervention of Early, Lethal Metastatic Prostate Cancer," was held in La Jolla, California from June 25 to 28, 2015.

METHODS

The Prostate Cancer Foundation (PCF) sponsors an annual, invitation-only, action-tank-structured meeting on a critical topic concerning lethal prostate cancer. The 2015 meeting was attended by 71 basic, translational, and clinical investigators who discussed the current state of the field, major unmet needs, and ideas for addressing earlier diagnosis and treatment of men with lethal prostate cancer for the purpose of extending lives and making progress toward a cure.

RESULTS

The questions addressed at the meeting included: cellular and molecular mechanisms of tumorigenesis, evaluating, and targeting the microenvironment in the primary tumor, advancing biomarkers for clinical integration, new molecular imaging technologies, clinical trials, and clinical trial design in localized high-risk and oligometastatic settings, targeting the primary tumor in advanced disease, and instituting multi-modal care of high risk and oligometastatic patients.

DISCUSSION

This article highlights the current status, greatest unmet needs, and anticipated field changes that were discussed at the meeting toward the goal of optimizing earlier interventions to potentiate cures in high-risk and oligometastatic prostate cancer patients.

Biomarkers for evaluation of prostate cancer prognosis

Prostate cancer, with a lifetime prevalence of one in six men, is the second cause of malignancy-related death and the most prevalent cancer in men in many countries. Nowadays, prostate cancer diagnosis is often based on the use of biomarkers, especially prostate-specific antigen (PSA) which can result in enhanced detection at earlier stage and decreasing in the number of metastatic patients. However, because of the low specificity of PSA, unnecessary biopsies and mistaken diagnoses frequently occur. Prostate cancer has various features so prognosis following diagnosis is greatly variable. There is a requirement for new prognostic biomarkers, particularly to differentiate between inactive and aggressive forms of disease, to improve clinical management of prostate cancer. Research continues into finding additional markers that may allow this goal to be attained. We here selected a group of candidate biomarkers including PSA, PSA velocity, percentage free PSA, TGFβ1, AMACR, chromogranin A, IL-6, IGFBPs, PSCA, biomarkers related to cell cycle regulation, apoptosis, PTEN, androgen receptor, cellular adhesion and angiogenesis, and also prognostic biomarkers with Genomic tests for discussion. This provides an outline of biomarkers that are presently of prognostic interest in prostate cancer investigation.

Utilization of a Genomic Classifier for Prediction of Metastasis Following Salvage Radiation Therapy after Radical Prostatectomy

BACKGROUND

Despite salvage radiation therapy (SRT) for recurrent prostate cancer (PCa) after radical prostatectomy (RP), some patients still progress to metastases. Identifying these men would allow them to undergo systemic therapy including testing novel therapies to reduce metastases risk.

OBJECTIVE

To test whether the genomic classifier (GC) predicts development of metastatic disease.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective multi-center and multi-ethnic cohort study from two academic centers and one Veterans Affairs Medical Center in the United States involving 170 men receiving SRT for recurrent PCa post-RP.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Time from SRT to development of metastatic disease tested using Cox regression, survival c-index, and decision curve analysis. Performance of GC was compared to the Cancer of the Prostate Risk Assessment Score and Briganti risk models based on these metrics.

RESULTS AND LIMITATIONS

With a median 5.7 yr follow-up after SRT, 20 patients (12%) developed metastases. On multivariable analysis, for each 0.1 unit increase in GC (scaled from 0 to 1), the hazard ratio for metastasis was 1.58 (95% confidence interval 1.16-2.17; p=0.002). Adjusting for androgen deprivation therapy did not materially change the results. The c-index for GC was 0.85 (95% confidence interval 0.73-0.88) versus 0.63-0.65 for published clinico-pathologic risk models. The 5-yr cumulative incidence of metastasis post-SRT in patients with low, intermediate, and high GC scores was 2.7%, 8.4%, and 33.1%, respectively (p<0.001).

CONCLUSIONS

While validation in larger, prospectively collected cohorts is required, these data suggest GC is a strong predictor of metastases among men receiving SRT for recurrent PCa post-RP, accurately identifying men who are excellent candidates for systemic therapy due to their very high-risk of metastases.

PATIENT SUMMARY

Genomic classifier and two clinico-pathologic risk models were evaluated on their ability to predict metastases among men receiving salvage radiation therapy for recurrent prostate cancer. Genomic classifier was able to identify candidates for further therapies due to their very high-risk of metastases.

Active Surveillance of Prostate Cancer: Use, Outcomes, Imaging, and Diagnostic Tools

Active surveillance (AS) has emerged as a standard management option for men with very low-risk and low-risk prostate cancer, and contemporary data indicate that use of AS is increasing in the United States and abroad. In the favorable-risk population, reports from multiple prospective cohorts indicate a less than 1% likelihood of metastatic disease and prostate cancer-specific mortality over intermediate-term follow-up (median 5-6 years). Higher-risk men participating in AS appear to be at increased risk of adverse outcomes, but these populations have not been adequately studied to this point. Although monitoring on AS largely relies on serial prostate biopsy, a procedure associated with considerable morbidity, there is a need for improved diagnostic tools for patient selection and monitoring. Revisions from the 2014 International Society of Urologic Pathology consensus conference have yielded a more intuitive reporting system and detailed reporting of low-intermediate grade tumors, which should facilitate the practice of AS. Meanwhile, emerging modalities such as multiparametric magnetic resonance imaging and tissue-based molecular testing have shown prognostic value in some populations. At this time, however, these instruments have not been sufficiently studied to consider their routine, standardized use in the AS setting. Future studies should seek to identify those platforms most informative in the AS population and propose a strategy by which promising diagnostic tools can be safely and efficiently incorporated into clinical practice.

Contemporary Role of the Decipher® Test in Prostate Cancer Management: Current Practice and Future Perspectives

We performed a systematic literature search to identify original articles and editorials about the Decipher(®) Prostate Cancer Test (GenomeDx Biosciences, San Diego, CA) to provide an overview of the current literature and its present role in urologic clinical practice. The Decipher test, which uses the expression of 22 selected RNA markers (from a total of over 1.4 million), showed a very high discrimination in predicting clinical metastasis (0.75-0.83) and cancer-specific mortality (0.78) in external validation studies, outperforming all routinely available clinicopathologic characteristics. Further, the timing of postoperative radiotherapy (adjuvant vs salvage) may be guided based on Decipher scores. The Decipher test was also the only independent predictor of clinical metastasis in patients with biochemical recurrence after surgery. The Decipher Genomic Resource Information Database (GRID) is a novel research tool that captures 1.4 million marker expressions per patient and may facilitate precision-guided, individualized care to patients with prostate cancer. In this era of precision medicine, Decipher, along with the Decipher GRID platform, is a promising genomic tool that may aid in managing prostate cancer patients throughout the continuum of care and delivering appropriate treatment at an individualized level.

Differentially Expressed Genes and Signature Pathways of Human Prostate Cancer

Genomic technologies including microarrays and next-generation sequencing have enabled the generation of molecular signatures of prostate cancer. Lists of differentially expressed genes between malignant and non-malignant states are thought to be fertile sources of putative prostate cancer biomarkers. However such lists of differentially expressed genes can be highly variable for multiple reasons. As such, looking at differential expression in the context of gene sets and pathways has been more robust. Using next-generation genome sequencing data from The Cancer Genome Atlas, differential gene expression between age- and stage- matched human prostate tumors and non-malignant samples was assessed and used to craft a pathway signature of prostate cancer. Up- and down-regulated genes were assigned to pathways composed of curated groups of related genes from multiple databases. The significance of these pathways was then evaluated according to the number of differentially expressed genes found in the pathway and their position within the pathway using Gene Set Enrichment Analysis and Signaling Pathway Impact Analysis. The “transforming growth factor-beta signaling” and “Ran regulation of mitotic spindle formation” pathways were strongly associated with prostate cancer. Several other significant pathways confirm reported findings from microarray data that suggest actin cytoskeleton regulation, cell cycle, mitogen-activated protein kinase signaling, and calcium signaling are also altered in prostate cancer. Thus we have demonstrated feasibility of pathway analysis and identified an underexplored area (Ran) for investigation in prostate cancer pathogenesis.

Biomarkers for prostate cancer: present challenges and future opportunities

Prostate cancer (PCa) has variable biological potential with multiple treatment options. A more personalized approach, therefore, is needed to better define men at higher risk of developing PCa, discriminate indolent from aggressive disease and improve risk stratification after treatment by predicting the likelihood of progression. This may improve clinical decision-making regarding management, improve selection for active surveillance protocols and minimize morbidity from treatment. Discovery of new biomarkers associated with prostate carcinogenesis present an opportunity to provide patients with novel genetic signatures to better understand their risk of developing PCa and help forecast their clinical course. In this review, we examine the current literature evaluating biomarkers in PCa. We also address current limitations and present several ideas for future studies.