Urine TMPRSS2:ERG fusion transcript stratifies prostate cancer risk in men with elevated serum PSA

The diverse heterogeneity of molecular alterations in prostate cancer identified through next-generation sequencing

Prostate cancer is a leading cause of global cancer-related death but attempts to improve diagnoses and develop novel therapies have been confounded by significant patient heterogeneity. In recent years, the application of next-generation sequencing to hundreds of prostate tumours has defined novel molecular subtypes and characterized extensive genomic aberration underlying disease initiation and progression. It is now clear that the heterogeneity observed in the clinic is underpinned by a molecular landscape rife with complexity, where genomic rearrangements and rare mutations combine to amplify transcriptomic diversity. This review dissects our current understanding of prostate cancer 'omics', including the sentinel role of copy number variation, the growing spectrum of oncogenic fusion genes, the potential influence of chromothripsis, and breakthroughs in defining mutation-associated subtypes. Increasing evidence suggests that genomic lesions frequently converge on specific cellular functions and signalling pathways, yet recurrent gene aberration appears rare. Therefore, it is critical that we continue to define individual tumour genomes, especially in the context of their expressed transcriptome. Only through improved characterisation of tumour to tumour variability can we advance to an age of precision therapy and personalized oncology.

Biological determinants of health disparities in prostate cancer

PURPOSE OF REVIEW

Prostate cancer mortality rates are highest among men of African ancestry in the United States and globally. Environmental exposures and ancestry-related factors may influence tumor biology and induce a more aggressive disease in this population. Here, we summarize the most recent advances in our understanding of race/ethnic differences in the tumor biology of prostate cancer with an emphasis on the excess disease burden among African-Americans.

RECENT FINDINGS

Results from several DNA methylation studies showed an increased prevalence in DNA hypermethylation at disease-related loci in tumors from African-American patients compared with tumors from European-American patients. Analyses of genome-wide gene expression in prostate tumors revealed frequent alterations in the expression of genes related to immunobiology among the African-American patients, consistent with immune response differences between them and their European-American counterparts. Lastly, population differences in the frequency of oncogenic erythroblast transformation-specific family of transcription factors (ETS)-related gene rearrangements were evaluated in three studies that showed that these alterations manifest themselves most commonly in tumors from men of European ancestry, but are significantly less frequent in men of African ancestry, whereas least common in men of Asian ancestry.

SUMMARY

Analysis of tumor markers indicates that tumor biological differences may exist between prostate cancer patients of African ancestry and those of European or Asian ancestry. These differences could affect disease aggressiveness and response to therapy.

The current and future role of sequence-based analysis in prostate cancer treatment

Prostate cancer is the most commonly diagnosed, nondermatologic malignancy in US men. Localized disease can be managed through active surveillance or curative, locally directed therapies, but 30% of men treated with surgery or radiation will need additional (often systemic) treatment for relapsed disease. While spectacular advances in medical treatment of advanced prostate cancer have improved the quality and duration of patients' lives, metastatic prostate cancer remains an incurable, lethal disease that requires additional therapies and better treatment strategies. The advent of ultra-high-throughput sequencing technology provides an opportunity to comprehensively assess the constellation of genetic and molecular events underlying each patient's tumor, and promises to enhance our ability to deliver specifically tailored personalized treatment to men with prostate cancer. The known biological and clinical heterogeneity of prostate cancer presents both opportunities and challenges to the application and utilization of sequence-based analysis to guide prostate cancer treatment.

Advancing precision medicine for prostate cancer through genomics

Prostate cancer is the most common type of cancer in men and the second leading cause of cancer death in men in the United States. The recent surge of high-throughput sequencing of cancer genomes has supported an expanding molecular classification of prostate cancer. Translation of these basic science studies into clinically valuable biomarkers for diagnosis and prognosis and biomarkers that are predictive for therapy is critical to the development of precision medicine in prostate cancer. We review potential applications aimed at improving screening specificity in prostate cancer and differentiating aggressive versus indolent prostate cancers. Furthermore, we review predictive biomarker candidates involving ETS gene rearrangements, PTEN inactivation, and androgen receptor signaling. These and other putative biomarkers may signify aberrant oncogene pathway activation and provide a rationale for matching patients with molecularly targeted therapies in clinical trials. Lastly, we advocate innovations for clinical trial design to incorporate tumor biopsy and molecular characterization to develop biomarkers and understand mechanisms of resistance.

Urinary biomarkers for prostate cancer: a review

Although the routine use of serum prostate-specific antigen (PSA) testing has undoubtedly increased prostate cancer (PCa) detection, one of its main drawbacks is its lack of specificity. As a consequence, many men undergo unnecessary biopsies or treatments for indolent tumours. PCa-specific markers are needed for the early detection of the disease and the prediction of aggressiveness of a prostate tumour. Since PCa is a heterogeneous disease, a panel of tumour markers is fundamental for a more precise diagnosis. Several biomarkers are promising due to their specificity for the disease in tissue. However, tissue is unsuitable as a possible screening tool. Since urine can be easily obtained in a non-invasive manner, it is a promising substrate for biomarker testing. This article reviews the biomarkers for the non-invasive testing of PCa in urine.

Urinary TMPRSS2:ERG and PCA3 in an active surveillance cohort: results from a baseline analysis in the Canary Prostate Active Surveillance Study

PURPOSE

Active surveillance is used to manage low-risk prostate cancer. Both PCA3 and TMPRSS2:ERG are promising biomarkers that may be associated with aggressive disease. This study examines the correlation of these biomarkers with higher cancer volume and grade determined at the time of biopsy in an active surveillance cohort.

EXPERIMENTAL DESIGN

Urine was collected after digital rectal examination prospectively as part of the multi-institutional Canary Prostate Active Surveillance Study (PASS). PCA3 and TMPRSS2:ERG levels were analyzed in urine collected at study entry. Biomarker scores were correlated to clinical and pathologic variables.

RESULTS

In 387 men, both PCA3 and TMPRSS2:ERG scores were significantly associated with higher volume disease. For a negative repeat biopsy, and 1% to 10%, 11% to 33%, 34% or more positive cores, median PCA3, and TMPRSS2:ERG scores increased incrementally (P < 0.005). Both PCA3 and TMPRSS2:ERG scores were also significantly associated with the presence of high-grade disease. For a negative repeat biopsy, Gleason 6 and Gleason ≥7 cancers, the median PCA3, and TMPRSS2:ERG scores also increased incrementally (P = 0.02 and P = 0.001, respectively). Using the marker scores as continuous variables, the ORs for a biopsy in which cancer was detected versus a negative repeat biopsy (ref) on modeling was 1.41 (95% CI: 1.07-1.85), P = 0.01 for PCA3 and 1.28 (95% CI: 1.10-1.49), P = 0.001 for TMPRSS2:ERG.

CONCLUSIONS

For men on active surveillance, both PCA3 and TMPRSS2:ERG seem to stratify the risk of having aggressive cancer as defined by tumor volume or Gleason score.

PCA3 in the detection and management of early prostate cancer

Although widely used, the value of prostate-specific antigen (PSA) in the detection of prostate cancer is controversial. The percentage of free PSA increases the specificity of PSA, but results are not enough. Prostate cancer gene 3 (PCA3) has been proposed as an option that may complement these markers in the detection and management of early prostate cancer. Our aim has been to review the value of PCA3 as tumor marker. The available results suggest that PCA3 is particularly useful to select in which patients the biopsy should be repeated when the first biopsy was negative. However, some points should be specified with further studies, including the most appropriate PCA3 cutoff level and the significance of a high PCA3 score in patients with negative biopsy. False-negative results are also a conflictive point in the use of PCA3, because prostate cancer, including aggressive tumors, may be present in patients with a low PCA3 score. Probably, a proper interpretation of this test requires its management together with other tests, through multivariate models for the detection of prostate cancer. On the other hand, several studies showed the relation between PCA3 score and Gleason score, and also the utility of PCA3 to select patients for active surveillance. To summarize, the available studies show the utility of PCA3 in the detection and management of early prostate cancer, although some aspects referred to its use need to be retested after further studies to confirm the actual value and the limitations of this test.

Testing for the recurrent HOXB13 G84E germline mutation in men with clinical indications for prostate biopsy

PURPOSE

The G84E variant of HOXB13 was recently found to be associated with a significantly increased risk of prostate cancer in a case control study. We estimated the prevalence of this mutation in a clinical population of men at risk for prostate cancer who were scheduled to undergo prostate biopsy.

MATERIALS AND METHODS

We prospectively collected clinical information and DNA samples from men who underwent diagnostic prostate biopsy between June 2005 and October 2011. We genotyped samples for HOXB13 G84E using the MassARRAY® system. We determined the prevalence of the G84E variant in the overall cohort, among patients with a positive family history and among men age 55 years or younger.

RESULTS

A total of 1,175 subjects underwent biopsy, of whom 948 had a DNA sample for analysis. The G84E variant was detected in 4 patients (prevalence 0.42%, 95% CI 0.12-1.08), of whom 3 had prostate cancer on biopsy. None of 301 patients with a positive family history (prevalence 0.00%, 95% CI 0.00-1.22) and 1 of 226 patients age 55 years or younger tested positive (prevalence 0.44%, 95% CI 0.01-2.44).

CONCLUSIONS

The HOXB13 G84E variant is rare in this cohort, even among those with a positive family history. Our findings question the utility of testing for this variant among unselected men presenting for a diagnostic prostate biopsy.

Urine TMPRSS2:ERG fusion transcript integrated with PCA3 score, genotyping, and biological features are correlated to the results of prostatic biopsies in men at risk of prostate cancer

BACKGROUND

Detection of fusion gene TMPRSS2:ERG transcripts in urine have been recently described in order to refine urine-based detection of prostate cancer (PCa), but data its clinical impact remain scarce. We aimed at investigating the correlation of TMPRSS2:ERG, prostate cancer antigen 3 (PCA3), prostate specific antigen (PSA) density, genetic variants, and androgenic status with outcome and pathological findings at prostatic biopsy.

METHODS

Between 2007 and 2011, 291 patients at risk of PCa because of PSA > 3.0 ng/ml (55%) or candidate to active surveillance protocol justifying restaging biopsy management (45%) were recruited. TMPRSS2:ERG was detected by urine assay (Progensa™). PCA3-score, PSA level, bioavailable testosterone level, prostate volume, rs1447295 and rs6983267 genotypes were prospectively assessed. Univariate and multivariate analysis by logistic regression model (logit) were conducted to study the correlation of TMPRSS2:ERG status, PCA3, and PSA density with biopsy results, and Gleason score.

RESULTS

Of 291 patients, 173 had PCa and 118 had negative biopsy. PCA3 score, PSA density and TMPRSS2:ERG-score were correlated with presence of PCa (P < 0.0001, P = 0.046, and P < 0.0001, respectively). This correlation remained strong on multivariable analysis model (area under curve 0.743). PCA3 score and PSA density were significantly associated with presence of Grade 4 through multivariable analysis. PCA3 score was also correlated to the percentage of positive cores at biopsy (P = 0.008).

CONCLUSIONS

Integration of levels TMPRSS2:ERG transcripts in urine, with PCA3-score, androgenic status, genetic status and traditional clinical variables could significantly increase detection of high risk localized PCa.

Artificial neural networks and prostate cancer--tools for diagnosis and management

Artificial neural networks (ANNs) are mathematical models that are based on biological neural networks and are composed of interconnected groups of artificial neurons. ANNs are used to map and predict outcomes in complex relationships between given 'inputs' and sought-after 'outputs' and can also be used find patterns in datasets. In medicine, ANN applications have been used in cancer diagnosis, staging and recurrence prediction since the mid-1990s, when an enormous effort was initiated, especially in prostate cancer detection. Modern ANNs can incorporate new biomarkers and imaging data to improve their predictive power and can offer a number of advantages as clinical decision making tools, such as easy handling of distribution-free input parameters. Most importantly, ANNs consider nonlinear relationships among input data that cannot always be recognized by conventional analyses. In the future, complex medical diagnostic and treatment decisions will be increasingly based on ANNs and other multivariate models.

Distinct ERG rearrangement prevalence in prostate cancer: higher frequency in young age and in low PSA prostate cancer

Background:

The TMPRSS2-ERG gene fusion resulting in ERG overexpression has been found in around 50% of prostate cancers (PCa) and is a very early event in tumorigenesis. Most studies have reported on selected surgical cohorts with inconsistent results. We hypothesized that ERG gene rearrangements impact tumor development and investigated the frequency of ERG overexpression in the context of clinicopathological tumor characteristics.

Methods:

ERG overexpression (ERG+ or ERG-) was determined by immunohistochemistry (IHC) in 1039 radical prostatectomy (RP) tumors and association with PSA, D'Amico risk score, histopathology, biochemical recurrence, body mass index and age of PCa cases was analyzed.

Results:

ERG+ was associated with younger age at diagnosis (P<0.0001), lower serum PSA (P=0.002) and lower prostate volume (PV) (P=0.001). It was most frequent in the youngest age quartile (⩽55 years, 63.9% ERG+) and decreased constantly with increasing age to 40.8% in the oldest age quartile (⩾67 years, P<0.0001). In the PSA range <4 ng ml⁻¹ the frequency of ERG positivity was 60.2% compared with 47.5 and 49.1% in the PSA ranges 4–10 and ⩾10 ng ml⁻¹, respectively. In the first age quartile, ERG+ patients had lower median serum PSA and fPSA% and smaller PV. In the highest age quartile tumor volume (TV) was increased. Similar differences were observed in the low PSA range. Multivariate analysis identified the first age quartile as a predictor for ERG status (odds ratios (OR) 2.05, P=0.007). No association was found with the D'Amico progression risk score and with biochemical tumor recurrence.

Conclusions:

ERG+ tumors manifest clinically at lower PSA levels and their prevalence is age dependent. This suggests acceleration of tumor development by ERG overexpression that results in earlier tumor detection in young patients. Long-term results are warranted to determine the impact of ERG overexpression on disease outcome.

Early detection of clinically significant prostate cancer at diagnosis: a prospective study using a novel panel of TMPRSS2:ETS fusion gene markers

We explore noninvasive clinical applications of multiple disease-specific fusion markers recently discovered in prostate cancer to predict the risk of cancer occurrence and aggressiveness at diagnosis. A total of 92 men who were prostate-specific antigen (PSA) screened and scheduled for diagnostic biopsy were enrolled for this study. Prospectively collected urine was blind coded for laboratory tests. RNA from urine sediments was analyzed using a panel of 6 TMPRSS2:ETS fusion markers with a sensitive quantitative PCR platform. The pathology reported 39 biopsy-positive cases from 92 patients (42.4%). In urine test, 10 unique combinations of fusion types were detected in 32 of 92 (34.8%) prebiopsy samples. A novel combination of fusion markers, termed Fx (III, IV, ETS), was identified with a sensitivity of 51.3% and an odds ratio of 10.1 in detecting cancer on biopsy. Incorporating a categorical variable of Fx (III, IV, ETS) with urine PCA3 and serum PSA, a regression model was developed to predict biopsy outcomes with an overall accuracy of 77%. Moreover, the overexpression of Fx (III, IV, or ETS) was shown to be an independent predictor to the high-grade cancer, with a predictive accuracy of 80% when coupled with PSA density. The individualized risk scores further stratified a high-risk group that is composed of 92% high-grade cancers and a low-risk group that harbors mainly clinically insignificant cancers. In conclusion, we have identified a novel combination of fusion types very specific to the clinically significant prostate cancer and developed effective regression models to predict biopsy outcomes and aggressive cancers at diagnosis.

Marked heterogeneity of ERG expression in large primary prostate cancers

Approximately 50% of prostate cancers are characterized by TMPRSS2 (transmembrane protease serine 2)-ERG (avian v-ets erythroblastosis virus E26 oncogene homolog) gene fusions resulting in an androgen-regulated overexpression of the transcription factor ERG. Some studies have suggested prognostic or predictive relevance of ERG status in prostate cancer. Such concepts could be impaired by extensive ERG heterogeneity in analyzed tumors. The aim of this study was to analyze the extent of heterogeneity for TMPRSS2-ERG fusion in prostate cancer. To enable large-scale studies on the extent of heterogeneity of biomarkers in prostate cancer, a heterogeneity tissue microarray containing samples from 10 different tumor blocks of 190 large prostate cancers selected from a consecutive series of 480 radical prostatectomies was developed. ERG expression was analyzed by immunohistochemistry. Positive ERG immunostaining was found in arrayed cancer-containing samples from 103 of the 178 analyzable patients (58%). ERG immunostaining was homogeneously positive in 29 prostate cancers (16%), whereas heterogeneous ERG positivity was seen in 74 cancers (42%). ERG heterogeneity was within one tumor focus (intrafocal heterogeneity) in 69 cases (93% of heterogeneous cases) and between different tumor foci (interfocal heterogeneity) in 5 cases (7%). Marked intrafocal heterogeneity challenges the concept of TMPRSS2-ERG fusion always representing an early step in prostate cancer development. Marked heterogeneity also compromises the concept of analyzing ERG status for treatment decisions in diagnostic needle core biopsies.

Risk stratification in prostate cancer screening

Screening for prostate cancer is a controversial topic within the field of urology. The US Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial did not demonstrate any difference in prostate-cancer-related mortality rates between men screened annually rather than on an 'opportunistic' basis. However, in the world's largest trial to date--the European Randomised Study of Screening for Prostate Cancer--screening every 2-4 years was associated with a 21% reduction in prostate-cancer-related mortality rate after 11 years. Citing the uncertain ratio between potential harm and potential benefit, the US Preventive Services Task Force recently recommended against serum PSA screening. Although this ratio has yet to be elucidated, PSA testing--and early tumour detection--is undoubtedly beneficial for some individuals. Instead of adopting a 'one size fits all' approach, physicians are likely to perform personalized risk assessment to minimize the risk of negative consequences, such as anxiety, unnecessary testing and biopsies, overdiagnosis, and overtreatment. The PSA test needs to be combined with other predictive factors or be used in a more thoughtful way to identify men at risk of symptomatic or life-threatening cancer, without overdiagnosing indolent disease. A risk-adapted approach is needed, whereby PSA testing is tailored to individual risk.

New strategies in prostate cancer: translating genomics into the clinic

With the rapidly developing use of next-generation sequencing technologies, there has been a surge in our knowledge of the genomic landscape of prostate cancer and a movement toward developing a molecular subclassification system for the disease. With this new understanding comes great clinical potential, both for the development of biomarkers as well as new therapeutic targets. Herein, we highlight the potential clinical use of recent discoveries and how they fit into our current paradigm. We describe the challenges that lie ahead as we move from genomic sequencing toward routine clinical practice and adopt precision cancer care for patients with prostate cancer.

Personalized management in low-risk prostate cancer: the role of biomarkers

Current criteria to predict low-risk prostate cancer (PCa) are still subject to discussion as a substantial number of PCa patients who progress to a more aggressive disease seem to be missed, using these criteria. The main challenge in PCa diagnosis, therefore, is to distinguish patients with low-risk PCa who will show slow progression of disease from patients at risk for progression to a more aggressive cancer. The current discovered biomarkers could potentially guide in this management and improve detection, staging, and prognosis. This paper provides an overview of the current available serum-, urine-, and tissue-based biomarkers in PCa and evaluates the clinical usefulness of these biomarkers in the detection and management of low-risk PCa.

Comparative assessment of urinary prostate cancer antigen 3 and TMPRSS2:ERG gene fusion with the serum [-2]proprostate-specific antigen-based prostate health index for detection of prostate cancer

BACKGROUND

We compared urinary prostate cancer antigen 3 (PCA3), transmembrane protease, serine 2 (TMPRSS2):v-ets erythroblastosis virus E26 oncogene homolog (avian) (ERG) gene fusion (T2:ERG), and the serum [-2]proprostate-specific antigen ([-2]proPSA)-based prostate health index (Phi) for predicting biopsy outcome.

METHODS

Serum samples and first-catch urine samples were collected after digital rectal examination (DRE) from consented outpatients with PSA 0.5-20 μg/L who were scheduled for prostate biopsy. The PCA3 score (PROGENSA PCA3, Hologic Gen-Probe) and T2:ERG score (Hologic Gen-Probe) were determined. Measurements of serum PSA, free PSA, and [-2]proPSA (Beckman Coulter) were performed, and the percentages of free PSA (%fPSA) and Phi ([-2]proPSA/fPSA × √PSA) were determined.

RESULTS

Of 246 enrolled men, prostate cancer (PCa) was diagnosed in 110 (45%) and there was no evidence of malignancy (NEM) in 136 (55%). A first set of biopsies was performed in 136 (55%) of all men, and 110 (45%) had ≥1 repeat biopsies. PCA3, Phi, and T2:ERG differed significantly between men with PCa and NEM, and these markers showed the largest areas under the ROC curve (AUCs) (0.74, 0.68, and 0.63, respectively). PCA3 had the largest AUC of all parameters, albeit not statistically different from Phi. Phi showed somewhat lower specificities than PCA3 at 90% sensitivity. Combination of both markers enhanced diagnostic power with modest AUC gains of 0.01-0.04. Although PCA3 had the highest AUC in the repeat-biopsy cohort, the highest AUC for Phi was observed in DRE-negative patients with PSA in the 2-10 μg/L range.

CONCLUSIONS

PCA3 and Phi were superior to the other evaluated parameters but their combination gave only moderate enhancements in diagnostic accuracy for PCa at first or repeat prostate biopsy.

Regulators of gene expression as biomarkers for prostate cancer

Recent technological advancements in gene expression analysis have led to the discovery of a promising new group of prostate cancer (PCa) biomarkers that have the potential to influence diagnosis and the prediction of disease severity. The accumulation of deleterious changes in gene expression is a fundamental mechanism of prostate carcinogenesis. Aberrant gene expression can arise from changes in epigenetic regulation or mutation in the genome affecting either key regulatory elements or gene sequences themselves. At the epigenetic level, a myriad of abnormal histone modifications and changes in DNA methylation are found in PCa patients. In addition, many mutations in the genome have been associated with higher PCa risk. Finally, over- or underexpression of key genes involved in cell cycle regulation, apoptosis, cell adhesion and regulation of transcription has been observed. An interesting group of biomarkers are emerging from these studies which may prove more predictive than the standard prostate specific antigen (PSA) serum test. In this review, we discuss recent results in the field of gene expression analysis in PCa including the most promising biomarkers in the areas of epigenetics, genomics and the transcriptome, some of which are currently under investigation as clinical tests for early detection and better prognostic prediction of PCa.

Prospective multicentre evaluation of PCA3 and TMPRSS2-ERG gene fusions as diagnostic and prognostic urinary biomarkers for prostate cancer

BACKGROUND

Prostate cancer antigen 3 (PCA3) and v-ets erythroblastosis virus E26 oncogene homolog (TMPRSS2-ERG) gene fusions are promising prostate cancer (PCa) specific biomarkers that can be measured in urine.

OBJECTIVE

To evaluate the diagnostic and prognostic value of Progensa PCA3 and TMPRSS2-ERG gene fusions (as individual biomarkers and as a panel) for PCa in a prospective multicentre setting.

DESIGN, SETTING, AND PARTICIPANTS

At six centres, post-digital rectal examination first-catch urine specimens prior to prostate biopsies were prospectively collected from 497 men. We assessed the predictive value of Progensa PCA3 and TMPRSS2-ERG (quantitative nucleic acid amplification assay to detect TMPRSS2-ERG messenger RNA [mRNA]) for PCa, Gleason score, clinical tumour stage, and PCa significance (individually and as a marker panel). This was compared with serum prostate-specific antigen and the European Randomised Study of Screening for Prostate Cancer (ERSPC) risk calculator. In a subgroup (n=61) we evaluated biomarker association with prostatectomy outcome.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Univariate and multivariate logistic regression analysis and receiver operating curves were used.

RESULTS AND LIMITATIONS

Urine samples of 443 men contained sufficient mRNA for marker analysis. PCa was diagnosed in 196 of 443 men. Both PCA3 and TMPRSS2-ERG had significant additional predictive value to the ERSPC risk calculator parameters in multivariate analysis (p<0.001 and resp. p=0.002). The area under the curve (AUC) increased from 0.799 (ERSPC risk calculator), to 0.833 (ERSPC risk calculator plus PCA3), to 0.842 (ERSPC risk calculator plus PCA3 plus TMPRSS2-ERG) to predict PCa. Sensitivity of PCA3 increased from 68% to 76% when combined with TMPRSS2-ERG. TMPRSS2-ERG added significant predictive value to the ERSPC risk calculator to predict biopsy Gleason score (p<0.001) and clinical tumour stage (p=0.023), whereas PCA3 did not.

CONCLUSIONS

TMPRSS2-ERG had independent additional predictive value to PCA3 and the ERSPC risk calculator parameters for predicting PCa. TMPRSS2-ERG had prognostic value, whereas PCA3 did not. Implementing the novel urinary biomarker panel PCA3 and TMPRSS2-ERG into clinical practice would lead to a considerable reduction of the number of prostate biopsies.

The emergence of lncRNAs in cancer biology

The discovery of numerous noncoding RNA (ncRNA) transcripts in species from yeast to mammals has dramatically altered our understanding of cell biology, especially the biology of diseases such as cancer. In humans, the identification of abundant long ncRNA (lncRNA) >200 bp has catalyzed their characterization as critical components of cancer biology. Recently, roles for lncRNAs as drivers of tumor suppressive and oncogenic functions have appeared in prevalent cancer types, such as breast and prostate cancer. In this review, we highlight the emerging impact of ncRNAs in cancer research, with a particular focus on the mechanisms and functions of lncRNAs.

Correlation of urine TMPRSS2:ERG and PCA3 to ERG+ and total prostate cancer burden

ERG rearrangements (most commonly transmembrane protease, serine 2 [TMPRSS2]:ERG [T2:ERG] gene fusions) have been identified in approximately 50% of prostate cancers . Quantification of T2:ERG in postdigital rectal examination urine, in combination with PCA3, improves the performance of serum prostate-specific antigen for prostate cancer prediction on biopsy. Here we compared urine T2:ERG and PCA3 scores with ERG+ (determined with immunohistochemical analysis) and total prostate cancer burden in 41 mapped prostatectomies. Prostatectomies had a median of 3 tumor foci (range, 1-15) and 2.6 cm of summed linear tumor dimension (range, 0.6-7.1 cm). Urine T2:ERG score correlated most with summed linear ERG+ tumor dimension and number of ERG+ foci (r(s) = 0.68 and 0.67, respectively, both P < .001). Urine PCA3 score showed weaker correlation with both number of tumor foci (r(s) = 0.34, P = .03) and summed linear tumor dimension (r(s) = 0.26, P = .10). In summary, we demonstrate a strong correlation between urine T2:ERG score and total ERG+ prostate cancer burden at prostatectomy, consistent with high tumor specificity.

TMPRSS2-ERG fusion transcripts in matched urine and needle rinse material after biopsy for the detection of prostate cancer

BACKGROUND

Current methods for detecting TMPRSS2-ERG fusion transcript in the urine of patients with suspected prostate cancer lack diagnostic sensitivity. We combined urine and prostate biopsy rinse material (BRM) assays to improve the fusion gene detection rate.

METHODS

Eighty patients with clinical and/or prostate-specific antigen suspicion of prostate cancer were prospectively included in the study. Urine samples were collected before and after prostate biopsy, and BRM was collected from the biopsy needle. We used reverse-transcription PCR (RT-PCR) for the detection of fusion transcripts. Microfocal cancer (MFC) on biopsy was defined by a single core involved with ≤3 mm of cancer with Gleason score 3 + 3. We statistically assessed the association between RT-PCR and biopsy results.

RESULTS

Urine alone, BRM alone, and both samples were obtained in 4, 19, and 57 patients, respectively. Three patients were excluded because of insufficient material. In the remaining 77 patients, cancer was detected on biopsy in 42 (55%). The diagnostic sensitivity of the assay for cancer detection was 62% (95% CI 47%-78%), 69% (53%-85%), and 89% (73%-99%) with BRM alone, urine alone, and paired samples, respectively. The lowest values were obtained with the urine assay in patients with MFC or Gleason score >3 + 3 cancer. Assays of paired samples provided increased diagnostic sensitivity in all subgroups of patients.

CONCLUSIONS

TMPRSS2-ERG fusion gene detection may be improved by performing assays in both urine and BRM. Insufficient cell numbers in urine samples and cell lysis during centrifugation may explain the low diagnostic sensitivity of the urine assay.

Biomarkers for the diagnosis of new and recurrent prostate cancer

Prostate cancer is the most prevalent cancer in men and can be managed effectively if diagnosed early and monitored. Currently, prostate-specific antigen testing in conjunction with a digital rectal exam has been utilized for screening at-risk men. However, the lack of specificity of prostate-specific antigen as a marker for prostate cancer combined with the asymptomatic and slow-growing nature of prostate tumors has resulted in many men being overdiagnosed and subjected to surgery or treatment with adverse side effects. The focus in the research community currently has been on discovering noninvasive surrogate markers such as proteins, circulating tumor cells and nucleic acids in the blood or urine of patients with prostate cancer. These markers, in combination with prostate-specific antigen, are providing promise that a personalized multiparametric approach to prostate cancer diagnosis and monitoring will aid in managing this disease.

Beyond PSA: the next generation of prostate cancer biomarkers

Since the introduction of serum prostate-specific antigen (PSA) screening 25 years ago, prostate cancer diagnosis and management have been guided by this biomarker. Yet, PSA has proven controversial as a screening assay owing to several inherent limitations. The next wave of prostate cancer biomarkers has emerged, introducing new assays in serum and urine that may supplement or, in time, replace PSA because of their higher cancer specificity. This expanding universe of biomarkers has been facilitated, in large part, by new genomic technologies that have enabled an unbiased look at cancer biology. Such efforts have produced several notable success stories that involve rapidly moving biomarkers from the bench to the clinic. However, biomarker research has centered on disease diagnostics, rather than prognosis and prediction, which would address disease management. The development of biomarkers to stratify risk of prostate cancer aggressiveness at the time of screening remains the greatest unmet clinical need in prostate cancer. We review the current state of prostate cancer biomarker research, including the PSA revolution, its impact on early cancer detection, the recent advances in biomarker discovery, and the future efforts that promise to improve clinical management of this disease.

Toward the detection of prostate cancer in urine: a critical analysis

PURPOSE

Prostate specific antigen and digital rectal examination have low specificity for detecting prostate cancer and they poorly predict the presence of aggressive disease. Urine is readily available and noninvasive, and it represents a promising source of biomarkers for the early detection and prediction of prostate cancer prognosis. We identified promising biomarkers for urine based prostate cancer, examined trends and outlined potential pitfalls.

MATERIALS AND METHODS

We performed PubMed® and Web of Science® database searches of the peer reviewed literature on urine based testing for prostate cancer. Original studies of this subject as well as a small number of reviews were analyzed, including the strengths and weaknesses. We provide a comprehensive review of urine based testing for prostate cancer that covers the technical aspects, including the methodology of urine collection, as well as recent developments in biomarkers spanning the fields of genomics, epigenetics, transcriptomics, proteomics and metabolomics.

RESULTS

The process of urine collection is subject to variability, which may result in conflicting clinical results. Detecting prostate cancer in urine is technically feasible, as demonstrated by numerous proof of principle studies, but few markers have been validated in multiple large sample sets. Biomarker development using urine has been accelerating in recent years with numerous studies identifying DNA, RNA, protein and metabolite based biomarkers in urine. Advanced clinical studies have identified PCA3 and TMPRSS2:ERG fusion transcripts as promising RNA markers for cancer detection and possibly prognosis. DNA methylation analysis of multiple genes improves specificity and represents a promising platform for developing clinical grade assays.

CONCLUSIONS

Urine based testing is noninvasive and represents a rich source of novel biomarkers for prostate cancer. Although urine shows promise for detecting cancer, the ability to identify aggressive subsets of prostate cancer needs further development.

Advanced clinical states in prostate cancer

The classification of clinical disease states within advanced prostate cancer is set apart from other solid tumors largely through measurement of prostate-specific antigen in the blood. This testing has allowed the distinction between the castration-sensitive and the castration-resistant states, to complement radiographic distinction within advanced prostate cancer. This has paved the way for advances in prognostication and treatment of patients within a heterogeneous disease group. Currently used clinical classifications have limitations and continue to evolve. The authors define the current disease states and discuss implications for prognosis and treatment decisions, as well as the limitations of existing classifications and emerging discoveries.

Application of next generation sequencing to human gene fusion detection: computational tools, features and perspectives

Gene fusions are important genomic events in human cancer because their fusion gene products can drive the development of cancer and thus are potential prognostic tools or therapeutic targets in anti-cancer treatment. Major advancements have been made in computational approaches for fusion gene discovery over the past 3 years due to improvements and widespread applications of high-throughput next generation sequencing (NGS) technologies. To identify fusions from NGS data, existing methods typically leverage the strengths of both sequencing technologies and computational strategies. In this article, we review the NGS and computational features of existing methods for fusion gene detection and suggest directions for future development.

Systematic, evidence-based discovery of biomarkers at the NCI

In the past decade, biomarker discovery has become ubiquitous in cancer research. However, despite this interest in biomarker research, few newly-characterized biomarkers have emerged as clinically-used entities. Here, we review the current state of biomarker research in cancer and identify challenges that stall many biomarker discovery efforts. We outline a model for systematic biomarker discovery, exemplified by recent efforts in prostate cancer, in which bioinformatics plays a central role in identifying promising new candidate biomarkers. Finally, we review the role of the National Cancer Institute's Early Detection Research Network (EDRN) in biomarker studies and the importance of EDRN-led efforts to establish a research standard for more effective biomarker discovery efforts.

Circulating microRNAs: macro-utility as markers of prostate cancer?

The realization that microRNAs (miRNAs) are frequently deregulated in malignancy has had a major impact on cancer research. In particular, the recent finding that highly stable forms of miRNAs can be accurately measured in body fluids, including blood, has generated considerable excitement. Here, we discuss the potential of blood-based circulating miRNAs as diagnostic, prognostic, and predictive biomarkers of prostate cancer. We also describe practical considerations that may influence identification and/or measurement of miRNA biomarkers in the circulation. Finally, evidence is prevented for the emerging concept that circulating miRNAs are actively released by their cells of origin and can modulate gene expression at distal sites. These mobile miRNAs, which we term 'hormomirs' because of their hormone-like characteristics, could act as local or long-range signals to maintain normal homeostasis or influence the development and progression of diseases such as cancer.

The epigenetic promise for prostate cancer diagnosis

BACKGROUND

Prostate cancer is the most common cancer diagnosis in men and a leading cause of death. Improvements in disease management would have a significant impact and could be facilitated by the development of biomarkers, whether for diagnostic, prognostic, or predictive purposes. The blood-based prostate biomarker PSA has been part of clinical practice for over two decades, although it is surrounded by controversy. While debates of usefulness are ongoing, alternatives should be explored. Particularly with recent recommendations against routine PSA-testing, the time is ripe to explore promising biomarkers to yield a more efficient and accurate screening for detection and management of prostate cancer. Epigenetic changes, more specifically DNA methylation, are amongst the most common alterations in human cancer. These changes are associated with transcriptional silencing of genes, leading to an altered cellular biology.

METHODS

One gene in particular, GSTP1, has been widely studied in prostate cancer. Therefore a meta-analysis has been conducted to examine the role of this and other genes and the potential contribution to prostate cancer management and screening refinement.

RESULTS

More than 30 independent, peer reviewed studies have reported a consistently high sensitivity and specificity of GSTP1 hypermethylation in prostatectomy or biopsy tissue. The meta-analysis combined and compared these results.

CONCLUSIONS

GSTP1 methylation detection can serve an important role in prostate cancer managment. The meta-analysis clearly confirmed a link between tissue DNA hypermethylation of this and other genes and prostate cancer. Detection of DNA methylation in genes, including GSTP1, could serve an important role in clinical practice.

Defining prostate cancer risk before prostate biopsy

Prostate cancer is the most commonly diagnosed cancer in men. At present, patients are selected for prostate biopsy on the basis of age, serum prostate specific antigen (PSA), and prostatic digital rectal examination (DRE) findings. However, due to limitations in the use of PSA and DRE, many patients undergo unnecessary prostate biopsy. A further problem arises as many patients are diagnosed and treated for indolent disease. This review of the literature highlights the strengths and weaknesses of existing methods of prebiopsy risk stratification and evaluates promising serum, urine, and radiologic prostate cancer biomarkers, which may improve risk stratification for prostate biopsy in the future.

The TMPRSS2:ERG rearrangement, ERG expression, and prostate cancer outcomes: a cohort study and meta-analysis

BACKGROUND

Whether the genomic rearrangement transmembrane protease, serine 2 (TMPRSS2):v-ets erythroblastosis virus E26 oncogene homolog (ERG) has prognostic value in prostate cancer is unclear.

METHODS

Among men with prostate cancer in the prospective Physicians' Health and Health Professionals Follow-Up Studies, we identified rearrangement status by immunohistochemical assessment of ERG protein expression. We used Cox models to examine associations of ERG overexpression with biochemical recurrence and lethal disease (distant metastases or cancer-specific mortality). In a meta-analysis including 47 additional studies, we used random-effects models to estimate associations between rearrangement status and outcomes.

RESULTS

The cohort consisted of 1,180 men treated with radical prostatectomy between 1983 and 2005. During a median follow-up of 12.6 years, 266 men experienced recurrence and 85 men developed lethal disease. We found no significant association between ERG overexpression and biochemical recurrence [hazard ratio (HR), 0.99; 95% confidence interval (CI), 0.78-1.26] or lethal disease (HR, 0.93; 95% CI, 0.61-1.43). The meta-analysis of prostatectomy series included 5,074 men followed for biochemical recurrence (1,623 events), and 2,049 men followed for lethal disease (131 events). TMPRSS2:ERG was associated with stage at diagnosis [risk ratio (RR)(≥T3 vs. T2), 1.23; 95% CI, 1.16-1.30) but not with biochemical recurrence (RR, 1.00; 95% CI, 0.86-1.17) or lethal disease (RR, 0.99; 95% CI, 0.47-2.09).

CONCLUSIONS

These results suggest that TMPRSS2:ERG, or ERG overexpression, is associated with tumor stage but does not strongly predict recurrence or mortality among men treated with radical prostatectomy.

IMPACT

This is the largest prospective cohort study to examine associations of ERG overexpression and lethal prostate cancer among men treated with radical prostatectomy.

Development of an ELISA to detect the secreted prostate cancer biomarker AGR2 in voided urine

BACKGROUND

Comparative transcriptomics between sorted cells identified AGR2 as one of the highest up-regulated genes in cancer. Overexpression in primary tumors was verified by tissue microarray analysis. AGR2 encodes a 19-kDa secreted protein that might be found in urine.

METHODS

Monoclonal antibodies were generated against AGR2. One antibody pair, P1G4 (IgG1) to capture and P3A5 (IgG2a) to detect, showed good performance characteristics in a sandwich ELISA. This assay could detect AGR2 at sub ng/ml quantities.

RESULTS

AGR2 was detected in tissue digestion media of tumor specimens and culture media of AGR2-secreting prostate cancer cell lines. Additional testings involved frozen section immunohistochemistry, immunoprecipitation, and Western blot analysis. Voided urine samples were collected from pre-operative cancer patients, and urinary protein was desalted and concentrated by filtration. The amount of AGR2 detected was scored as pg/100 µg total protein, and then converted to pg/ml urine. The developed ELISA detected AGR2 protein, ranging from 3.6 to 181 pg/ml, in an initial cohort of samples. AGR2 was not detected in the urine of non-cancer and a bladder cancer patient.

CONCLUSIONS

For prostate cancer, an AGR2 urine test could be used for diagnosis. The data, although derived from a small number of samples assayed, showed that developing such a test for clinical application is viable because AGR2 is specific to cancer cells, and apparently secreted into urine.

Potential impact of adding genetic markers to clinical parameters in predicting prostate biopsy outcomes in men following an initial negative biopsy: findings from the REDUCE trial

BACKGROUND

Several germline single nucleotide polymorphisms (SNPs) have been consistently associated with prostate cancer (PCa) risk.

OBJECTIVE

To determine whether there is an improvement in PCa risk prediction by adding these SNPs to existing predictors of PCa.

DESIGN, SETTING, AND PARTICIPANTS

Subjects included men in the placebo arm of the randomized Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial in whom germline DNA was available. All men had an initial negative prostate biopsy and underwent study-mandated biopsies at 2 yr and 4 yr. Predictive performance of baseline clinical parameters and/or a genetic score based on 33 established PCa risk-associated SNPs was evaluated.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Area under the receiver operating characteristic curves (AUC) were used to compare different models with different predictors. Net reclassification improvement (NRI) and decision curve analysis (DCA) were used to assess changes in risk prediction by adding genetic markers.

RESULTS AND LIMITATIONS

Among 1654 men, genetic score was a significant predictor of positive biopsy, even after adjusting for known clinical variables and family history (p = 3.41 × 10(-8)). The AUC for the genetic score exceeded that of any other PCa predictor at 0.59. Adding the genetic score to the best clinical model improved the AUC from 0.62 to 0.66 (p<0.001), reclassified PCa risk in 33% of men (NRI: 0.10; p=0.002), resulted in higher net benefit from DCA, and decreased the number of biopsies needed to detect the same number of PCa instances. The benefit of adding the genetic score was greatest among men at intermediate risk (25th percentile to 75th percentile). Similar results were found for high-grade (Gleason score ≥ 7) PCa. A major limitation of this study was its focus on white patients only.

CONCLUSIONS

Adding genetic markers to current clinical parameters may improve PCa risk prediction. The improvement is modest but may be helpful for better determining the need for repeat prostate biopsy. The clinical impact of these results requires further study.

NGS catalog: A database of next generation sequencing studies in humans

Next generation sequencing (NGS) technologies have been rapidly applied in biomedical and biological research since its advent only a few years ago, and they are expected to advance at an unprecedented pace in the following years. To provide the research community with a comprehensive NGS resource, we have developed the database Next Generation Sequencing Catalog (NGS Catalog, http://bioinfo.mc.vanderbilt.edu/NGS/index.html), a continually updated database that collects, curates and manages available human NGS data obtained from published literature. NGS Catalog deposits publication information of NGS studies and their mutation characteristics (SNVs, small insertions/deletions, copy number variations, and structural variants), as well as mutated genes and gene fusions detected by NGS. Other functions include user data upload, NGS general analysis pipelines, and NGS software. NGS Catalog is particularly useful for investigators who are new to NGS but would like to take advantage of these powerful technologies for their own research. Finally, based on the data deposited in NGS Catalog, we summarized features and findings from whole exome sequencing, whole genome sequencing, and transcriptome sequencing studies for human diseases or traits.

ETS rearrangements in prostate cancer

Prostate cancer is a clinically and molecularly heterogeneous disease. Understanding the biologic underpinning of prostate cancer is necessary to best determine how biology is associated with the risk of disease progression and how this understanding might provide insight into the development of novel therapeutic approaches. The focus of this review is on the recently identified common ETS and non-ETS gene rearrangements in prostate cancer. Although multiple molecular alterations have been detected in prostate cancer, a basic understanding of gene fusion prostate cancer should help explain the clinical and biologic diversity, providing a rationale for a molecular subclassification of the disease.

Interrogating genomic and epigenomic data to understand prostate cancer

Major breakthroughs at the beginning of this century in high-throughput technologies have profoundly transformed biological research. Significant knowledge has been gained regarding our biological system and its disease such as malignant transformation. In this review, we summarize leading discoveries in prostate cancer research derived from the use of high-throughput approaches powered by microarrays and massively parallel next-generation sequencing (NGS). These include the seminal discovery of chromosomal translocations such as TMPRSS2-ERG gene fusions as well as the identification of critical oncogenes exemplified by the polycomb group protein EZH2. We then demonstrate the power of interrogating genomic and epigenomic data in understanding the plethora of mechanisms of transcriptional regulation. As an example, we review how androgen receptor (AR) binding events are mediated at multiple levels through protein-DNA interaction, histone and DNA modifications, as well as high-order chromatin structural changes.

Analysis of serum total and free PSA using immunoaffinity depletion coupled to SRM: correlation with clinical immunoassay tests

Recently, selected reaction monitoring mass spectrometry (SRM-MS) has been more frequently applied to measure low abundance biomarker candidates in tissues and biofluids, owing to its high sensitivity and specificity, simplicity of assay configuration, and exceptional multiplexing capability. In this study, we report for the first time the development of immunoaffinity depletion-based workflows and SRM-MS assays that enable sensitive and accurate quantification of total and free prostate-specific antigen (PSA) in serum without the requirement for specific PSA antibodies. Low ng/mL level detection of both total and free PSA was consistently achieved in both PSA-spiked female serum samples and actual patient serum samples. Moreover, comparison of the results obtained when SRM PSA assays and conventional immunoassays were applied to the same samples showed good correlation in several independent clinical serum sample sets. These results demonstrate that the workflows and SRM assays developed here provide an attractive alternative for reliably measuring candidate biomarkers in human blood, without the need to develop affinity reagents. Furthermore, the simultaneous measurement of multiple biomarkers, including the free and bound forms of PSA, can be performed in a single multiplexed analysis using high-resolution liquid chromatographic separation coupled with SRM-MS. This article is part of a Special Issue entitled: Translational Proteomics.

Prostate cancer - a biomarker perspective

Despite early detection and reduced risk of death, prostate cancer still remains the second leading cause of cancer death in American men. There is currently no cure for advanced prostate cancer. The multistage, stochastic and highly heterogeneous nature of prostate cancer, coupled with genetic and epigenetic alterations that occur during disease progression and response to therapy, represent fundamental challenges in our quest to understand and control this complex and prevalent disease. Recent advances in drug development and breakthroughs in omics technologies have renewed our efforts to identify novel biomarkers for prostate cancer prognosis, prediction, and therapeutic response monitoring. In this perspective article, we overview the current status and highlight future prospects of biomarkers for prostate cancer, a disease that affects millions of men worldwide.

Oncogenic activation of ERG: A predominant mechanism in prostate cancer

Prevalent gene fusions involving regulatory sequences of the androgen receptor (AR) regulated genes (primarily TMPRSS2) and protein coding sequences of nuclear transcription factors of the ETS gene family (predominantly ERG) result in unscheduled androgen dependent ERG expression in prostate cancer (CaP).Cumulative data from a large number of studies in the past six years accentuate ERG alterations in more than half of all CaP patients in Western countries. Studies underscore that ERG functions are involved in the biology of CaP. ERG expression in normal context is selective to endothelial cells, specific hematopoetic cells and pre-cartilage cells. Normal functions of ERG are highlighted in hematopoetic stem cells. Emerging data continues to unravel molecular and cellular mechanisms by which ERG may contribute to CaP. Herein, we focus on biological and clinical aspects of ERG oncogenic alterations, potential of ERG-based stratification of CaP and the possibilities of targeting the ERG network in developing new therapeutic strategies for the disease.

Long non-coding RNAs in Huntington's disease neurodegeneration

Neurodegeneration in the brains of Huntington's disease patients is accompanied by widespread changes in gene regulatory networks. Recent studies have found that these changes are not restricted to protein-coding genes, but also include non-coding RNAs (ncRNAs). One particularly abundant but poorly understood class of ncRNAs is the long non-coding RNAs (lncRNAs), of which at least ten thousand have been identified in the human genome. Although we presently know little about their function, lncRNAs are widely expressed in the mammalian nervous system, and many are likely to play critical roles in neuronal development and activity. LncRNAs are now being implicated in neurodegenerative processes, including Alzheimer's (AD) and Huntington's disease (HD). In the present study, I discuss the potential significance of lncRNAs in HD. To support this, I have mined existing microarray data to discover seven new lncRNAs that are dysregulated in HD brains. Interestingly, several of these contain genomic binding sites for the transcriptional repressor REST, a key mediator of transcriptional changes in HD, including the known REST target lncRNA, DGCR5. Previously described lncRNAs TUG1 (necessary for retinal development) and NEAT1 (a structural component of nuclear paraspeckles) are upregulated in HD caudate, while the brain-specific tumour-suppressor MEG3 is downregulated. Three other lncRNAs of unknown function are also significantly changed in HD brains. Many lncRNAs regulate gene expression through formation of epigenetic ribonucleoprotein complexes, including TUG1 and MEG3. These findings lead me to propose that lncRNA expression changes in HD are widespread, that many of these result in altered epigenetic gene regulation in diseased neurons, and that contributes to neurodegeneration. Therefore, elucidating lncRNA network changes in HD may be important in understanding and treating this and other neurodegenerative processes.

Organ Specific Tumor Markers: What's New?

Tumor markers are molecules produced in the body in response to cancer. An ideal tumor marker should have high sensitivity and specificity, should be cheap, and should be easily detected in body fluids. Identification of novel markers is important and it is expected that with the advent of newer technologies, more reliable markers will be discovered. This review discusses the currently available tumor markers for different malignancies.