A novel diagnostic test for prostate cancer emerges from the determination of alpha-methylacyl-coenzyme a racemase in prostatic secretions

Evaluation and multi-institutional validation of a novel urine biomarker lncRNA546 to improve the diagnostic specificity of prostate cancer in PSA gray-zone

Background and objectives

Prostate specific antigen (PSA) is currently the most commonly used biomarker for prostate cancer diagnosis. However, when PSA is in the gray area of 4-10 ng/ml, the diagnostic specificity of prostate cancer is extremely low, leading to overdiagnosis in many clinically false-positive patients. This study was trying to discover and evaluate a novel urine biomarker long non-coding RNA (lncRNA546) to improve the diagnostic accuracy of prostate cancer in PSA gray-zone.

Methods

A cohort study including consecutive 440 participants with suspected prostate cancer was retrospectively conducted in multi-urology centers. LncRNA546 scores were calculated with quantitative real-time polymerase chain reaction. The area under the receiver operating characteristic curve (AUROC), decision curve analysis (DCA) and a biopsy-specific nomogram were utilized to evaluate the potential for clinical application. Logistic regression model was constructed to confirm the predictive power of lncRNA546.

Results

LncRNA546 scores were sufficient to discriminate positive and negative biopsies. ROC analysis showed a higher AUC for lncRNA546 scores than prostate cancer antigen 3 (PCA3) scores (0.78 vs. 0.66, p<0.01) in the overall cohort. More importantly, the AUC of lncRNA546 (0.80) was significantly higher than the AUCs of total PSA (0.57, p=0.02), percentage of free PSA (%fPSA) (0.64, p=0.04) and PCA3 (0.63, p<0.01) in the PSA 4-10 ng/ml cohort. A base model constructed by multiple logistic regression analysis plus lncRNA546 scores improved the predictive accuracy (PA) from 79.8% to 86.3% and improved AUC results from 0.862 to 0.915. DCA showed that the base model plus lncRNA546 displayed greater net benefit at threshold probabilities beyond 15% in the PSA 4-10 ng/ml cohort.

Conclusion

LncRNA546 is a promising novel biomarker for the early detection of prostate cancer, especially in the PSA 4-10 ng/ml cohort.

Identification of Clinically Significant Prostate Cancer by Combined PCA3 and AMACR mRNA Detection in Urine Samples

Purpose

Preclinical evaluation of PCA3 and AMACR transcript simultaneous detection in urine to diagnose clinical significant prostate cancer (prostate cancer with Gleason score ≥7) in a Russian cohort.

Patients and Methods

We analyzed urine samples of patients with a total serum PSA ≥2 ng/mL: 31 men with prostate cancer scheduled for radical prostatectomy, 128 men scheduled for first diagnostic biopsy (prebiopsy cohort). PCA3, AMACR, PSA and GPI transcripts were detected by multiplex reverse transcription quantitative polymerase chain reaction, and the results were used for scores for calculation and statistical analysis.

Results

There was no significant difference between clinically significant and nonsignificant prostate cancer PCA3 scores. However, there was a significant difference in the AMACR score (patients scheduled for radical prostatectomy p=0.0088, prebiopsy cohort p=0.029). We estimated AUCs, optimal cutoffs, sensitivities and specificities for PCa and csPCa detection in the prebiopsy cohort by tPSA, PCA3 score, PCPT Risk Calculator and classification models based on tPSA, PCA3 score and AMACR score. In the clinically significant prostate cancer ROC analysis, the PCA3 score AUC was 0.632 (95%CI: 0.511–0.752), the AMACR score AUC was 0.711 (95%CI: 0.617–0.806) and AUC of classification model based on the PCA3 score, the AMACR score and total PSA was 0.72 (95%CI: 0.58–0.83). In addition, the correlation of the AMACR score with the ratio of total RNA and RNA of prostate cells in urine was shown (tau=0.347, p=6.542e–09). Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use.

Conclusion

The AMACR score is a good predictor of clinically significant prostate cancer. Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. Evaluation of the AMACR score and classification models based on it for clinically significant prostate cancer detection with larger samples and a follow-up analysis is promising.

Prostate Cancer Diagnosis Using Urine Sediment Analysis-Based α-Methylacyl-CoA Racemase Score: A Single-Center Experience

To evaluate the diagnostic value of α-methylacyl-CoA racemase (AMACR) score in Han Chinese patients with prostate cancer (PCa) through urine sediment analysis. We collected 292 urine sediment samples after digital rectal examination. Levels of AMACR and prostate-specific antigen (PSA) messenger RNA (mRNAs) were evaluated by quantitative real time-polymerase chain reaction. The diagnostic value of AMACR score was assessed by receiver-operating characteristic analysis (ROC), Mann-Whitney test, logistic regression analysis and decision curve analysis. In all patients (n = 292), the area under the curve (AUC) for serum PSA, AMACR score, and a combinative model of these 2 parameters were 0.745 (95% confidence interval [CI]: 0.691-0.794), 0.753 (95% CI: 0.700-0.802), and 0.784 (95% CI: 0.732-0.830). No statistical difference was found between AMACR score and serum PSA (P = .826), while the combinative model was better than AMACR score (Z = 5.222, P < .001). Among patients with serum PSA level of 4 to 10 ng/mL (n = 121), the AMACR score was significantly higher in patients with PCa (P = 0.0002), while serum PSA showed no difference (P = 0.3023). Alpha-methylacyl-CoA racemase score (AUC = 0.712, 95% CI: 0.623-0.790) and a combinative model (AUC = 0.714, 95% CI: 0.626-0.793) showed a better diagnostic value than serum PSA (AUC = 0.559, 95% CI: 0.466-0.649), (P = .048, P = .042). Decision curve analysis showed a biopsy prediction model including AMACR score have a better net benefit when the threshold probability greater than 20%. The diagnostic model combing serum PSA and AMACR score has a better diagnostic value in patients with abnormal PSA level (including PSA level ranging from 4-10 ng/mL), and could reduce unnecessary prostate biopsy in clinical use.

Approaches to urinary detection of prostate cancer

Background:

Prostate cancer is the most common cancer in American men that ranges from low risk states amenable to active surveillance to high risk states that can be lethal especially if untreated. There is a critical need to develop relatively non-invasive and clinically useful methods for screening, detection, prognosis, disease monitoring, and prediction of treatment efficacy. In this review, we focus on important advances as well as future efforts needed to drive clinical innovation in this area of urine biomarker research for prostate cancer detection and prognostication.

Methods:

We provide a review of current literature on urinary biomarkers for prostate cancer. We evaluate the strengths and limitations of a variety of approaches that vary in sampling strategies and targets measured; discuss reported urine tests for prostate cancer with respect to their technical, analytical, and clinical parameters; and provide our perspectives on critical considerations in approaches to developing a urine-based test for prostate cancer.

Results:

There has been an extensive history of exploring urine as a source of biomarkers for prostate cancer that has resulted in a variety of urine tests that are in current clinical use. Importantly, at least three tests have demonstrated high sensitivity (~90%) and negative predictive value (~95%) for clinically significant tumors; however, there has not been widespread adoption of these tests.

Conclusions:

Conceptual and methodological advances in the field will help to drive the development of novel urinary tests that in turn may lead to a shift in the clinical paradigm for prostate cancer diagnosis and management.

Semen AMACR protein as a novel method for detecting prostate cancer

BACKGROUND

Alpha methylacyl A coenzyme racemase (AMACR) has shown to be an excellent immunohistological biomarker for prostate cancer (CaP). Given the connection between prostate and urethra, we hypothesized that semen ejaculate would be an ideal specimen for detection of CaP specific biomarkers, such as AMACR. This study explores the detection of semen AMACR protein in men with and without CaP.

METHODS

Semen ejaculates from 28 biopsy proven CaP patients prior to radical prostatectomy and 15 age-comparable controls were analyzed. An indirect sandwich ELISA chemiluminescence assay was used to detect semen AMACR, PSA, and Matriptase proteins. Tissue AMACR protein was quantified in 12 corresponding prostatectomy specimens using automated quantitative analysis (AQUA).

RESULTS

Semen AMACR protein was detected in 23 of 28 (82%) CaP patients and 23 of 24 (96%) CaP patients with significant tumor volume (>0.5 cc or 0.3 g). Among the 5 cancer patients with undetectable semen AMACR, 4 patients had small tumor volumes (<1% or 0.3 g). Semen AMACR protein was also detected in 7 of 15 (47%) control noncancer patients. Using 76 ng/ml as a cutoff value, 20 of 28 (71%) patients and 20 of 24 (83%) patients with significant tumor volume were positive for semen AMACR protein, whereas only 5 of 15 (33%) age-comparable controls were positive. AMACR levels degrade with time.

CONCLUSIONS

This is the first study to demonstrate that AMACR protein is detectable in semen ejaculate. The higher AMACR levels detected in cancer patients suggests that semen AMACR protein may be useful as a noninvasive test for prostate cancer. Further validation is warranted.

α-methylacyl-CoA racemase (AMACR) expression in chordomas differentiates them from chondrosarcomas

Aims: Chordomas and chondrosarcomas are malignant mesenchymal tumours with overlapping morphological and immunohistochemical (IHC) characteristics. Our aim was to evaluate the IHC expression of α-methylacyl-CoA racemase (AMACR/P504S), β-catenin and E-cadherin in chordomas relative to chondrosarcomas and assess the utility of these markers for differential diagnosis. Methods: Archival sections of 18 chordomas, 19 chondrosarcomas and 10 mature cartilage samples were immunostained and scored for AMACR, β-catenin and E-cadherin and the relative differential capacity of each marker was calculated. In addition, AMACR mRNA level was assessed in 5 chordomas by RT-PCR and evaluated by comparative C_T method. Results: AMACR and β-catenin stained 88.9% and 94.1% of the chordomas respectively, 21.1% and 10.5% of the chondrosarcomas correspondingly and none of the mature cartilage samples. E-cadherin stained positively 82.4% of the chordomas, 36.8% of the chondrosarcomas and 42.9% of the mature cartilage cases. Both AMACR and β-catenin showed statistically significant difference between chordomas and chondrosarcomas (p < 0.001 for both), unlike E-cadherin. AMACR was detected at the mRNA level. Conclusions: AMACR is expressed in most of the chordomas but only in a minority of chondrosarcomas. AMACR may serve as IHC marker of chordoma with differentiating ability comparable to that of β-catenin.

Using gene expression from urine sediment to diagnose prostate cancer: development of a new multiplex mRNA urine test and validation of current biomarkers

Background

Additional accurate non-invasive biomarkers are needed in the clinical setting to improve prostate cancer (PCa) diagnosis. Here we have developed a new and improved multiplex mRNA urine test to detect prostate cancer (PCa). Furthermore, we have validated the PCA3 urinary transcript and some panels of urinary transcripts previously reported as useful diagnostic biomarkers for PCa in our cohort.

Methods

Post-prostatic massage urine samples were prospectively collected from PCa patients and controls. Expression levels of 42 target genes selected from our previous studies and from the literature were studied in 224 post-prostatic massage urine sediments by quantitative PCR. Univariate logistic regression was used to identify individual PCa predictors. A variable selection method was used to develop a multiplex biomarker model. Discrimination was measured by ROC curve AUC for both, our model and the previously published biomarkers.

Results

Seven of the 42 genes evaluated (PCA3, ELF3, HIST1H2BG, MYO6, GALNT3, PHF12 and GDF15) were found to be independent predictors for discriminating patients with PCa from controls. We developed a four-gene expression signature (HIST1H2BG, SPP1, ELF3 and PCA3) with a sensitivity of 77 % and a specificity of 67 % (AUC = 0.763) for discriminating between tumor and control urines. The accuracy of PCA3 and previously reported panels of biomarkers is roughly maintained in our cohort.

Conclusions

Our four-gene expression signature outperforms PCA3 as well as previously reported panels of biomarkers to predict PCa risk. This study suggests that a urinary biomarker panel could improve PCa detection. However, the accuracy of the panels of urinary transcripts developed to date, including our signature, is not high enough to warrant using them routinely in a clinical setting.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2127-2) contains supplementary material, which is available to authorized users.

Development and prospective multicenter evaluation of the long noncoding RNA MALAT-1 as a diagnostic urinary biomarker for prostate cancer

The current strategy for diagnosing prostate cancer (PCa) is mainly based on the serum prostate-specific antigen (PSA) test. However, PSA has low specificity and has led to numerous unnecessary biopsies. We evaluated the effectiveness of urinary metastasis-associated lung adenocarcinoma transcript 1 (MALAT-1), a long noncoding RNA, for predicting the risk of PCa before biopsy. The MALAT-1 score was tested in a discovery phase and a multi-center validation phase. The predictive power of the MALAT-1 score was evaluated by the area under receiver operating characteristic (ROC) curve (AUC) and by decision curve analysis. As an independent predictor of PCa, the MALAT-1 score was significantly higher in men with a positive biopsy than in those with a negative biopsy. The ROC analysis showed a higher AUC for the MALAT-1 score (0.670 and 0.742) vs. the total PSA (0.545 and 0.601) and percent free PSA (0.622 and 0.627) in patients with PSA values of 4.0-10 ng/ml. According to the decision curve analysis, using a probability threshold of 25%, the MALAT-1 model would prevent 30.2%-46.5% of unnecessary biopsies in PSA 4–10 ng/ml cohorts, without missing any high-grade cancers. Our results demonstrate that urine MALAT-1 is a promising biomarker for predicting prostate cancer risk.

The emerging role of extracellular vesicles as biomarkers for urogenital cancers

The knowledge gained from comprehensive profiling projects that aim to define the complex genomic alterations present within cancers will undoubtedly improve our ability to detect and treat those diseases, but the influence of these resources on our understanding of basic cancer biology is still to be demonstrated. Extracellular vesicles have gained considerable attention in past years, both as mediators of intercellular signalling and as potential sources for the discovery of novel cancer biomarkers. In general, research on extracellular vesicles investigates either the basic mechanism of vesicle formation and cargo incorporation, or the isolation of vesicles from available body fluids for biomarker discovery. A deeper understanding of the cargo molecules present in extracellular vesicles obtained from patients with urogenital cancers, through high-throughput proteomics or genomics approaches, will aid in the identification of novel diagnostic and prognostic biomarkers, and can potentially lead to the discovery of new therapeutic targets.

Selection of aptamers for fluorescent detection of alpha-methylacyl-CoA racemase by single-bead SELEX

This paper first reports DNA aptamers and a fluorescent enzyme-linked aptamer assay (ELAA) targeting alpha-methylacyl-CoA racemase (AMACR), an emerging prostate cancer biomarker. The aptamers were in vitro selected using a new single-bead SELEX approach, which was rapid and consumed only ca. 45 ng AMACR. Before SELEX, silane chemistry was used to prepare epoxide-functionalized glass microbeads (EGBs, 500 μm in size and manipulated by tweezers) for AMACR coating. Recombinant AMACR was also prepared. During SELEX, the ligand evolution was assured by a differential real-time quantitative PCR assay. After SELEX, the aptamers were identified by the alignment analysis and 2nd structure prediction from the selected, cloned sequences. The circular dichroism (CD) analysis revealed that the aptamers formed stable B-form, stem-loop conformations. The fluorescent ELAA method confirmed the nM-level affinity and high specificity of the aptamers against AMACR. Finally, an aptamer-based fluorescent AMACR assay was demonstrated. The assay featured a wide dynamic range (from 10(-1) to 10(3) nM of AMACR), a low detection limit of 0.44 nM (19.5 ng/mL), and high AMACR specificity and is promising for clinical AMACR diagnostics.

Nucleic acid-based biomarkers in body fluids of patients with urologic malignancies

This review focuses on the promising potential of nucleic acids in body fluids such as blood and urine as diagnostic, prognostic, predictive and monitoring biomarkers in urologic malignancies. The tremendous progress in the basic knowledge of molecular processes in cancer, as shown in the companion review on nucleic acid-based biomarkers in tissue of urologic tumors, provides a strong rationale for using these molecular changes as non-invasive markers in body fluids. The changes observed in body fluids are an integrative result, reflecting both tissue changes and processes occurring in the body fluids. The availability of sensitive methods has only recently made possible detailed studies of DNA- and RNA-based markers in body fluids. In addition to these biological aspects, methodological aspects of the determination of nucleic acids in body fluids, i.e. pre-analytical, analytical and post-analytical issues, are particularly emphasized. The characteristic changes of RNA (differential mRNA and miRNA expression) and DNA (concentrations, integrity index, mutations, microsatellite and methylation alterations) in serum/plasma and urine samples of patients suffering from the essential urologic cancers of the prostate, bladder, kidney and testis are summarized and critically discussed below. To translate the promising results into clinical practice, laboratory scientists and clinicians have to collaborate to resolve the challenges of harmonized and feasible pre-analytical and analytical conditions for the selected markers and to validate these markers in well-designed and sufficiently powered multi-center studies.

Gene expression profiles in prostate cancer: identification of candidate non-invasive diagnostic markers

OBJECTIVE

To analyze gene expression profiles of prostate cancer (PCa) with the aim of determining the relevant differentially expressed genes and subsequently ascertain whether this differential expression is maintained in post-prostatic massage (PPM) urine samples.

MATERIAL AND METHODS

Forty-six tissue specimens (36 from PCa patients and 10 controls) and 158 urine PPM-urines (113 from PCa patients and 45 controls) were collected between December 2003 and May 2007. DNA microarrays were used to identify genes differentially expressed between tumour and control samples. Ten genes were technically validated in the same tissue samples by quantitative RT-PCR (RT-qPCR). Forty two selected differentially expressed genes were validated in an independent set of PPM-urines by qRT-PCR.

RESULTS

Multidimensional scaling plot according to the expression of all the microarray genes showed a clear distinction between control and tumour samples. A total of 1047 differentially expressed genes (FDR≤.1) were indentified between both groups of samples. We found a high correlation in the comparison of microarray and RT-qPCR gene expression levels (r=.928, P<.001). Thirteen genes maintained the same fold change direction when analyzed in PPM-urine samples and in four of them (HOXC6, PCA3, PDK4 and TMPRSS2-ERG), these differences were statistically significant (P<.05).

CONCLUSION

The analysis of PCa by DNA microarrays provides new putative mRNA markers for PCa diagnosis that, with caution, can be extrapolated to PPM-urines.

A Quest to Identify Prostate Cancer Circulating Biomarkers with a Bench-to-Bedside Potential

Prostate cancer (PCA) is a major health concern in current times. Ever since prostate specific antigen (PSA) was introduced in clinical practice almost three decades ago, the diagnosis and management of PCA have been revolutionized. With time, concerns arose as to the inherent shortcomings of this biomarker and alternatives were actively sought. Over the past decade new PCA biomarkers have been identified in tissue, blood, urine, and other body fluids that offer improved specificity and supplement our knowledge of disease progression. This review focuses on superiority of circulating biomarkers over tissue biomarkers due to the advantages of being more readily accessible, minimally invasive (blood) or noninvasive (urine), accessible for sampling on regular intervals, and easily utilized for follow-up after surgery or other treatment modalities. Some of the circulating biomarkers like PCA3, IL-6, and TMPRSS2-ERG are now detectable by commercially available kits while others like microRNAs (miR-21, -221, -141) and exosomes hold potential to become available as multiplexed assays. In this paper, we will review some of these potential candidate circulating biomarkers that either individually or in combination, once validated with large-scale trials, may eventually get utilized clinically for improved diagnosis, risk stratification, and treatment.

Medical technologies for the diagnosis of prostate cancer

Prostate cancer is an extremely prevalent problem, especially in our aging population. The prostate-specific antigen test has revolutionized prostate cancer screening. Significant advances have been made in the usage of prostate-specific antigen and its derivatives, biomarkers, diagnostic imaging techniques, biopsy strategy, biopsy needle design and anesthetic agents. Further improvement in prostate cancer detection hinges on the development of an imaging technique that is tumor specific and sensitive to biological aggressiveness.

A-methylacyl-CoA racemase (AMACR) and prostate-cancer risk: a meta-analysis of 4,385 participants

Background

Alpha-methylacyl-CoA racemase (AMACR) is a mitochondrial and peroxisomal enzyme that is overexpressed in prostate cancer. The aim of this study was to confirm and expand the findings that the PCa risk increased in men associated with AMACR expression across various geographic regions.

Methods

A systematic search of databases was carried out and other relevant articles were also identified. Then the meta-analyses were conducted according to the standard guidelines.

Results

A total of 22 studies with 4,385 participants were included on the basis of inclusion criteria. AMACR by IHC was significantly associated with increased diagnosis of PCa (OR = 76.08; 95% CI, 25.53–226.68; P<0.00001). Subgroup-analysis showed that findings didn’t substantially change when only Caucasians or Asians (OR = 51.23; 95% CI, 19.41–135.24; P<0.00001) were considered. Expression of AMACR by PCR in relation to PCa risk suggested that AMACR was associated with PCa (OR = 33.60; 95% CI, 4.67–241.77; P<0.00001). There was also no significant publication bias observed.

Conclusions

Our findings provide further evidences that the expression of AMACR contribute to PCa risk. AMACR protein overexpression was found in prostate cancers, low expression in any of the normal tissues or in benign prostatic tissue. AMACR is potentially an important prostate tumor marker.

Molecular diagnosis of prostate cancer: are we up to age?

Prostate cancer (PCa), a highly heterogeneous disease, is the one of the leading cause of morbidity and mortality in the developed countries. Historically used biomarkers such as prostatic acid phosphatase (PAP), serum prostate-specific antigen (PSA), and its precursor have not stood the challenge of sensitivity and specificity. At present, there is need to re-evaluate the approach to diagnose and monitor PCa. To this end, molecular markers that can accurately identify men with PCa at an early stage, and those who would benefit from early therapeutic intervention, are the need of the hour. There has been unprecedented progress in the development of new PCa biomarkers through advancements in proteomics, tissue DNA and protein/RNA microarray, identification of microRNA, isolation of circulating tumor cells, and tumor immunohistochemistry. This review will examine the current status of prostate cancer biomarkers with emphasis on emerging biomarkers by evaluating their diagnostic and prognostic potentials.

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.

Detection of α-Methylacyl-Coenzyme-A Racemase Transcripts in Blood and Urine Samples of Prostate Cancer Patients

BACKGROUND

Alpha-methylacyl-coenzyme-A racemase (AMACR) has been shown to be a highly specific marker for prostate cancer cells, even in the earliest stages of malignant progression. It is expressed at much higher levels than prostate-specific antigen (PSA) in malignant tissues, and is not expressed at appreciable levels in normal prostatic epithelium. In this study, we demonstrate the quantitative detection of AMACR transcripts in peripheral blood of prostate cancer patients using real-time RT-PCR. In addition, we have undertaken a pilot study to demonstrate the potential application of this technique for the detection of prostate tumor cells in urine samples from patients with prostate cancer.

METHODS

A real-time RT-PCR assay was developed for detection of the expression of AMACR in prostate cancer patients. Blood samples from 163 patients were tested at various stages of disease progression, with or without therapy. Blood specimens from patients with benign prostate disorders and other types of cancer were also evaluated.

RESULTS

In 28 of 58 samples from patients with known metastatic disease who were undergoing treatment, an AMACR expression signal above the cut-off value was detected, consistent with the presence of circulating tumor cells. In 39 of 88 patients with presumptive organ-confined disease, there was evidence of low levels of circulating tumor cells. Comparison of AMACR RT-PCR with known serum PSA values indicated that a combination of these parameters significantly increased the sensitivity for detection of progressive disease. In a pilot study analyzing urine samples from seven prostate cancer patients, elevated AMACR expression levels were detected in the urine sediments of four of six stage-T1 prostate cancer patients and in the one patient with stage-T2 prostate cancer.

CONCLUSION

The data presented in this study indicates that AMACR real-time RT-PCR may aid in the detection and staging of prostate cancer.

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 role of combined measurement of tissue mRNA levels of AMACR and survivin in the diagnosis and risk stratification of patients with suspected prostate cancer

AIM

To determine whether the measurement of tissue mRNA levels of AMACR and survivin has a role in distinguishing prostate cancer (PCa) from benign lesions and high risk from low-risk PCa in men with suspected PCa.

METHODS

TRUS prostate biopsies from 170 patients with suspected PCa were used to measure the mRNA levels of AMACR and survivin using semi-quantitative RT-PCR technique. The diagnosis, staging and risk stratification of PCa was based on established clinical criteria. The ability of tissue mRNA levels to distinguish benign from malignant prostate and high- and low-risk PCa was assessed. The diagnostic value for the two genes was evaluated by calculating their individual and combined sensitivity and specificity, which were compared with that of PSA.

RESULTS

Histological examination showed 90/170 (53%) of patients had benign prostate pathology, while 80/170 (47%) had PCa. Tissue mRNA levels of both AMACR and survivin were able to distinguish benign from PCa biopsies (p<0.0001) and also high-risk from low-risk PCa cases (p<0.02, p<0.05, respectively). Compared with serum PSA levels, the combined use of tissue mRNA levels of AMACR and survivin yielded a higher detection specificity (84 vs. 22%).

CONCLUSION

Based on AMACR and survivin combined sensitivity and specificity, these mRNA markers can be used as an adjunct to distinguish patients with and without PCa and in men with PCa may help to identify those with low- or high-risk PCa.

α-Methylacyl-CoA racemase spliced variants and their expression in normal and malignant prostate tissues

OBJECTIVES

To evaluate the possibility of using α-methylacyl-CoA racemase (AMACR) variants to improve the specificity of prostate cancer (CaP) detection. AMACR has been used as a diagnostic biomarker for CaP and is now a standard biomarker for needle biopsy specimens with ambiguous lesions.

METHODS

We used in silico analysis and molecular cloning to discover new AMACR variants and quantitative reverse transcription-polymerase chain reaction (RT-PCR) to measure the transcript levels of AMACR and its variants in 4 prostate cell lines and in 23 pairs of CaP and adjacent normal tissue.

RESULTS

We found 4 novel variants, IAs, IBL, IBLd, and IBLi. Transcript levels of most AMACR variants were significantly upregulated in CaP compared with its adjacent normal counterparts. A variants, the functional variants based on bioinformatic analysis, showed levels of transcript expression in CaP in this order: IA≫IAd=IIA≫IIAs>IAs. In contrast, the expression of the B variants, which appear to be nonfunctional due to the absence of exon 3, was lower than that of the A variants. IB was the most abundant form of B variant; and expression of IIB was negligible. More important, the difference between levels of variant IA, IAd, IIA, IIAs, IB, and IBLi in CaP and normal tissue was significantly higher than the difference in levels of total AMACR.

CONCLUSIONS

Our data suggest that AMACR variants have better power than total AMACR in discriminating between CaP and adjacent normal tissue. These findings may be useful for the development of future diagnostic assays.

Cancer biomarker discovery: the entropic hallmark

Background

It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods.

Methodology/Principal Findings

Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer.

Conclusions/Significance

We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-througput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases.

Markers for detection of prostate cancer

Early detection of prostate cancer is problematic, not just because of uncertainly whether a diagnosis will benefit an individual patient, but also as a result of the imprecise and invasive nature of establishing a diagnosis by biopsy. Despite its low sensitivity and specificity for identifying patients harbouring prostate cancer, serum prostate specific antigen (PSA) has become established as the most reliable and widely-used diagnostic marker for this condition. In its wake, many other markers have been described and evaluated. This review focuses on the supporting evidence for the most prominent of these for detection and also for predicting outcome in prostate cancer.

Biomarkers for prostate cancer detection

Since its approval by the US FDA in 1986, prostate-specific antigen (PSA) has been employed to monitor men with a diagnosis of prostate cancer. In 1994, PSA was approved for use in prostate cancer screening and has been employed worldwide. However, due to the limited specificity of PSA for the disease, novel biomarkers are needed for detecting prostate cancer and for determining which cancers need to be treated. This review will discuss the development of new biomarkers for prostate cancer detection and disease prognostication, focusing on recent progress and particular topical issues related to the development and validation of these new markers.

Urine biomarkers in prostate cancer

The deficiencies of serum PSA as a prostate-cancer-specific diagnostic test are well recognized. Thus, the development of novel biomarkers for prostate cancer detection remains an important and exciting challenge. Noninvasive urine-based tests are particularly attractive candidates for large-scale screening protocols, and biomarker discovery programs using urine samples have emerged for detecting and predicting aggressiveness of prostate cancer. Some new biomarkers already outperform serum PSA in the diagnosis of this disease. Currently, the PCA3 (prostate cancer antigen 3) urine test is probably the best adjunct to serum PSA for predicting biopsy outcome, and has proven its clinical relevance by surpassing the predictive abilities of traditional serum biomarkers. New research methods are also emerging, and high-throughput technologies will facilitate high-dimensional biomarker discovery. Future approaches will probably integrate proteomic, transcriptomic and multiplex approaches to detect novel biomarkers, and aim to identify combinations of multiple biomarkers to optimize the detection of prostate cancer. In addition, an unmet need remains for markers that differentiate indolent from aggressive cancers, to better inform treatment decisions.

A duplex quantitative polymerase chain reaction assay based on quantification of alpha-methylacyl-CoA racemase transcripts and prostate cancer antigen 3 in urine sediments improved diagnostic accuracy for prostate cancer

PURPOSE

Most men with increased serum prostate specific antigen and negative biopsy require repeat biopsy because of the lack of a sensitive and specific prostate cancer detection test. In this study we evaluated the diagnostic potential of a duplex assay for prostate cancer by quantifying transcript levels of alpha-methylacyl-CoA racemase and prostate cancer antigen 3 in urine sediments following prostatic massage.

MATERIALS AND METHODS

Urine sediments from 92 patients, 43 with and 49 without prostate cancer, were collected after digital rectal examination. Transcript levels of AMACR, PCA3 and PSA in total RNA isolated from these samples were determined by absolute quantitative real-time polymerase chain reaction. AMACR and PCA3 scores were obtained by normalizing the transcript level to that of prostate specific antigen for each sample and multiplying by 100.

RESULTS

AMACR (p = 0.006) and PCA3 (p = 0.014) scores, but not serum prostate specific antigen (p = 0.306), distinguished specimens from patients with prostate cancer from specimens from patients without prostate cancer, and ROC analysis established the diagnostic cutoff scores for the AMACR and PCA3 tests at 10.7 and 19.9, respectively. As determined from these cutoff scores the AMACR test had 70% (95% CI 56-83) sensitivity and 71% (95% CI 59-84) specificity, whereas the PCA3 test had 72% (95% CI 59-85) sensitivity and 59% (95% CI 45-73) specificity for prostate cancer detection. The combined use of AMACR and PCA3 scores in a dual marker test increased sensitivity to 81% (95% CI 70-93) and specificity to 84% (95% CI 73-94).

CONCLUSIONS

Urinary AMACR and PCA3 tests were superior to a serum prostate specific antigen test for detecting prostate cancer. Their combined use in a dual marker test further improved sensitivity and accuracy, and could serve as a surveillance test after repeat negative prostate biopsies.

Simultaneously detection of genomic and expression alterations in prostate cancer using cDNA microarray

BACKGROUND

Prostate cancer is a common disease among men but the knowledge of the prostate carcinogenesis is still limited.

METHODS

cDNA microarray-based comparative genomic hybridization (CGH) and expression profiling were performed to screen the genomic and the expression changes in prostate cancer respectively. The two data were integrated to study the influence of genomic aberrations on gene expression and seek for the genes with their expression affected by the genomic aberrations. Real-time PCR was performed to evaluate the array data.

RESULTS

Array-based CGH detected gains at 2q, 3p/q, 5q, 6q, 8q, 9p, 10p/q, 11q, 12p, 14q, and 19p/q and losses at 1p, 2p, 4q, 6p/q, 7p, 11p/q, 12q, 17p/q, 19p/q, and Xp/q in more than 20% prostate tumors and narrowed these aberrations. For example, the gain of 8q was mapped to five minimal regions. Novel aberrations were also identified, such as loss at Xq21.33-q22.2. Expression profiling discovered the significant biological processes involved in the prostate carcinogenesis, such as exogenous antigen presentation via MHC class II and protein ubiquitination. Integration analysis revealed a weak positive correlation between genomic copy number and gene expression level. Fifty-three genes showed their expression directly affected by the genomic aberrations possibly, including more than one member of Ras superfamily and major histocompatibility complex (MHC). These genes are involved in multiple biological processes.

CONCLUSIONS

Integration of the CGH and expression data provided more information than separate analysis. Although the direct influence of genomic aberrations on gene expression seems weak, the influence can be extended by indirect regulation through a few directly affected genes. Because the influence can be persistent, the genes directly affected by the genomic aberrations may play key roles in the prostate carcinogenesis and are worth further analysis.

Heterogeneous expression of alpha-methylacyl-CoA racemase in prostatic cancer correlates with Gleason score

AIMS

Alpha-methylacyl-CoA racemase (AMACR) is a sensitive and specific immunohistochemical marker of prostatic malignancy, staining 80-100% of prostatic cancers with absent staining in benign glands. However, positive staining in benign conditions as well as low rates of AMACR reactivity in prostatic cancer variants have been described. Preliminary use of AMACR immunohistochemistry in our institution has suggested lower specificity and sensitivity for prostatic cancer than initially proposed. The aim of this study was to establish true rates of AMACR reactivity in prostatic cancer and benign prostatic hyperplasia (BPH).

METHODS AND RESULTS

AMACR immunohistochemistry was performed on sections from 57 prostatic cancers and 44 BPH resections. Ninety-one percent of cancers were AMACR+, with diffuse (> 75%) tumour staining in 53% of cases. Thirty-eight percent of tumours showed heterogeneous expression (1-75% tumour staining). This was significantly correlated with increased Gleason score. High-grade prostatic intraepithelial neoplasia (PIN) was AMACR+ in 87% of cancers. Eleven percent of BPH showed moderate or strong staining in benign glands, focally mimicking the malignant staining pattern.

CONCLUSIONS

This study confirms heterogeneous AMACR expression in prostatic cancer and shows a correlation with Gleason score. Positive staining in BPH is also documented, thus emphasizing the importance of interpreting AMACR immunohistochemistry in the context of other findings in a diagnostic setting.

Method for Quantification of a Prostate Cancer Biomarker in Urine without Sample Preparation

We describe a macrocantilever-based method for detecting a prostate cancer biomarker (alpha-methylacyl-CoA racemase; AMACR) directly in patient urine without a sample preparation step and without the use of labeled reagents. Clean catch voided urine specimens were prospectively collected from five confirmed prostate cancer patients 3 weeks postbiopsy. The presence of AMACR was measured in a blinded manner by exposing 3 mL of urine to the anti-AMACR-immobilized piezoelectric-excited millimeter-sized (PEMC) sensor. The resonance frequency of PEMC decreases as AMACR from sample binds to the antibody on the sensor. The resonance frequency changes for the five patients tested were 4,314 +/- 35 (n = 2), 269 +/- 17 (n = 2), 977 +/- 64 (n = 3), 600 +/- 31 (n = 2), and 801 +/- 81 (n = 2) Hz, respectively. Positive detection was observed within approximately 15 min. The responses to positive, negative, and buffer controls were -9 +/- 13, -34 +/- 18, and -6 +/- 18 Hz, respectively. Positive verification of AMACR attachment was confirmed by low-pH buffer release. The sensor response was quantitatively related to AMACR concentration in control urine, and the relationship was used in developing an in situ calibration method for quantifying AMACR in patient urine. Estimated concentrations of 42, 2, and 3 fg/mL AMACR were calculated for the three patients' urine, while absence of AMACR was confirmed in control urine (n = 13). Because of simplicity of measurement combined with high sensitivity and specificity, the method may be a useful adjunct in a point-of-care setting to identify men at increased risk for prostate cancer.

Urinary markers for prostate cancer

Prostate cancer is the commonest solid-organ malignancy to affect men in Europe and the USA; it is estimated that one in six men will develop this cancer in their lifetime. Current screening relies on a digital rectal examination with a serum prostate-specific antigen test. Novel urinary diagnostic tests are potentially interesting screening tools for this disease. We examined published reports assessing the use of urinary markers for the diagnosis of prostate cancer. Using a PubMed-based search we identified studies of urinary markers for prostate cancer published from 1985 to February 2006 using the search terms 'urine', 'marker' and 'prostate cancer'. Studies to date have used small cohorts and relied on prostatic biopsies to provide histology. The sensitivity and specificity of markers are wide ranging but with only a few studies published on each putative marker it is difficult to assess their potential impact. Using urinary biomarkers for prostate cancer is a relatively novel diagnostic approach; they are appealing as a screening test because they are not invasive. Further work is needed to identify and validate 'signature markers' indicative of prostatic malignancy. The newer proteomic platforms are promising biomarker discovery tools that might uncover the next generation of urinary biomarkers.

Molecular markers of prostate cancer

Although prostate-specific antigen (PSA) has evolved as a very useful tool for detection of prostate cancer, there remains an urgent need for more accurate biomarkers to diagnose prostate cancer and predict cancer-related outcomes. Recent advances in the study of proteomics and high throughput techniques have led to the discovery of many potential biomarkers for prostate cancer. This article briefly reviews the current status of PSA testing and discusses several candidate protein biomarkers for prostate cancer, as well as highlighting some recent proteomic discoveries with the potential to supplement or even replace PSA for the diagnosis and prognosis of prostate cancer.

Kinetic fluorescence reverse transcriptase-polymerase chain reaction for alpha-methylacyl CoA racemase distinguishes prostate cancer from benign lesions

BACKGROUND

High-throughput gene expression profiling has recently shown that the mRNA for alpha-methylacyl CoA racemase (AMACR or P504S) is overexpressed in prostate carcinomas (PCa). Several immunohistochemical studies have reported the usefulness of anti-AMACR/P504S for detecting prostate cancer over the full range of prostate specimens encountered in surgical pathology. We tested real-time reverse transcriptase-polymerase chain reaction (RT-PCR) for specific and sensitive detection of AMACR transcripts as a supplementary measure for discriminating between malignant and benign lesions in prostatic tissues.

METHODS

Total RNA was isolated from snap-frozen chips in 55 cases of benign prostatic hyperplasia (BPH) and from frozen sections in 57 prostatectomy cases. The latter were analyzed by an uropathologist (J.K.) and found to contain at least 50% malignant epithelia. Relative quantification of AMACR transcripts was performed by RT-PCR using hybridization probes for detection and PBGD for normalization.

RESULTS

Normalized AMACR transcript levels showed an average 3.75-fold increase in 57 prostate carcinomas cases when compared to 55 cases of BPH (p<0.0001). A 85.6% specificity and 64.9% sensitivity can be achieved if the cutoff is set at 12.95. AMACR expression levels among PCa cases were not statistically associated with the tumor and lymph node stage, the grading, the surgical margins, the Gleason score or progression.

DISCUSSION

The present study demonstrates the usefulness of quantitative AMACR-mRNA transcript detection in prostatic tissues as an alternative to immunological staining techniques. Since the latter clearly predominate in the laboratory routine, PCR-based detection of AMACR has the potential to gain widespread acceptance as a suitable future tool for monitoring prostate cancer patients.

Molecular markers in the diagnosis of prostate cancer

The genetic alterations leading to prostate cancer are gradually being discovered. A wide variety of genes have been associated with prostate cancer development as well as tumor progression. Knowledge of gene polymorphisms associated with disease aid in the understanding of important pathways involved in this process and may result in the near future in clinical applications. Urinary molecular markers will soon be available to aid in the decision of repeat prostate biopsies. Recent findings suggest the importance of androgen signaling in disease development and progression. The further understanding of interaction of inflammation, diet, and genetic predisposition will improve risk stratification in the near future.

Can p503s, p504s and p510s gene expression in peripheral-blood be useful as a marker of prostatic cancer?

BACKGROUND

The aim of the study was to investigate whether p503S, p504S and p510S gene expression in peripheral-blood be useful as a diagnostic or prognostic marker of prostatic cancer.

METHODS

Circulating cells were identified by reverse transcription-polymerase chain reaction (RT-PCR) to detect p503S, p504S and p510S mRNA in peripheral blood (PB) from 11 patients with treated prostatic carcinoma (CaP), 11 with newly-diagnosed untreated CaP and 20 with benign prostatic hyperplasia (BPH) (controls).

RESULTS

RT-PCR amplified P503S in 7 of 11 untreated and 2 of 11 treated patients with CaP and 5 of 20 with BPH; p504S in 7 of 11 untreated and in 9 of 11 treated patients with CaP and 11 of 20 with BPH; whereas it amplified p510S in all subjects with CaP and in 15 of 20 with BPH.

CONCLUSION

These findings suggest that the investigated genes are poorly specific and probably of little use as diagnostic or prognostic prostatic markers in peripheral blood for monitoring disease progression and recurrence.