Efforts to resolve the contradictions in early diagnosis of prostate cancer: a comparison of different algorithms of sarcosine in urine

Metabolomic profile and its association with the diagnosis of prostate cancer: a systematic review

OBJECTIVE

To determine the association of a metabolomic profile with the diagnosis of localized prostate cancer.

METHODS

We conducted a search strategy in MEDLINE (OVID), EMBASE, LILACS, and the Cochrane Central Register of Controlled Trials (CENTRAL) from 2008 to the present. We included Clinical trials and analytical and descriptive observational studies that reported metabolite results and metabolite profiles in serum, tissue, urine, and seminal fluid. All studies used metabolomic techniques such as MS and MRI to identify patients with localized prostate cancer compared with patients without cancer. We used QUADAS 2 to assess the risk of bias.

RESULTS

We found 1248 studies with the search strategy. Finally, 14 case-control studies were included. Serum was the primary sample to identify the metabolites. Low concern was found regarding applying the index test and the reference standard in assessing the risk of bias. The metabolites of interest associated with establishing a metabolomic profile in the diagnosis of localized prostate cancer were amino acids, lipids, androgens, estrogens, nucleotides, and histidine metabolism.

CONCLUSION

Disturbances in the metabolism of fatty acids, amino acids, nucleotides, and steroid hormones were identified, suggesting the presence of localized prostate cancer. Importantly, serum samples showed an increase in amino acid levels. Glutamate and aspartic acid stand out among the amino acids that register high levels. In addition, glycine and serine were consistently decreased metabolites in the three kinds of biological samples analyzed.

The Integration of Metabolomics with Other Omics: Insights into Understanding Prostate Cancer

Our understanding of prostate cancer (PCa) has shifted from solely caused by a few genetic aberrations to a combination of complex biochemical dysregulations with the prostate metabolome at its core. The role of metabolomics in analyzing the pathophysiology of PCa is indispensable. However, to fully elucidate real-time complex dysregulation in prostate cells, an integrated approach based on metabolomics and other omics is warranted. Individually, genomics, transcriptomics, and proteomics are robust, but they are not enough to achieve a holistic view of PCa tumorigenesis. This review is the first of its kind to focus solely on the integration of metabolomics with multi-omic platforms in PCa research, including a detailed emphasis on the metabolomic profile of PCa. The authors intend to provide researchers in the field with a comprehensive knowledge base in PCa metabolomics and offer perspectives on overcoming limitations of the tool to guide future point-of-care applications.

Noninvasive urine metabolomics of prostate cancer and its therapeutic approaches: a current scenario and future perspective

INTRODUCTION

The sensitive, specific, fast, robust and noninvasive biomarkers for the evaluation of prostate cancer (PC) remain elusive in medical research. However, efforts are in full sway to investigate and resolve these puzzles for clinical practice. Advances in modern analytical techniques, sample processing, and the emergence of multiple omics approaches have created a great hope for the development of better detection modalities for PC. The objective of the present review is to provide a concise overview of the PC metabolomics-based potential discriminating molecules in urine samples using nuclear magnetic resonance spectroscopy and mass spectrometry.

AREA COVERED

A literature search was executed to find the studies reporting the noninvasive urine-based biomarkers for the diagnosis and prognosis of underlying disease. Most studies have extensivelyreported PC discriminating molecules with their respective controls. Additionally, pathophysiology and the treatment paradigm of PC are summarized and related to the insights underpinning the therapeutic intervention of PC.

EXPERT OPINION

With multi-centric, global, comprehensive omics approaches via either a non- or least-invasive bio-matrix may open new avenues of research for PC biomarker discovery, backed by a molecular mechanistic outline.

Beyond liquid biopsy: Toward non-invasive assays for distanced cancer diagnostics in pandemics

Liquid biopsy technologies have seen a significant improvement in the last decade, offering the possibility of reliable analysis and diagnosis from several biological fluids. The use of these technologies can overcome the limits of standard clinical methods, related to invasiveness and poor patient compliance. Along with this there are now mature examples of lab-on-chips (LOC) which are available and could be an emerging and breakthrough technology for the present and near-future clinical demands that provide sample treatment, reagent addition and analysis in a sample-in/answer-out approach. The possibility of combining non-invasive liquid biopsy and LOC technologies could greatly assist in the current need for minimizing exposure and transmission risks. The recent and ongoing pandemic outbreak of SARS-CoV-2, indeed, has heavily influenced all aspects of life worldwide. Ordinary tasks have been forced to switch from “in presence” to “distanced”, limiting the possibilities for a large number of activities in all fields of life outside of the home. Unfortunately, one of the settings in which physical distancing has assumed noteworthy consequences is the screening, diagnosis and follow-up of diseases.

In this review, we analyse biological fluids that are easily collected without the intervention of specialized personnel and the possibility that they may be used -or not-for innovative diagnostic assays. We consider their advantages and limitations, mainly due to stability and storage and their integration into Point-of-Care diagnostics, demonstrating that technologies in some cases are mature enough to meet current clinical needs.

Metabolic Rewiring and the Characterization of Oncometabolites

Simple Summary

Oncometabolites are produced by cancer cells and assist the cancer to proliferate and progress. Oncometabolites occur as a result of mutated enzymes in the tumor tissue or due to hypoxia. These processes result in either the abnormal buildup of a normal metabolite or the accumulation of an unusual metabolite. Definition of the metabolic changes that occur due to these processes has been accomplished using metabolomics, which mainly uses mass spectrometry platforms to define the content of small metabolites that occur in cells, tissues, organs and organisms. The four classical oncometabolites are fumarate, succinate, (2R)-hydroxyglutarate and (2S)-hydroxyglutarate, which operate by inhibiting 2-oxoglutarate-dependent enzyme reactions that principally regulate gene expression and response to hypoxia. Metabolomics has also revealed several putative oncometabolites that include lactate, kynurenine, methylglyoxal, sarcosine, glycine, hypotaurine and (2R,3S)-dihydroxybutanoate. Metabolomics will continue to be critical for understanding the metabolic rewiring involving oncometabolite production that underpins many cancer phenotypes.

Abstract

The study of low-molecular-weight metabolites that exist in cells and organisms is known as metabolomics and is often conducted using mass spectrometry laboratory platforms. Definition of oncometabolites in the context of the metabolic phenotype of cancer cells has been accomplished through metabolomics. Oncometabolites result from mutations in cancer cell genes or from hypoxia-driven enzyme promiscuity. As a result, normal metabolites accumulate in cancer cells to unusually high concentrations or, alternatively, unusual metabolites are produced. The typical oncometabolites fumarate, succinate, (2R)-hydroxyglutarate and (2S)-hydroxyglutarate inhibit 2-oxoglutarate-dependent dioxygenases, such as histone demethylases and HIF prolyl-4-hydroxylases, together with DNA cytosine demethylases. As a result of the cancer cell acquiring this new metabolic phenotype, major changes in gene transcription occur and the modification of the epigenetic landscape of the cell promotes proliferation and progression of cancers. Stabilization of HIF1α through inhibition of HIF prolyl-4-hydroxylases by oncometabolites such as fumarate and succinate leads to a pseudohypoxic state that promotes inflammation, angiogenesis and metastasis. Metabolomics has additionally been employed to define the metabolic phenotype of cancer cells and patient biofluids in the search for cancer biomarkers. These efforts have led to the uncovering of the putative oncometabolites sarcosine, glycine, lactate, kynurenine, methylglyoxal, hypotaurine and (2R,3S)-dihydroxybutanoate, for which further research is required.

A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer

OBJECTIVE

Significant efforts are currently being made to identify novel biomarkers for the diagnosis and risk stratification of prostate cancer (PCa). Metabolomics can be a very useful approach in biomarker discovery because metabolites are an important read-out of the disease when characterized in biological samples. We aimed to determine a metabolomic signature which can accurately distinguish men with clinically significant PCa from those affected by benign prostatic hyperplasia (BPH).

METHODS

We first performed untargeted metabolomics using ultrahigh-performance liquid chromatography tandem mass spectrometry on expressed prostatic secretion urine (EPS-urine) from 25 patients affected by BPH and 25 men with clinically significant PCa (defined as Gleason score ≥ 3 + 4). Diagnosis was histologically confirmed after surgical treatment. The EPS-urine metabolomic approach was then applied to a larger, prospective cohort of 92 consecutive patients undergoing multiparametric magnetic resonance imaging for clinical suspicion of PCa prior to biopsy.

RESULTS

We established a novel metabolomic signature capable of accurately distinguishing PCa from benign tissue. A metabolomic signature was associated with clinically significant PCa in all subgroups of the Prostate Imaging Reporting and Data System (PI-RADS) classification (100% and 89.13% of accuracy when the PI-RADS was in range of 1-2 and 4-5, respectively, and 87.50% in the more critical cases when the PI-RADS was 3).

CONCLUSIONS

A combination of metabolites and clinical variables can effectively help in identifying PCa patients that might be overlooked by current imaging technologies. Metabolites from EPS-urine should help in defining the diagnostic pathway of PCa, thus improving PCa detection and decreasing the number of unnecessary prostate biopsies.

Urinary Biomarkers in Tumors: An Overview

Recent reports suggest that urine is a useful noninvasive tool for the identification of urogenital tumors, including bladder, prostate, kidney, and other nonurological cancers. As a liquid biopsy, urine represents an important source for the improvement of new promising biomarkers, a suitable tool to identify indolent cancer and avoid overtreatment. Urine is enriched with DNAs, RNAs, proteins, circulating tumor cells, exosomes, and other small molecules which can be detected with several diagnostic methodologies.We provide an overview of the ongoing state of urinary biomarkers underlying both their potential utilities to improve cancer prognosis, diagnosis, and therapeutic strategy and their limitations.

Metal-coded hydrogel magnetic molecularly imprinted polymer for preconcentration and cleanup of sarcosine: Determination in urine; coupled to on-column capillary electrophoresis

In this study, sarcosine metal-coded hydrogel magnetic molecularly imprinted polymer (Hydro-MeC-MMIP) has been fabricated and coupled to on-column derivatization capillary electrophoresis (CE). As a metal-coding approach, sarcosine-Cu²⁺-ligand (Sar-Cu²⁺-L) chelate complex was introduced as a template to overcome the problems associated with the fabrication of MMIP for a small molecule having limited functional groups such as sarcosine. To our best knowledge, it is the first time that methacrylamide (MA) coated Fe₃O₄ (Fe₃O₄@MA) with abounded reactive double-bound on the surface has been used as a magnetic core in the one-pot synthesis of MMIPs. As prepared, Hydro-MeC-MMIP was characterized by different microscopic, spectroscopic, and thermal gravimetric methods. Hydro-MeC-MMIP was used to extract and preconcentrate sarcosine in the urine sample with no treatment and dilution. Sarcosine was quantified by on-column derivatization capillary electrophoresis equipped with a photodiode array detector. A mixture of thirteen amino acids was separated with a total run time of 12 min. Three structural analogs, including alanine, sarcosine, and glycine, were significantly resolved. Under optimal experimental conditions, the method's detection and quantification limits were 9.93 and 33.10 ng mL^-1, respectively. The linear range of 50-2000 ng mL^-1 and 96% recovery, along with the relative standard deviation of 6.07% (n = 6) for the target amino acid, were obtained. This method provides a simple, low-cost, fast, and efficient tool for extracting and quantifying sarcosine in the urine. The present method can address inconsistency in evaluating sarcosine as a candidate biomarker for prostate cancer with a simple CE/UV; no need for a sophisticated detection system such as a mass spectrometer.

Precision Medicine Approach in Prostate Cancer

Prostate cancer is the most prevalent type of cancer and the second cause of death in men worldwide. Various diagnostic and treatment procedures are available for this type of malignancy, but High-grade or locally advanced prostate cancers showed the potential to develop to lethal phase that can be causing dead. Therefore, new approaches are needed to prolong patients' survival and to improve their quality of life. Precision medicine is a novel emerging field that plays an essential role in identifying new sub-classifications of diseases and in providing guidance in treatment that is based on individual multi-omics data. Multi-omics approaches include the use of genomics, transcriptomics, proteomics, metabolomics, epigenomics and phenomics data to unravel the complexity of a disease-associated biological network, to predict prognostic biomarkers, and to identify new targeted drugs for individual cancer patients. We review the impact of multi-omics data in the framework of systems biology in the era of precision medicine, emphasising the combination of molecular imaging modalities with highthroughput techniques and the new treatments that target metabolic pathways involved in prostate cancer.

Programming bulk enzyme heterojunctions for biosensor development with tetrahedral DNA framework

Protein-protein interactions are spatially regulated in living cells to realize high reaction efficiency, as seen in naturally existing electron-transfer chains. Nevertheless, arrangement of chemical/biochemical components at the artificial device interfaces does not possess the same level of control. Here we report a tetrahedral DNA framework-enabled bulk enzyme heterojunction (BEH) strategy to program the multi-enzyme catalytic cascade at the interface of electrochemical biosensors. The construction of interpenetrating network of BEH at the millimeter-scale electrode interface brings enzyme pairs within the critical coupling length (CCL) of ~10 nm, which in turn greatly improve the overall catalytic cascade efficiency by ~10-fold. We demonstrate the BEH generality with a range of enzyme pairs for electrochemically detecting clinically relevant molecular targets. As a proof of concept, a BEH-based sarcosine sensor enables single-step detection of the metabolic biomarker of sarcosine with ultrasensitivity, which hold the potential for precision diagnosis of early-stage prostate cancer.

Genetic and molecular determinants of prostate cancer among Iranian patients: An update

Prostate cancer (PCa) is one of the most common age-related cancers among men. Various environmental and genetic factors are involved in the development and progression of PCa. In most cases, the primary symptoms of disease are not severe. Therefore, it is common for patients to be referred with severe clinical manifestations at advanced stages of disease. Since this malignancy is age related and Iran will face a significant increase in the number of seniors, it is expected that the prevalence of PCa among Iranian men will rise. PCa progression has been observed to be associated with genetic and ethnic factors. It may therefore be clinically useful to determine a panel of genetic markers, in addition to routine diagnostic methods, to detect tumors in the early stages. In the present review, we have summarized the reported genetic markers in PCa Iranian patients to pave the way for the determination of an ethnic specific genetic marker panel for the early detection of PCa. To understand the genetic and molecular biology of PCa among Iranians, we have categorized these genetic markers based on their cellular functions.

Reliable identification of prostate cancer using mass spectrometry metabolomic imaging in needle core biopsies

Metabolomic profiling can aid in understanding crucial biological processes in cancer development and progression and can also yield diagnostic biomarkers. Desorption electrospray ionization coupled to mass spectrometry imaging (DESI-MSI) has been proposed as a potential adjunct to diagnostic surgical pathology, particularly for prostate cancer. However, due to low resolution sampling, small numbers of mass spectra, and little validation, published studies have yet to test whether this method is sufficiently robust to merit clinical translation. We used over 900 spatially resolved DESI-MSI spectra to establish an accurate, high-resolution metabolic profile of prostate cancer. We identified 25 differentially abundant metabolites, with cancer tissue showing increased fatty acids (FAs) and phospholipids, along with utilization of the Krebs cycle, and benign tissue showing increased levels of lyso-phosphatidylethanolamine (PE). Additionally, we identified, for the first time, two lyso-PEs with abundance that decreased with cancer grade and two phosphatidylcholines (PChs) with increased abundance with increasing cancer grade. Importantly, we developed and internally validated a multivariate metabolomic classifier for prostate cancer using 534 spatial regions of interest (ROIs) in the training cohort and 430 ROIs in the test cohort. With excellent statistical power, the training cohort achieved a balanced accuracy of 97% and validation on testing data set demonstrated 85% balanced accuracy. Given the validated accuracy of this classifier and the correlation of differentially abundant metabolites with established patterns of prostate cancer cell metabolism, we conclude that DESI-MSI is an effective tool for characterizing prostate cancer metabolism with the potential for clinical translation.

NMR-Based Metabolomic Profiling of Urine: Evaluation for Application in Prostate Cancer Detection

Detection of prostate cancer (PCa) and distinguishing indolent versus aggressive forms of the disease is a critical clinical challenge. The current clinical test is circulating prostate-specific antigen levels, which faces particular challenges in cancer diagnosis in the range of 4 to 10 ng/mL. Thus, a concerted effort toward building a noninvasive biomarker panel has developed. In this report, the hypothesis that nuclear magnetic resonance (NMR)-derived metabolomic profiles measured in the urine of biopsy-negative versus biopsy-positive individuals would nominate a selection of potential biomarker signals was investigated. 1H NMR spectra of urine samples from 317 individuals (111 biopsy-negative, 206 biopsy-positive) were analyzed. A double cross-validation partial least squares-discriminant analysis modeling technique was utilized to nominate signals capable of distinguishing the two classes. It was observed that after variable selection protocols were applied, a subset of 29 variables produced an area under the curve (AUC) value of 0.94 after logistic regression analysis, whereas a “master list” of 18 variables produced a receiver operating characteristic ROC) AUC of 0.80. As proof of principle, this study demonstrates the utility of NMR-based metabolomic profiling of urine biospecimens in the nomination of PCa-specific biomarker signals and suggests that further investigation is certainly warranted.

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.

Metabolomic and BH3 profiling of esophageal cancers: novel assessment methods for precision therapy

BACKGROUND

Esophageal cancers accounted for nearly 16,000 deaths in 2016. The number of patients with esophageal cancers increases every year. Neoadjuvant chemoradiotherapy (nCRT) prior to esophagectomy is a standard treatment for esophageal cancers. The patients who have no residual tumor (pathological complete response (pCR)) at surgery are the most likely to experience long term survival. Accurately determining which patients will have a pCR will improve prognostic information for patients and families, confirm lack of response to nCRT, or avoid surgery if no residual tumor is present. Imaging, endoscopy, and liquid biomarkers have all failed to detect pCR without performing an esophagectomy.

METHODS

In this study, we are enrolling patients with esophageal adenocarcinoma and squamous cell carcinoma. Patients will undergo standard evaluation including CT scans, laboratory tests, endoscopy with biopsies, and evaluation by a thoracic surgeon. Tissue biopsy is required for enrollment that will be sent for BH3 profiling and metabolomics. Patients will be treated with standard nCRT followed by surgery. Patients with metastatic disease are not eligible. Surgery at the National Cancer Institute will be minimally-invasive robotic surgery. Patients will remain on study indefinitely with regular clinic visits and imaging tests.

DISCUSSION

The mitochondria are critically involved in the intrinsic pathway apoptosis. Bcl-2 homology domain 3 (BH3) profiling is a technique to measure a cell's susceptibility to apoptosis. BH3 profiling measures the relative interactions of proteins that induce or block apoptosis. The collective balance of these proteins determines whether a cell is near the threshold to undergo apoptosis. If the cell is near this threshold, then the tumor may be more likely to die when treated with nCRT. The mitochondria secrete metabolites that may be detectable as biomarkers. Metabolomics is a global assessment of all metabolite changes that has been performed for detection, monitoring, prognosis, and treatment response in cancers. Stratification of patients based on whether pCR occurs or not may elucidate metabolomic signatures that may be associated with response. We are asking whether BH3 profiling or a metabolomic signature will correlate with tumor death after nCRT for esophageal cancer.

TRIAL REGISTRATION

NCT03223662 ; Clinicaltrials.gov. July 21, 2017.

Development of sarcosine quantification in urine based on enzyme-coupled colorimetric method for prostate cancer diagnosis

An enzyme-coupled colorimetric assay for quantification of urinary sarcosine was developed. The proposed method is a specific reaction based on hydrogen peroxide (H2O2) formation via sarcosine oxidase (SOX). The liberated H2O2 reacts with Amplex Red in the presence of horseradish peroxidase (HRP) to produce the red-fluorescent oxidation product, resorufin, which can be measured spectrophotometrically (OD570). The method was performed in the 96-well microtiter plate. Reaction conditions, such as pH and reaction time were optimized. At the optimum conditions, the limit of detection (LOD) and quantification (LOQ) were found to be 0.7 and 1 µM, respectively. A good linearity was revealed with a coefficient of 0.990. The assay showed no significant interference from ascorbic acid, glucose and bilirubin. In addition, it is extremely specific for sarcosine rather than other amino acids. The determination of sarcosine in human urine displayed high accuracy and good reproducibility. This method is promising to differentiate prostate cancer patients from healthy subjects according to urinary sarcosine level. Altogether, this study provides a rapid, simple and specific tool to determine urinary sarcosine which could be useful for prostate cancer diagnosis.

The Role of Sarcosine, Uracil, and Kynurenic Acid Metabolism in Urine for Diagnosis and Progression Monitoring of Prostate Cancer

The aim of this pilot study is to evaluate sarcosine, uracil, and kynurenic acid in urine as potential biomarkers in prostate cancer detection and progression monitoring. Sarcosine, uracil, and kynurenic acid were measured in urine samples of 32 prostate cancer patients prior to radical prostatectomy, 101 patients with increased prostate-specific antigen prior to ultrasonographically-guided prostatic biopsy collected before and after prostatic massage, and 15 healthy volunteers (controls). The results were related to histopathologic data, Gleason score, and PSA (Prostate Specific Antigen). Metabolites were measured after analysis of urine samples with Ultra-High Performance Liquid Chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) instrumentation. Multivariate, nonparametric statistical tests including receiver operating characteristics analyses, one-way analysis of variance (Kruskal–Wallis test), parametric statistical analysis, and Pearson correlation, were performed to evaluate diagnostic performance. Decreased median sarcosine and kynurenic acid and increased uracil concentrations were observed for patients with prostate cancer compared to participants without malignancy. Results showed that there was no correlation between the concentration of the studied metabolites and the cancer grade (Gleason score <7 vs. ≥7) and the age of the patients. Evaluation of biomarkers by ROC (Receiving Operating Characteristics) curve analysis showed that differentiation of prostate cancer patients from participants without malignancy was not enhanced by sarcosine or uracil levels in urine. In contrast to total PSA values, kynurenic acid was found a promising biomarker for the detection of prostate cancer particularly in cases where collection of urine samples was performed after prostatic massage. Sarcosine and uracil in urine samples of patients with prostate cancer were not found as significant biomarkers for the diagnosis of prostate cancer. None of the three metabolites can be used reliably for monitoring the progress of the disease.

Prostate tumor attenuation in the nu/nu murine model due to anti-sarcosine antibodies in folate-targeted liposomes

Herein, we describe the preparation of liposomes with folate-targeting properties for the encapsulation of anti-sarcosine antibodies (antisarAbs@LIP) and sarcosine (sar@LIP). The competitive inhibitory effects of exogenously added folic acid supported the role of folate targeting in liposome internalization. We examined the effects of repeated administration on mice PC-3 xenografts. Sar@LIP treatment significantly increased tumor volume and weight compared to controls treated with empty liposomes. Moreover, antisarAbs@LIP administration exhibited a mild antitumor effect. We also identified differences in gene expression patterns post-treatment. Furthermore, Sar@LIP treatment resulted in decreased amounts of tumor zinc ions and total metallothioneins. Examination of the spatial distribution across the tumor sections revealed a sarcosine-related decline of the MT1X isoform within the marginal regions but an elevation after antisarAbs@LIP administration. Our exploratory results demonstrate the importance of sarcosine as an oncometabolite in PCa. Moreover, we have shown that sarcosine can be a potential target for anticancer strategies in management of PCa.

Biomarkers in localized prostate cancer

Biomarkers can improve prostate cancer diagnosis and treatment. Accuracy of prostate-specific antigen (PSA) for early diagnosis of prostate cancer is not satisfactory, as it is an organ- but not cancer-specific biomarker, and it can be improved by using models that incorporate PSA along with other test results, such as prostate cancer antigen 3, the molecular forms of PSA (proPSA, benign PSA and intact PSA), as well as kallikreins. Recent reports suggest that new tools may be provided by metabolomic studies as shown by preliminary data on sarcosine. Additional molecular biomarkers have been identified by the use of genomics, proteomics and metabolomics. We review the most relevant biomarkers for early diagnosis and management of localized prostate cancer.

A case control study of sarcosine as an early prostate cancer detection biomarker

Background

Sarcosine has been investigated as a prostate cancer biomarker with mixed results concerning its predictive power. We performed a case–control evaluation of the predictive value of serum sarcosine for early detection in a population-based cohort of men undergoing prostate-specific antigen (PSA) screening.

Methods

For analysis we used 251 cancer cases and 246 age-matched non-cancer cases from the San Antonio Biomarkers Of Risk (SABOR) screening study. For cancer cases, pre-diagnostic serum was utilized for sarcosine measurement. Controls were defined as men who had been followed at least for 5 years on study with no prostate cancer diagnosis; sarcosine was measured on the initial baseline serum. HPLC-electrospray ionization mass spectrometry was used for serum sarcosine quantification. The association of sarcosine with prostate cancer was assessed using area underneath the receiver-operating characteristic curve (AUC), and logistic regression adjusting for PSA, digital rectal exam, family history, age, race, and history of a prior negative biopsy. Among cancer cases, nominal logistic regression was used for the association of sarcosine with Gleason grade.

Results

Sarcosine levels were overlapping between the prostate cancer cases (median 15.8 uM, range 6.2 to 42.5 uM) and controls (median 16.2 uM, range 6.4 to 53.6 uM). The AUC of sarcosine was not statistically different from random chance either for participants with any PSA value (52.2 %) or those with PSA values in the range of 2 to 10 ng/mL (54.3 %). Sarcosine was not predictive of Gleason score and added no independent predictive power to standard prostate cancer risk factors for detection of prostate cancer (all p-values > 0.05).

Conclusions

Serum sarcosine should not be pursued further as a marker for the early detection of prostate cancer.

Metabolomic profiling for the identification of novel diagnostic markers in prostate cancer

Metabolomic profiling offers a powerful methodology for understanding the perturbations of biochemical systems occurring during a disease process. During neoplastic transformation, prostate cells undergo metabolic reprogramming to satisfy the demands of growth and proliferation. An early event in prostate cell transformation is the loss of capacity to accumulate zinc. This change is associated with a higher energy efficiency and increased lipid biosynthesis for cellular proliferation, membrane formation and cell signaling. Moreover, recent studies have shown that sarcosine, an N-methyl derivative of glycine, was significantly increased during disease progression from normal to localized to metastatic prostate cancer. Mapping the metabolomic profiles to their respective biochemical pathways showed an upregulation of androgen-induced protein synthesis, an increased amino acid metabolism and a perturbation of nitrogen breakdown pathways, along with high total choline-containing compounds and phosphocholine levels. In this review, the role of emerging biomarkers is summarized, based on the current understanding of the prostate cancer metabolome.

Recent Advances in Metabolic Profiling And Imaging of Prostate Cancer

Cancer is a metabolic disease. Cancer cells, being highly proliferative, show significant alterations in metabolic pathways such as glycolysis, respiration, the tricarboxylic acid (TCA) cycle, oxidative phosphorylation, lipid metabolism, and amino acid metabolism. Metabolites like peptides, nucleotides, products of glycolysis, the TCA cycle, fatty acids, and steroids can be an important read out of disease when characterized in biological samples such as tissues and body fluids like urine, serum, etc. The cancer metabolome has been studied since the 1960s by analytical techniques such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Current research is focused on the identification and validation of biomarkers in the cancer metabolome that can stratify high-risk patients and distinguish between benign and advanced metastatic forms of the disease. In this review, we discuss the current state of prostate cancer metabolomics, the biomarkers that show promise in distinguishing indolent from aggressive forms of the disease, the strengths and limitations of the analytical techniques being employed, and future applications of metabolomics in diagnostic imaging and personalized medicine of prostate cancer.

The role of sarcosine metabolism in prostate cancer progression

Metabolomic profiling of prostate cancer (PCa) progression identified markedly elevated levels of sarcosine (N-methyl glycine) in metastatic PCa and modest but significant elevation of the metabolite in PCa urine. Here, we examine the role of key enzymes associated with sarcosine metabolism in PCa progression. Consistent with our earlier report, sarcosine levels were significantly elevated in PCa urine sediments compared to controls, with a modest area under the receiver operating characteristic curve of 0.71. In addition, the expression of sarcosine biosynthetic enzyme, glycine N-methyltransferase (GNMT), was elevated in PCa tissues, while sarcosine dehydrogenase (SARDH) and pipecolic acid oxidase (PIPOX), which metabolize sarcosine, were reduced in prostate tumors. Consistent with this, GNMT promoted the oncogenic potential of prostate cells by facilitating sarcosine production, while SARDH and PIPOX reduced the oncogenic potential of prostate cells by metabolizing sarcosine. Accordingly, addition of sarcosine, but not glycine or alanine, induced invasion and intravasation in an in vivo PCa model. In contrast, GNMT knockdown or SARDH overexpression in PCa xenografts inhibited tumor growth. Taken together, these studies substantiate the role of sarcosine in PCa progression.

Serum sarcosine is a risk factor for progression and survival in patients with metastatic castration-resistant prostate cancer

AIM

Sarcosine has been identified as a differential metabolite that is greatly increased during progression from normal tissue to prostate cancer and metastatic disease. In this study we assessed the role of serum sarcosine in metastatic castration-resistant prostate cancer (mCRPC) patients.

PATIENTS & METHODS

Data from 52 mCRPC patients treated with docetaxel-based chemotherapy were retrospectively analyzed. Receiver operating characteristic curves, and Kaplan-Meier and Cox multivariate analyses were performed.

RESULTS

Median sarcosine values were significantly higher in mCRPC versus non-mCRPC patients (0.81 vs 0.52 nmol/µl; p < 0.0001). A significant correlation resulted between serum sarcosine levels and the duration of hormone sensitivity (Spearman's correlation coefficient: -0.51; p = 0.001). At multivariate analysis sarcosine was an independent prognostic factor of outcome in terms of overall and progression-free survival.

CONCLUSION

Serum sarcosine values were significantly increased in patients with metastatic disease. Moreover, this biomarker is a risk factor for progression and survival in chemotherapy-treated mCRPC patients.

Metabolomic signatures of aggressive prostate cancer

BACKGROUND

Current diagnostic techniques have increased the detection of prostate cancer; however, these tools inadequately stratify patients to minimize mortality. Recent studies have identified a biochemical signature of prostate cancer metastasis, including increased sarcosine abundance. This study examined the association of tissue metabolites with other clinically significant findings.

METHODS

A state of the art metabolomics platform analyzed prostatectomy tissues (331 prostate tumor, 178 cancer-free prostate tissues) from two independent sites. Biochemicals were analyzed by gas chromatography-mass spectrometry and ultrahigh performance liquid chromatography-tandem mass spectrometry. Statistical analyses identified metabolites associated with cancer aggressiveness: Gleason score, extracapsular extension, and seminal vesicle and lymph node involvement.

RESULTS

Prostate tumors had significantly altered metabolite profiles compared to cancer-free prostate tissues, including biochemicals associated with cell growth, energetics, stress, and loss of prostate-specific biochemistry. Many metabolites were further associated with clinical findings of aggressive disease. Aggressiveness-associated metabolites stratified prostate tumor tissues with high abundances of compounds associated with normal prostate function (e.g., citrate and polyamines) from more clinically advanced prostate tumors. These aggressive prostate tumors were further subdivided by abundance profiles of metabolites including NAD+ and kynurenine. When added to multiparametric nomograms, metabolites improved prediction of organ confinement (AUROC from 0.53 to 0.62) and 5-year recurrence (AUROC from 0.53 to 0.64).

CONCLUSIONS

These findings support and extend earlier metabolomic studies in prostate cancer and studies where metabolic enzymes have been associated with carcinogenesis and/or outcome. Furthermore, these data suggest that panels of analytes may be valuable to translate metabolomic findings to clinically useful diagnostic tests.

TMEFF2 and SARDH cooperate to modulate one-carbon metabolism and invasion of prostate cancer cells

BACKGROUND

The transmembrane protein with epidermal growth factor and two follistatin motifs, TMEFF2, has been implicated in prostate cancer but its role in this disease is unclear. We recently demonstrated that the tumor suppressor role of TMEFF2 correlates, in part, with its ability to interact with sarcosine dehydrogenase (SARDH) and modulate sarcosine level. TMEFF2 overexpression inhibits sarcosine-induced invasion. Here, we further characterize the functional interaction between TMEFF2 and SARDH and their link with one-carbon (1-C) metabolism and invasion.

METHODS

RNA interference was used to study the effect of SARDH and/or TMEFF2 knockdown (KD) in invasion, evaluated using Boyden chambers. The dependence of invasion on 1-C metabolism was determined by examining sensitivity to methotrexate. Real-time PCR and Western blot of subcellular fractions were used to study the effect of SARDH KD or TMEFF2 KD on expression of enzymes involved in one-carbon (1-C) metabolism and on TMEFF2 expression and localization. Protein interactions were analyzed by mass spectrometry. Cell viability and proliferation were measured by cell counting and MTT analysis.

RESULTS

While knocking down SARDH affects TMEFF2 subcellular localization, this effect is not responsible for the increased invasion observed in SARDH KD cells. Importantly, SARDH and/or TMEFF2 KD promote increased cellular invasion, sensitize the cell to methotrexate, render the cell resistant to invasion induced by sarcosine, a metabolite from the folate-mediated 1-C metabolism pathway, and affect the expression level of enzymes involved in that pathway.

CONCLUSIONS

Our findings define a role for TMEFF2 and the folate-mediated 1-C metabolism pathway in modulating cellular invasion.

Prospective evaluation of serum sarcosine and risk of prostate cancer in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial

Metabolomic profiling has identified, sarcosine, a derivative of the amino acid glycine, as an important metabolite involved in the etiology or natural history of prostate cancer. We examined the association between serum sarcosine levels and risk of prostate cancer in 1122 cases (813 non-aggressive and 309 aggressive) and 1112 controls in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Sarcosine was quantified using high-throughput liquid chromatography-mass spectrometry. A significantly increased risk of prostate cancer was observed with increasing levels of sarcosine (odds ratio [OR] for the highest quartile of exposure [Q4] versus the lowest quartile [Q1] = 1.30, 95% confidence interval [CI]: 1.02, 1.65; P-trend 0.03). When stratified by disease aggressiveness, we observed a stronger association for non-aggressive cases (OR for Q4 versus Q1 = 1.44, 95% CI: 1.11, 1.88; P-trend 0.006) but no association for aggressive prostate cancer (OR for Q4 versus Q1 = 1.03, 95% CI: 0.73, 1.47; P-trend 0.89). Although not statistically significant, temporal analyses showed a stronger association between sarcosine and prostate cancer for serum collected closer to diagnosis, suggesting that sarcosine may be an early biomarker of disease. Interestingly, the association between sarcosine and prostate cancer risk was stronger among men with diabetes (OR = 2.66, 95% CI: 1.04, 6.84) compared with those without reported diabetes (OR = 1.23, 95% CI: 0.95-1.59, P-interaction = 0.01). This study found that elevated levels of serum sarcosine are associated with an increased prostate cancer risk and evidence to suggest that sarcosine may be an early biomarker for this disease.

Sarcosine and other metabolites along the choline oxidation pathway in relation to prostate cancer--a large nested case-control study within the JANUS cohort in Norway

Methyl group donors and intermediates of one-carbon metabolism affect DNA synthesis and DNA methylation, and may thereby affect prostate carcinogenesis. Choline, the precursor of betaine, and the one-carbon metabolite sarcosine have been associated with increased prostate cancer risk. Within JANUS, a prospective cohort in Norway (n = 317,000) with baseline serum samples, we conducted a nested case-control study among 3,000 prostate cancer cases and 3,000 controls. Using conditional logistic regression, odds ratios (ORs) and 95% confidence intervals (CIs) for prostate cancer risk were estimated according to quintiles of circulating betaine, dimethylglycine (DMG), sarcosine, glycine and serine. High sarcosine and glycine concentrations were associated with reduced prostate cancer risk of borderline significance (sarcosine: highest vs. lowest quintile OR = 0.86, CI = 0.72-1.01, p(trend) = 0.03; glycine: OR = 0.83, CI = 0.70-1.00, p(trend) = 0.07). Serum betaine, DMG and serine were not associated with prostate cancer risk. However, individuals with a high glycine/serine ratio were at decreased prostate cancer risk (OR = 0.74, CI = 0.69-0.85, p(trend) < 0.001). This population-based study suggested that men with high serum sarcosine or glycine concentrations have modestly reduced prostate cancer risk. Ratios of metabolites reflecting one-carbon balance may be associated with prostate cancer risk, as demonstrated for the glycine/serine ratio, and should be explored in future studies.

Sarcosine as a potential prostate cancer biomarker--a review

Prostate cancer (CaP) is the most common type of tumour disease in men. Early diagnosis of cancer of the prostate is very important, because the sooner the cancer is detected, the better it is treated. According to that fact, there is great interest in the finding of new markers including amino acids, proteins or nucleic acids. Prostate specific antigen (PSA) is commonly used and is the most important biomarker of CaP. This marker can only be detected in blood and its sensitivity is approximately 80%. Moreover, early stages cannot be diagnosed using this protein. Currently, there does not exist a test for diagnosis of early stages of prostate cancer. This fact motivates us to find markers sensitive to the early stages of CaP, which are easily detected in body fluids including urine. A potential is therefore attributed to the non-protein amino acid sarcosine, which is generated by glycine-N-methyltransferase in its biochemical cycle. In this review, we summarize analytical methods for quantification of sarcosine as a CaP marker. Moreover, pathways of the connection of synthesis of sarcosine and CaP development are discussed.

Spondin-2, a secreted extracellular matrix protein, is a novel diagnostic biomarker for prostate cancer

PURPOSE

SPON2 belongs to the F-spondin family of secreted extracellular matrix proteins. It is deregulated in some tumors, including prostate cancer. In this prospective study we assessed the role of serum SPON2 as a biomarker for prostate cancer diagnosis as well as any association between SPON2 levels and clinicopathological features. We also compared the diagnostic performance of this biomarker to that of serum sarcosine, and percent free-to-total and total prostate specific antigen.

MATERIALS AND METHODS

SPON2 was measured using a sandwich enzyme linked immunosorbent assay in serum samples from 286 patients with prostate cancer and 68 with no evidence of malignancy, as confirmed by 10 to 12-core ultrasound guided prostate biopsy. Nonparametric statistical tests and ROC analysis were done to assess the diagnostic performance of SPON2 vs the other biomarkers.

RESULTS

Median serum SPON2 was significantly higher in patients with prostate cancer than in those with no evidence of malignancy (77.5 vs 23.6 ng/ml, p<0.0001). ROC analysis showed a higher predictive value of SPON2 (AUC 0.952) than of serum sarcosine (AUC 0.674), percent free-to-total prostate specific antigen (AUC 0.806) and total prostate specific antigen (AUC 0.561). Moreover, patients with low grade prostate cancer had higher median SPON2 levels (p=0.001). Spearman rank correlation confirmed a negative association with Gleason score (rs=-0.29, p=0.0005).

CONCLUSIONS

We found evidence that SPON2 levels were significantly higher in patients with prostate cancer than in healthy individuals. Moreover, this biomarker had better diagnostic performance than serum sarcosine, and percent free-to-total and total prostate specific antigen. This greater accuracy was also present in a subset of patients with normal prostate specific antigen.

Molecular diagnostic trends in urological cancer: biomarkers for non-invasive diagnosis

The early detection of urological cancers is pivotal for successful patient treatment and management. The development of molecular assays that can diagnose disease accurately, or that can augment current methods of evaluation, would be a significant advance. Ideally, such molecular assays would be applicable to non-invasively obtained body fluids, enabling not only diagnosis of at risk patients, but also asymptomatic screening, monitoring disease recurrence and response to treatment. The advent of advanced proteomics and genomics technologies and associated bioinformatics development is bringing these goals into focus. In this article we will discuss the promise of biomarkers in urinalysis for the detection and clinical evaluation of the major urological cancers, including bladder, kidney and prostate. The development of urine-based tests to detect urological cancers would be of tremendous benefit to both patients and the healthcare system.

Expanding the reach of cancer metabolomics

Metabolism is again emerging as a key property that differentiates normal cells from neoplastic tissues. The coupling of this phenomenon with advanced bioanalytic methods may now open new avenues for diagnostics in cancer via discovery of chemical biomarkers. In this issue of Cancer Prevention Research, Montrose and colleagues apply metabolic profiling to a model of chemically induced colorectal cancer and describe the metabolomic landscape of colorectal tumors and associated biofluids in great detail. Their analysis of plasma and fecal metabolites provides inroads into the noninvasive detection of colorectal cancer using biochemical markers, as some conserved metabolic changes were altered across tumors, plasma, and feces. Meanwhile, the specific alterations identified in this study offer insights into potential metabolic drivers of colorectal cancer. For example, elevated sarcosine and 2-hydroxyglutarate were detected in these induced tumors, implicating their respective metabolic pathways and downstream interactions in colorectal cancer progression. This work highlights the potential value of cancer metabolomics for the noninvasive analysis of colorectal neoplasias while underscoring the importance of profiling diverse sample sets and metabolites in relevant cancer models to identify and validate such findings.

Serum sarcosine increases the accuracy of prostate cancer detection in patients with total serum PSA less than 4.0 ng/ml

BACKGROUND

Sarcosine is reported to be a differential metabolite that is greatly increased during prostate cancer (PCa) progression. In this study, we assessed the role of serum sarcosine as a biomarker for PCa, as well as any association between sarcosine levels and clinical-pathological parameters.

METHODS

Sarcosine was measured by fluorometric assay in serum samples from 290 PCa patients and 312 patients with no evidence of malignancy (NEM), confirmed by 8-12 core prostate biopsies. Nonparametric statistical tests and receiver operating characteristics (ROC) analyses were performed to assess the diagnostic performance of sarcosine in different (prostate-specific antigen) PSA ranges.

RESULTS

ROC analyses in subjects with PSA < 4 ng/ml showed a higher predictive value of sarcosine (AUC = 0.668) versus total PSA (AUC = 0.535) (P = 0.03), whereas for the other two PSA ranges (4-10 ng/ml and >10 ng/ml), percent ratio of free to total PSA (%fPSA) showed a predictive superiority over sarcosine. Moreover, in patients with a PSA < 4 ng/ml, the percentage of low/intermediate-grade cancers was positively associated with sarcosine levels (P = 0.005). The specificities for serum sarcosine, %fPSA, PSA, and the logistic regression model at 95% sensitivity were 24.4, 3.41, 2.22, and 28.4%, respectively.

CONCLUSIONS

We provide evidence that serum sarcosine has a higher predictive value than tPSA and %fPSA in patients with PSA < 4 ng/ml. Moreover, sarcosine levels were significantly different in low grade versus high grade cancers in this subset of patients, suggesting that this marker may be a further tool not only for diagnosing PCa in normal PSA and abnormal DRE/TRUS patients but also for selecting candidates for non-aggressive therapies and active surveillance.

Recent advances in metabolomics in oncology

The burden of cancer is growing worldwide and with it a more desperate need for better tools to detect, diagnose and monitor the disease is required. It is well recognized that cancer cells are characterized by distinct metabolic perturbations. The metabolomics approach involves the comprehensive profiling of the full complement of low MW compounds in a biological system. By applying advanced analytical and statistical tools, the 'metabolome' is mined for biomarkers that are associated with the state of cancer. This review presents an introduction to the main analytical platforms used in metabolomics analyses, such as NMR spectroscopy and MS, as well as the statistical tools used to mine these datasets. The discussion focuses on 'state-of-the-art' investigations on the four cancer types that have received the most study by metabolomics, namely breast, prostate, colorectal and liver cancer.

Validation study of urinary metabolites as potential biomarkers for prostate cancer detection

Background: Urinary metabolomic profiles have recently drawn a lot of attention owing to a debate regarding their possible role as potential clinical markers for prostate cancer. In this study, levels of proline, kynurenine, uracil and glycerol-3-phosphate in 126 patients with genitourinary malignancies were analyzed using a validated method and compared with no evidence of malignancy. Results: The statistical results showed that these biomarkers cannot differentiate prostate cancer from no evidence of malignancy or from other related cancer types, such as bladder cancer. In addition, there was no significant difference in biomarker levels for T1 stages, T2 stages and Gleason scores <7, ≥7. From the correlation study, results showed/demonstrated that age or serum prostate-specific antigen levels do not influence these metabolite concentrations in urine. However, the strong correlation between these metabolites and urinary creatinine concentrations implies that their occurrence is mainly due to renal excretion. Conclusion: This detailed study shows that the aforementioned urinary metabolites are not reliable biomarkers for prostate cancer detection or for differentiating the aggressiveness of prostate cancer.

Exclusive recognition of sarcosine in water and urine by a cavitand-functionalized silicon surface

A supramolecular approach for the specific detection of sarcosine, recently linked to the occurrence of aggressive prostate cancer forms, has been developed. A hybrid active surface was prepared by the covalent anchoring on Si substrates of a tetraphosphonate cavitand as supramolecular receptor and it was proven able to recognize sarcosine from its nonmethylated precursor, glycine, in water and urine. The entire complexation process has been investigated in the solid state, in solution, and at the solid-liquid interface to determine and weight all the factors responsible of the observed specificity. The final outcome is a Si-based active surface capable of binding exclusively sarcosine. The complete selectivity of the cavitand-decorated surface under these stringent conditions represents a critical step forward in the use of these materials for the specific detection of sarcosine and related metabolites in biological fluids.

Fully automated solid-phase microextraction-fast gas chromatography-mass spectrometry method using a new ionic liquid column for high-throughput analysis of sarcosine and N-ethylglycine in human urine and urinary sediments

A fully automated, non invasive, rapid and high-throughput method for the direct determination of sarcosine and N-ethylglycine in urine and urinary sediments using hexyl chloroformate derivatization followed by direct immersion solid-phase micro extraction and fast gas chromatography-mass spectrometric analysis was developed and validated. The use of a new ionic liquid narrow bore column, as well as the automation and miniaturization of the preparation procedure by a customized configuration of the utilized XYZ robotic system, allowed a friendly use of the GC apparatus achieving a quantitation limit of 0.06 μg L(-1) for sarcosine, good repeatability with CV always lower than 7% and reduced analysis times useful for point-of-care testing. The method was then applied for the analysis of 56 samples of urine and urinary sediments in healthy subjects, in those with benign prostatic hypertrophy and in patients with clinically localized prostate cancer. The results obtained showed that the medians of sarcosine/creatinine in urine were 103, 137 and 267 μg g(-1) respectively, thus assessing the potential use of sarcosine as urinary biomarker for prostate cancer detection. The highest values of sensitivity (79%) and specificity (87%) were obtained in correspondence of a cut-off value of 179 μg sarcosine(g creatinine)(-1), thus by using this cut-off threshold, sarcosine was significantly associated with the presence of cancer (p<0.0001). Finally, ROC analyses proved that the discrimination between clinically localized prostate cancer and patients without evidence of tumor is significantly correlated with sarcosine.

Application of metabolomics to prostate cancer

The prostate has long been known to exhibit unique metabolite profiles. In the last decade, advances in nuclear magnetic resonance spectroscopy and mass spectrometry have been applied toward identifying metabolic alterations in prostate cancer that may provide clinically useful biomarkers. As with genomics and proteomics, advances in technology and bioinformatics have led to the application of metabolomic profiling to prostate cancer-the high throughput evaluation of a large complement of metabolites in the prostate and how they are altered by disease perturbations. Recently, high profile publications have drawn attention to the potential of metabolomic analysis to identify biomarkers for early detection or disease progression from readily accessible body fluids as well as tissue specimens from biopsy and surgery. This review will examine applications of metabolomics to prostate cancer and highlight clinical associations and potential challenges.

Serum methionine metabolites are risk factors for metastatic prostate cancer progression

BACKGROUND

Clinical decision for primary treatment for prostate cancer is dictated by variables with insufficient specificity. Early detection of prostate cancer likely to develop rapid recurrence could support neo-adjuvant therapeutics and adjuvant options prior to frank biochemical recurrence. This study compared markers in serum and urine of patients with rapidly recurrent prostate cancer to recurrence-free patients after radical prostatectomy. Based on previous identification of urinary sarcosine as a metastatic marker, we tested whether methionine metabolites in urine and serum could serve as pre-surgical markers for aggressive disease.

METHODOLOGY/PRINCIPAL FINDINGS

Urine and serum samples (n = 54 and 58, respectively), collected at the time of prostatectomy were divided into subjects who developed biochemical recurrence within 2 years and those who remained recurrence-free after 5 years. Multiple methionine metabolites were measured in urine and serum by GC-MS. The role of serum metabolites and clinical variables (biopsy Gleason grade, clinical stage, serum prostate specific antigen [PSA]) on biochemical recurrence prediction were evaluated. Urinary sarcosine and cysteine levels were significantly higher (p = 0.03 and p = 0.007 respectively) in the recurrent group. However, in serum, concentrations of homocysteine (p = 0.003), cystathionine (p = 0.007) and cysteine (p<0.001) were more abundant in the recurrent population. The inclusion of serum cysteine to a model with PSA and biopsy Gleason grade improved prediction over the clinical variables alone (p<0.001).

CONCLUSIONS

Higher serum homocysteine, cystathionine, and cysteine concentrations independently predicted risk of early biochemical recurrence and aggressiveness of disease in a nested case control study. The methionine metabolites further supplemented known clinical variables to provide superior sensitivity and specificity in multivariable prediction models for rapid biochemical recurrence following prostatectomy.