Biomarker For Diagnosis Of Prostate Cancer Research Articles

204 Plasma circulating miRNAs: A new potential biomarker for prostate cancer diagnosis

204 Plasma circulating miRNAs: A new potential biomarker for prostate cancer diagnosis

Identification of miR-187 and miR-182 as Biomarkers of Early Diagnosis and Prognosis in Patients with Prostate Cancer Treated with Radical Prostatectomy

miRNAs are noncoding RNAs that negatively regulate target mRNA gene expression. Aberrant miRNA expression is associated with prostate cancer pathogenesis. We identified miRNAs as potential biomarkers for prostate cancer diagnosis and prognosis. Total RNA was obtained from 10 normal prostate and 50 prostate cancer samples, and analyzed using the GeneChip® miRNA 2.0 Array. At a median followup of 92 months (range 2 to 189) an independent cohort of 273 paraffin embedded prostate cancer samples was used for validation by quantitative reverse transcriptase-polymerase chain reaction. Another 92 urine samples from patients undergoing prostate biopsy were evaluated for these miRNAs. miR-182 and 187, the miRNAs most differentially expressed between normal and tumor tissue, were selected for further validation. miR-187 inversely correlated with cT (p = 0.125) and pT (p = 0.0002) stages, Gleason score (p = 0.003) and TMPRSS2-ERG status (p = 0.003). The log rank test showed associations of miR-182 with biochemical (p = 0.026) and clinical (p = 0.043) progression-free survival, as also noted on multivariate analysis. A significant independent improvement in the definition of risk of progression was achieved by combining miR-182 expression with Gleason score (p <0.0001). miR-187 detection in urine provided an independent predictive value for positive biopsy. A prediction model including serum prostate specific antigen, urine PCA3 and miR-187 provided 88.6% sensitivity and 50% specificity (AUC 0.711, p = 0.001). Results show that miR-182 and 187 are promising biomarkers for prostate cancer prognosis to identify patients at risk for progression and for diagnosis to improve the predictive capability of existing biomarkers.

New serum biomarkers for prostate cancer diagnosis

Prostate-specific antigen (PSA) is currently used as a biomarker for diagnosis and management of prostate cancer (CaP). However, PSA typically lacks the sensitivity and specificity desired of a diagnostic marker. The goal of this study was to identify an additional biomarker or a panel of biomarkers that is more sensitive and specific than PSA in differentiating benign versus malignant prostate disease and/or localized CaP versus metastatic CaP. Concurrent measurements of circulating interleukin-8 (IL-8), Tumor necrosis factor-α (TNF-α) and soluble tumor necrosis factor-α receptors 1 (sTNFR1) were obtained from four groups of men: (1) Controls (2) with elevated prostate-specific antigen with a negative prostate biopsy (elPSA_negBx) (3) with clinically localized CaP and (4) with castration resistant prostate cancer. TNF-α Area under the receiver operating characteristic curve (AUC = 0.93) and sTNFR1 (AUC = 0.97) were strong predictors of elPSA_negBx (vs. CaP). The best predictor of elPSA_negBx vs CaP was sTNFR1 and IL-8 combined (AUC = 0.997). The strongest single predictors of localized versus metastatic CaP were TNF-α (AUC = 0.992) and PSA (AUC = 0.963) levels. The specificity and sensitivity of a PSA-based CaP diagnosis can be significantly enhanced by concurrent serum measurements of IL-8, TNF-α and sTNFR1. In view of the concerns about the ability of PSA to distinguish clinically relevant CaP from indolent disease, assessment of these biomarkers in the larger cohort is warranted.

Prospective Application of Lipidomics in Prostate Cancer

Lipidomics, a rapidly developing research field, has been widely studied in many non-cancer areas, and in some cancers. Taking prostate cancer as an example, this article has concisely reviewed applications of lipidomics in cancer research. Lipidomics is able to identify a few out of thousands individual lipid species in bio-fluids as biomarkers in diagnosis of prostate cancer with high sensitivity, specificity and accuracy. This technology has been also used in studying the pathogenesis of prostate cancer by combining data of lipid profiling with lipid metabolites and pathways strategy. Importantly, lipidomics can provide details of lipid compositions different between prostate cancer and benign prostate, which will greatly help to make strategy in prevention and treatment of prostate cancer.

Novel biomarker for prostate cancer diagnosis by MRS

Magnetic resonance spectroscopy (MRS) is a prospective tool for characterization of the chemical composition of tissues. In vivo MRS can be used for metabolite profiling in the prostate tissue to discriminate non-invasively carcinomas and healthy prostate. In this article different prostate metabolites have been discussed and how to exploit the MRS technique for the estimation of metabolites in prostate tissue quantitatively is elucidated. Choline, citrate, creatine, myo-inositol metabolites can be considered as biomarker for localization of malignancy in the prostate and their ratio can be used for the determination of cancer tissue in the prostate gland.

Expression of the cancer‐testis antigen BORIS correlates with prostate cancer

BORIS, a paralogue of the transcription factor CTCF, is a member of the cancer-testis antigen (CT) family. BORIS is normally present at high levels in the testis; however it is aberrantly expressed in various tumors and cancer cell lines. The main objectives of this study were to investigate BORIS expression together with sub-cellular localization in both prostate cell lines and tumor tissues, and assess correlations between BORIS and clinical/pathological characteristics. We examined BORIS mRNA expression, protein levels and cellular localization in a panel of human prostate tissues, cancer and benign, together with a panel prostate cell lines. We also compared BORIS levels and localization with clinical/pathological characteristics in prostate tumors. BORIS was detected in all inspected prostate cancer cell lines and tumors, but was absent in benign prostatic hyperplasia. Increased levels of BORIS protein positively correlated with Gleason score, T-stage and androgen receptor (AR) protein levels in prostate tumors. The relationship between BORIS and AR was further highlighted in prostate cell lines by the ability of ectopically expressed BORIS to activate the endogenous AR mRNA and protein. BORIS localization in the nucleus plus cytoplasm was also associated with higher BORIS levels and Gleason score. Detection of BORIS in prostate tumors suggests potential applications of BORIS as a biomarker for prostate cancer diagnosis, as an immunotherapy target and, potentially, a prognostic marker of more aggressive prostate cancer. The ability of BORIS to activate the AR gene indicates BORIS involvement in the growth and development of prostate tumors.

Cell-free plasma DNA for the diagnosis and follow-up of prostate cancer patients.

e16058 Background: Cell free plasma DNA (CF–pDNA) may have diagnostic and prognostic value in patients with Prostate Cancer (PCa). Methods: We included 133 men with PCa and 33 controls. PCa patients had blood drawn every 3 months for 2 years. CFpDNA was measured by spectrophotometry. Results: CF-pDNA had an area under the curve of 0.824 with a sensitivity of 66.2%, a specificity of 87.9% ,a positive and negative likelihood ratios of 5.46 and 0.39, respectively. There was no statistical significant correlation between CF-pDNA levels at study entry with PSA, Gleason score, stage and biochemical recurrence free survival(BRFS). However, with a mean follow up of 13.5 months, we observed significantly shorter BRFS for patients with at least one value above 140 ng/ mL of CF-pDNA during follow up (p= 0.048). Conclusions: CF-pDNA is a potentially valuable biomarker for PCa diagnosis and may have a prognostic role during follow-up of patients with PCa.

Gp78 is specifically expressed in human prostate cancer rather than normal prostate tissue

Elevated expression of gp78 has been observed in many types of cancers including lung, stomach, colon, liver and skin cancer. But there is no report about its expression in prostate cancers. In this study, using immunohistochemical staining we found gp78 is highly expressed in prostate cancers especially early stage tumors, but not in normal prostate tissues. gp78 protein expression is heterogeneous. In some tumors it was expressed in basal cells, while others in stromal cells. For gp78 is a ubiquitin E3 ligase, we then investigated the expression pattern of its cognate E2 (ubiquitin conjugating enzyme)-Ube2g2 in prostate cancers. We found it was expressed in both cancerous and normal tissues of prostate without significant differences in expression level. And unlike gp78, it exhibited a homogeneous expression pattern in different cell types in prostate tissues. In conclusion, our results indicate that gp78 is expressed specifically in human prostate cancer rather than normal prostate tissues, it could be a putative biomarker for prostate cancer diagnosis.

Spondin-2, a Secreted Extracellular Matrix Protein, is a Novel Diagnostic Biomarker for Prostate Cancer

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. 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. 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). 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.

Identification of New Differentially Methylated Genes That Have Potential Functional Consequences in Prostate Cancer

Many differentially methylated genes have been identified in prostate cancer (PCa), primarily using candidate gene-based assays. Recently, several global DNA methylation profiles have been reported in PCa, however, each of these has weaknesses in terms of ability to observe global DNA methylation alterations in PCa. We hypothesize that there remains unidentified aberrant DNA methylation in PCa, which may be identified using higher resolution assay methods. We used the newly developed Illumina HumanMethylation450 BeadChip in PCa (n = 19) and adjacent normal tissues (n = 4) and combined these with gene expression data for identifying new DNA methylation that may have functional consequences in PCa development and progression. We also confirmed our methylation results in an independent data set. Two aberrant DNA methylation genes were validated among an additional 56 PCa samples and 55 adjacent normal tissues. A total 28,735 CpG sites showed significant differences in DNA methylation (FDR adjusted P<0.05), defined as a mean methylation difference of at least 20% between PCa and normal samples. Furthermore, a total of 122 genes had more than one differentially methylated CpG site in their promoter region and a gene expression pattern that was inverse to the direction of change in DNA methylation (e.g. decreased expression with increased methylation, and vice-versa). Aberrant DNA methylation of two genes, AOX1 and SPON2, were confirmed via bisulfate sequencing, with most of the respective CpG sites showing significant differences between tumor samples and normal tissues. The AOX1 promoter region showed hypermethylation in 92.6% of 54 tested PCa samples in contrast to only three out of 53 tested normal tissues. This study used a new BeadChip combined with gene expression data in PCa to identify novel differentially methylated CpG sites located within genes. The newly identified differentially methylated genes may be used as biomarkers for PCa diagnosis.

Multiparametric magnetic resonance imaging of the prostate can improve the predictive value of the urinary prostate cancer antigen 3 test in patients with elevated prostate‐specific antigen levels and a previous negative biopsy

Study Type--Clinical (prospective trial) Level of Evidence 2b. What's known on the subject? and What does the study add? In clinical practice, we know that it is necessary to identify new biomarkers that can better detect prostate cancer (PC), at the same time as reducing the number of unnecessary biopsies. Recently, studies have suggested that the most relevant clinical scenario in which the prostate cancer antigen 3 (PCA3) score could be used comprises patients with a previous negative prostate biopsy and persistently elevated PSA levels. At the same time, although multiparametric MRI is not currently used as a first approach for diagnosing PC, it can be useful for directing targeted biopsies, especially in those patients with elevated PSA levels and a previous negative TRUS-guided biopsy. Considering all of these aspects, the present study aimed to evaluate the role of multiparametric MRI as an additional diagnostic tool for improving the accuracy of the urinary PCA3 test in patients with increased PSA levels and a previous negative prostate biopsy. Our hypothesis is that the potential value of the PCA3 test as a biomarker for PC diagnosis could be improved by the use of multiparametric MRI in directing prostate biopsy. In the present study, we show that, in cases with a previous negative biopsy and persistently elevated PSA levels submitted to multiparametric MRI to direct biopsies, the sensitivity of the PCA3 test significantly improved (79% vs 68%). However, further larger randomized studies on this combination using a new biomarker and a new imaging modality for PC diagnosis are expected. • To evaluate the role of multiparametric magnetic resonance imaging (MRI) as an additional diagnostic tool for improving the accuracy of the urinary prostate cancer antigen 3 (PCA3) test in patients with an increase in prostate-specific antigen (PSA) levels and a previous negative prostate biopsy. • The present study comprised a prospective randomized study on patients with a previous negative transrectal ultrasonography (TRUS)-guided prostate biopsy and elevated PSA levels. • In total, 180 cases were analyzed, and all were submitted to PCA3 assay. • Patients in group A were submitted to a second random TRUS-guided prostate biopsy, whereas patients in group B were submitted to a multiparametric MRI examination and then to a second TRUS-guided prostate biopsy. • At the second biopsy, a histological diagnosis of prostate cancer was found in 26 of 84 cases (30.9%) in group A and in 29 of 84 cases (34.5%) in group B. • In group A, the sensitivity and specificity of the PCA3 score were 68.0% and 74.5% respectively (positive predictive value of 53.1%, negative predictive value of 84.6% and accuracy of 72.6%). • In group B, the sensitivity and specificity of the PCA3 score were 79.3% and 72.7%, respectively (positive predictive value of 60.5%, negative predictive value of 86.9% and accuracy of 75.0%). • For the PCA3 score, the area under the receiver-operator characteristic curve was 0.825 (95% confidence interval, 0.726-0.899) in group A and 0.857 (95% confidence interval, 0.763-0.924) in group B (P < 0.001). • In patients with a previous negative biopsy and persistently elevated PSA levels, the use of multiparametric MRI for indicating sites suitable for rebiopsy can significantly improve the sensitivity of the PCA3 test in the diagnosis of prostate cancer.

Abstract A37: Low-density protein array reveals inflammation associated serum-autoantibody profile in prostate cancer.

Abstract Background: Chronic prostatic inflammation of the prostate is one of the main reasons for false positive serum PSA tests in prostate cancer screening. In addition there is accumulating evidence that an inflammatory microenvironment may support the development of malignancy and the progression to metastatic disease. Easy accessible and non-invasive indicators for prostate inflammation would be very helpful for a biopsy decision after an elevated PSA test result. However, at present, the histological examination of prostate biopsies remains the only way for identification of prostatic inflammation. The finding that cancer is immunogenic and that patients are able to elicit and potentially amplify an immune response against their tumor antigens suggests that autoantibodies serve as non-invasive serum biomarkers for prostate cancer diagnosis. Consequently, autoantibodies may also be capable of detecting differential disease progression grades -e.g. inflammatory states- enabling a more specific and individualized treatment in cancer therapy. In the present study, we aimed to find new non-invasive biomarkers for the diagnosis of prostatic inflammation in prostate cancer. Methods: Seventy prostate cancer tissue samples derived from radical prostatectomy were classified into two groups (high/low inflammation) according to the amount of tissue infiltrating lymphocytes. Clinical parameters including PSA, fPSA, GSC, prostate weight, prostate volume, tumor size, age and CRP were controlled for equal distribution amongst the two groups. The corresponding blood serum samples were analyzed using a low density protein array (microarray) containing 4012 prostate cancer associated and inflammation related recombinant proteins. Statistical comparison of the serum autoantibody profile in the two groups was used to identify differentially expressed biomarkers. Finally, specificity of candidate autoantibody markers was validated by immunohistochemical detection of corresponding autoantigens in prostate tissue. Results: Autoantibodies against 165 antigens were found to be differentially expressed in the high compared to the low inflammation group. 30 out of these proteins have recently been identified to be associated with prostate cancer. The identified autoantibody profile discriminated between prostate cancer patients bearing high or low inflammation in prostate tissue with a ROC curve AUC of 0.71. Out of the top ranked autoantibodies, three candidate proteins were selected due to their differential expression and significant up-regulation in serum samples of the high inflammation group: SPAST (Spastin), STX18 (Syntaxin 18) and SPOP (speckle-type POZ protein). Immunohistochemical analysis showed that targets of all three autoantibody candidates are expressed in epithelial prostate cells. Remarkably, the highest staining intensity was detected in tissue infiltrating lymphocytes in both high and low inflammation samples. Conclusion: The presented data evaluates the possible use of serum autoantibody markers as non-invasive indicators for the diagnosis of chronic inflammation in prostate cancer. The polyclonal immune response to aberrant proteins in heterogeneous diseases such as cancer and autoimmunity favors the development of autoantibody markers with potential specificities to detect disease subtypes and disease progression grades. We provide evidence for an inflammation specific antibody profile and verify the expression of three biomarker candidates in prostate tissue. Citation Format: Bettina Schlick, Petra Massoner, Angelika Luecking, Christof Saifarth, Georg Schaefer, Klaus Marquart, Peter Amersdorfer, Peter Schulz-Knappe, Helmut Klocker. Low-density protein array reveals inflammation associated serum-autoantibody profile in prostate cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Prostate Cancer Research; 2012 Feb 6-9; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2012;72(4 Suppl):Abstract nr A37.

541 MiRNA profiling in the screening of potential biomarkers for prostate cancer diagnosis

541 MiRNA profiling in the screening of potential biomarkers for prostate cancer diagnosis

Expression analysis of osteopontin mRNA splice variants in prostate cancer and benign prostatic hyperplasia

Osteopontin splicing isoforms (OPN-SI) present differential expression patterns and specific tumor roles. Our aims were to characterize OPN-SI expression in prostate cancer (PCa) and benign prostate hyperplasia (BPH) tissues, besides evaluating their potential as biomarkers for PCa diagnosis and prognostic implications. Prostatic tissue specimens were obtained from 40 PCa and 30 benign prostate hyperplasia (BPH) patients. Quantitative real time PCR (qRT-PCR) was used to measure OPN-SI mRNA expression. Immunohistochemical analysis was performed using an anti-OPNc polyclonal antibody. Biostatistical analyses evaluated the association of OPN-SI and total Prostate Specific Antigen (PSA) serum levels with clinical and pathological data. PCa tissue samples presented significantly higher levels of OPNa, OPNb and OPNc transcripts (p<0.01) than in BPH specimens. OPN-SI mRNA expression were positively correlated with Gleason Score (p<0.01). ROC curves and logistic regression analyses demonstrated that OPN-SI and PSA were able to distinguish PCa from BPH patients (p<0.01). The OPNc isoform was the most upregulated variant and the best marker to distinguish patients' groups, presenting sensitivity and specificity of 90% and 100%, respectively. Immunohistochemistry analysis also demonstrated OPNc upregulation in PCa samples as compared to BPH tissues. OPNcprotein was also strongly stained PCa tissues presenting High Gleason Score. Multivariate analysis indicated that OPNc expression levels above the cut-off value presented a chance 4-fold higher for PCa occurrence. We conclude that OPN-SI were overexpressed in PCa tissues, strongly associated with PCa occurrence and with tumor cell differentiation. Our results suggest OPNc splicing isoform as an important biomarker contributing to improve PCa diagnosis and prognosis, besides providing insights into early steps of PCa carcinogenesis.

KLK5 gene expression is severely upregulated in androgen-independent prostate cancer cells after treatment with the chemotherapeutic agents docetaxel and mitoxantrone

Kallikrein-related peptidases (KLKs), including KLK5, have been proposed as promising biomarkers for prostate cancer diagnosis and prognosis. In the present study, we report that distinct augmentations (up to 6.4-fold) of KLK5 mRNA expressional levels, calculated via quantitative real-time PCR, occur after treatment of DU145 cells with appropriate concentrations, determined by the MTT method, of docetaxel and mitoxantrone. Our data reveal the endogenous need of prostate cancer cells for modified KLK5 expression to cope with the administration of chemotherapeutic drugs. Furthermore, it is proposed that the expression profile of KLK5 could serve as a putative biomarker for monitoring the treatment response in hormone refractory prostate cancer patients.

Abstract C28: Discovery of new protein biomarkers for prostate cancer diagnosis using a Pten-dependent mouse model and their validation in human patients

Abstract Purpose: The identification of novel biomarkers for the detection of localized cancers will have a profound impact on human health, especially for tumors with silent progression such as prostate cancer. Current prostate cancer biomarkers such as Prostate Specific Antigen (PSA) have limited accuracy and there is a need for improved non-invasive diagnostic tests. Material and Methods: Blood is thought to pick up molecular cues as it circulates through the various tissues, collectively reflecting molecular processes active in those different tissues. To increase the proteomic detection sensitivity, we have developed a method for the selective analysis of N-glycosites from tissue and serum. The analysis of glycoproteins is ideally suited for the detection of such signatures because they are preferentially released from tissue and deposited in the bloodstream where they can be detected in a non-invasive fashion. In our study we initially used the Pten conditional knock-out mouse model for prostate cancer progression. This model in which the different stages of the disease can be deliberately and reproductively induced and followed, allowed us to simulate with very high fidelity the early steps of the human disease. Under the assumption that proteins of interest are enriched in the tissue, we performed label-free comparative proteomics of Pten−/− and control tissue at different time points. Interesting candidates were then monitored in the corresponding mice sera by targeted mass spectrometry using Multiple Reaction Monitoring (MRM) at high sensitivity and selectivity. Results: This approach enabled us to identify 785 N-linked glycoproteins, mostly located to relevant cellular compartments such as the extracellular space, the plasma membrane or the secretory pathway. Quantitative proteomic comparison of mice with homozygous Pten deletion and constitutive PKB activation with the corresponding control animals led to the identification of 153 candidate biomarkers differentially regulated in a Pten dependent manner. The validation phase was carried out using 76 sera collected from patients with either benign prostatic hyperplasia (n=35) or localized prostate cancer (n=41). Candidate biomarkers were monitored by immunoassays and/or targeted mass spectrometry. Using a cross-validated logistic regression approach in our ongoing study, we have identified a 4-biomarker signature that correctly predicts 71% of cases (sens. 78%/spec. 63%). In comparison, PSA correctly predicted 67% (sens. 89%/spec. 32%) at a cutoff of 2 ng/ml. By combining PSA with the 4-biomarker signature, accuracy was greatly improved and 87% of the cases were correctly predicted (sens. 90/spec. 83%). We further extended our analysis to the discovery of novel candidate serum biomarkers for the discrimination of aggressive cancers (Gleason score&amp;gt;7) from slow progressing cancers (Gleason score&amp;lt;=6) that may be considered for active surveillance instead of immediate active treatment. Conclusion: The use of a translational approach which relies on a genetically defined mouse model together with novel proteomics techniques and validation in human sera is thus an ideal starting point for the discovery of novel biomarkers. Citation Information: Cancer Res 2009;69(23 Suppl):C28.

The potential value of microseminoprotein‐β as a prostate cancer biomarker and therapeutic target

Recent genome-wide association studies have shown an association of a SNP two base pairs upstream of the 5' UTR of the microseminoprotein-beta (MSMB) gene with an increased risk of developing the prostate cancer, re-igniting interest in its protein product, MSMB. As one of the most abundant prostatic proteins, MSMB can be reliably detected in tissue and serum. It has been consistently shown that MSMB expression is high in normal and benign prostate tissue and lowered or lost in prostate cancer suggesting that it might be a useful tissue biomarker for prostate cancer diagnosis and its levels in serum may be useful as a marker for prognosis. Members of the cysteine-rich secretory protein family and laminin receptors have been shown to bind MSMB at the cell surface and in serum thereby regulating apoptosis. Thus, in the benign prostate, MSMB regulates cell growth, but when MSMB is lost during tumourigenesis, cells are able to grow in a more uncontrolled manner. Both full length MSMB and a short peptide comprised of amino acids 31-45 have been tested for potential therapeutic benefit in mouse models and humans. MSMB has potential as a biomarker of prostate cancer development, progression and recurrence and potentially as a target for therapeutic intervention.

The prostate-cancer metabolome

Non-invasive detection and prognostic evaluation of cancer represents a formidable challenge. Studies of the entire metabolite composition of cells promise advances towards this objective for prostate cancer. A systematic analysis of metabolites in prostate cancer samples has led to the discovery that sarcosine, an amino acid common in many biological tissues including muscle, is highly elevated in aggressive prostate cancers and detectable in the urine of men with prostate cancer. This makes sarcosine a candidate biomarker for prostate cancer diagnosis. Targeted knockdown of the enzyme that generates sarcosine from glycine attenuated prostate cell invasion in mice, pointing to a possible role in metastasis, and adding the sarcosine pathway to the list of possible therapeutic targets.