Validation Study of Urinary Metabolites As Potential Biomarkers For Prostate Cancer Detection

Gamagedara, Sanjeewa; Kaczmarek, A; Jiang, Yongqing; Cheng, Xiaoliang; Rupasinghe, Maduka; Ma, Yinfa

doi:10.4155/bio.12.92

Cited by 22 publications

(28 citation statements)

References 15 publications

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“…found no association between prostate cancer and sarcosine levels in blood or tissue (43). Sarcosine could not be reliably measured in two further studies (30, 37), however Shuster et al . replicated Sreekumar et al .…”

Section: Resultsmentioning

confidence: 88%

“…This was in line with the findings of Huang et al (51), who reported that the metabolite profiles of patients successfully treated with endocrine therapy, closely resembled those of healthy controls. Among all the included studies one did not report any significant findings (37). This study, by Gamagedara et al was targeted to only four metabolites that had previously been reported as significant in tissue.…”

Section: Resultsmentioning

confidence: 99%

“…It is it notable that is it analytically challenging to precisely and accurately measure sarcosine, particularly at low concentrations (68), as is evidenced by the two studies that were unable to do so (30, 37). It has been suggested that liquid chromatography for sample separation prior to MS, may be preferable to gas chromatography for the measurement of sarcosine and that this may explain the conflicting findings (68).…”

Section: Resultsmentioning

confidence: 99%

“…In common with the majority of the existing metabolomics literature (54), all studies were case-control in design; including two nested within cohorts (22, 23). Twenty-two studies used external controls who were either healthy (n=13 studies) (22, 23, 34, 37-42, 49-52), suffering from benign prostatic hyperplasia (BPH) (n=3) (26, 29, 53), non-recurrent cases (n=2) (45, 48) or they included multiple control groups (n=4) (25, 35, 36, 43). In the remainder, the prostate cancer cases acted as their own controls through the use of matched biological samples or the measurement of metabolites pre-and post-therapy.…”

Section: Study Designs and Methodsmentioning

confidence: 99%

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Metabolomic Biomarkers of Prostate Cancer: Prediction, Diagnosis, Progression, Prognosis, and Recurrence

Kelly

Heiden

Giovannucci

et al. 2016

Cancer Epidemiology, Biomarkers &Amp; Prevention

107

111

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Metabolite profiling is being increasing employed in the study of prostate cancer as a means of identifying predictive, diagnostic and prognostic biomarkers. This review provides a summary and critique of the current literature. Thirty-three human case-control studies of prostate cancer exploring disease prediction, diagnosis, progression or treatment response were identified. All but one demonstrated the ability of metabolite profiling to distinguish cancer from benign, tumor aggressiveness, cases who recurred, and those who responded well to therapy. In the subset of studies where biomarker discriminatory ability was quantified, high AUCs were reported that would potentially outperform the current gold standards in diagnosis, prognosis and disease recurrence, including PSA testing. There were substantial similarities between the metabolites and the associated pathways reported as significant by independent studies, and important roles for abnormal cell growth, intensive cell proliferation and dysregulation of lipid metabolism were highlighted. The weight of the evidence therefore suggests metabolic alterations specific to prostate carcinogenesis and progression that may represent potential metabolic biomarkers. However, replication and validation of the most promising biomarkers is currently lacking and a number of outstanding methodological issues remain to be addressed in order to maximize the utility of metabolomics in the study of prostate cancer.

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Section: Resultsmentioning

confidence: 88%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Study Designs and Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Metabolomic Biomarkers of Prostate Cancer: Prediction, Diagnosis, Progression, Prognosis, and Recurrence

Kelly

Heiden

Giovannucci

et al. 2016

Cancer Epidemiology, Biomarkers &Amp; Prevention

107

111

View full text Add to dashboard Cite

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“…However, it must be considered that sulfites occurring naturally or as additives in foods and beverages are also metabolized to thiosulfate and could be an interfering factor in this respect [19]. Other studies that aimed to validate differentially expressed metabolites in prostate cancer tissue [15] (sarcosine, proline, kynurenine, uracil, and glycerol-3-phosphate) as non-invasive biomarkers in urine proved a rather strong correlation of these metabolites with their renal excretion but not with the cancer status [20,21].…”

mentioning

confidence: 99%

Thiosulfate in urine: new hope or new failure of a biomarker for prostate cancer?

Jung¹,

Stephan²

2013

Clinical Chemistry and Laboratory Medicine

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Partial enzymatic elimination and quantification of sarcosine from alanine using liquid chromatography–tandem mass spectrometry

Burton

Gamagedara

2013

Anal Bioanal Chem

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Since sarcosine and D,L-alanine co-elute on reversed-phase high-performance liquid chromatography (HPLC) columns and the tandem mass spectrometer cannot differentiate them due to equivalent parent and fragment ions, derivatization is often required for analysis of sarcosine in LC/MS systems. This study offers an alternative to derivatization by employing partial elimination of sarcosine by enzymatic oxidation. The decrease in apparent concentration from the traditionally merged sarcosine-alanine peak associated with the enzymatic elimination has been shown to be proportional to the total sarcosine present (R(2) = 0.9999), allowing for determinations of urinary sarcosine. Sarcosine oxidase was shown to eliminate only sarcosine in the presence of D,L-alanine, and was consequently used as the selective enzyme. This newly developed technique has a method detection limit of 1 μg/L (parts per billion) with a linear range of 3 ppb-1 mg/L (parts per million) in urine matrices. The method was further validated through spiked recoveries of real urine samples, as well as the analysis of 35 real urine samples. The average recoveries for low, middle, and high sarcosine concentration spikes were 111.7, 90.8, and 90.1 %, respectively. In conclusion, this simple enzymatic approach coupled with HPLC/MS/MS is able to resolve sarcosine from D,L-alanine leading to underivatized quantification of sarcosine.

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Validation Study of Urinary Metabolites As Potential Biomarkers For Prostate Cancer Detection

Abstract: 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.

Cited by 22 publications

References 15 publications

Metabolomic Biomarkers of Prostate Cancer: Prediction, Diagnosis, Progression, Prognosis, and Recurrence

Metabolomic Biomarkers of Prostate Cancer: Prediction, Diagnosis, Progression, Prognosis, and Recurrence

Thiosulfate in urine: new hope or new failure of a biomarker for prostate cancer?

Partial enzymatic elimination and quantification of sarcosine from alanine using liquid chromatography–tandem mass spectrometry

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