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.
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.
Authors: Nicolas Barry Delongchamps; Patrick Younes; Lydie Denjean; Marc Zerbib; Phuong-Nhi Bories Journal: World J Urol Date: 2014-07-05 Impact factor: 4.226
Authors: Stella Koutros; Tamra E Meyer; Stephen D Fox; Haleem J Issaq; Timothy D Veenstra; Wen-Yi Huang; Kai Yu; Demetrius Albanes; Lisa W Chu; Gerald Andriole; Robert N Hoover; Ann W Hsing; Sonja I Berndt Journal: Carcinogenesis Date: 2013-05-22 Impact factor: 4.944
Authors: Amjad P Khan; Thekkelnaycke M Rajendiran; Bushra Ateeq; Irfan A Asangani; Jyoti N Athanikar; Anastasia K Yocum; Rohit Mehra; Javed Siddiqui; Ganesh Palapattu; John T Wei; George Michailidis; Arun Sreekumar; Arul M Chinnaiyan Journal: Neoplasia Date: 2013-05 Impact factor: 5.715
Authors: Tong Zhang; David G Watson; Lijie Wang; Muhammad Abbas; Laura Murdoch; Lisa Bashford; Imran Ahmad; Nga-Yee Lam; Anthony C F Ng; Hing Y Leung Journal: PLoS One Date: 2013-06-18 Impact factor: 3.240