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A Comparison of Different Algorithms of Sarcosine in Urine

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A Comparison of Different Algorithms of Sarcosine in Urine Prostate Cancer and Prostatic Diseases (2011) 14, 166–172 & 2011 Macmillan Publishers Limited All rights reserved 1365-7852/11 www.nature.com/pcan ORIGINAL ARTICLE Efforts to resolve the contradictions in early diagnosis of prostate cancer: a comparison of different algorithms of sarcosine in urine D-L Cao1,2, D-W Ye1,2, Y Zhu1,2, H-L Zhang1,2, Y-X Wang3 and X-D Yao1,2 1Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China; 2Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China and 3Phase I clinical laboratory, Fudan University Shanghai Cancer Center, Shanghai, China Controversial data on sarcosine as a promising biomarker for prostate cancer (PCa) detection are present. The objective was to clarify these discrepancies and reevaluate the potential value of sarcosine in PCa. Sarcosine algorithms (supernatant and sediment sarcosine/creatinine, supernatant and sediment log2 (sarcosine/alanine)) in urine samples from 71 untreated patients with PCa, 39 patients with no evidence of malignancy (NEM) and 20 healthy women and men were quantified by liquid chromatography/tandem mass spectrometry. Although any sarcosine algorithms were significantly higher in PCa patients than in NEM patients (all Po0.05), comparable sarcosine values were measured in healthy women and men. Additionally, neither biopsy Gleason score nor clinical T-stage were correlated with sarcosine algorithms (all P40.05), and receiver operating characteristic curve analysis indicated that the diagnostic power of any of sarcosine algorithms was nonsignificantly higher than that of serum and urine PSA, but nonsignificantly lower than prostate cancer antigen 3 (PCA3) and the percent-free PSA (%fPSA). Improved diagnostic performances were observed when any of sarcosine algorithms was combined with PCA3 or %fPSA. In conclusion, the predictive power of sarcosine in PCa is modest compared with PCA3 and %fPSA. Sarcosine, which awaits more validation before it reaches the clinic, could be included into the list of candidate PCa biomarkers. Prostate Cancer and Prostatic Diseases (2011) 14, 166–172; doi:10.1038/pcan.2011.2; published online 15 February 2011 Keywords: prostate cancer detection; prostate cancer antigen 3; PSA; sarcosine in urine Introduction Notably, Sreekumar et al.8 demonstrated that sarcosine can be used as a biomarker for PCa and was non-invasively Prostate cancer (PCa) is one of the most commonly detected in urine, which led to great interest in the scientific diagnosed malignancies, and is the second leading cause community and among potential PCa patients. However, of cancer-related deaths in the Western male population.1 the first independent validation study9 showed that In China, the detection rate of PCa is increasing rapidly sarcosine cannot be used as a biomarker to diagnose because of the extension of life expectancy, the change of PCa and predict its aggression. Following these observa- lifestyles and the improvement of clinical skills.2 Subse- tions, letters and replies10–16 were published to discuss quently, conquering this stubborn disease has significant potential reasons for the contradictions between these two effect on the improvement of the health of the global studies.8,9 Although many possibilities (for example, the male population. On the basis of individual metabolites analytical method, the biomarker assay, the comparators representing end points of the molecular pathways and the study cohort) were discussed; no data from perturbed by events in the genome, transcriptome or complete article has been reported. proteome, newly emerging metabolite profile or meta- In this report, we sought to use liquid chromatogra- bolomics shows potential to monitor metabolite changes phy/tandem mass spectrometry, compare log2 (sarco- that characterize abnormal processes occurring in the sine/alanine) and sarcosine/creatinine in both urinary progression of disease and might provide clues for the supernatant and sediment and use prostate cancer treatment and diagnosis of disease.3,4 To the best of our antigen 3 (PCA3) and the percent-free PSA (%fPSA) as knowledge, metabolomic analysis has already been used comparators to determine whether sarcosine has the for identifying metabolic markers in tumors.5–7 potential role in PCa diagnostics and prognostics. Correspondence: Dr X-D Yao, Department of Urology, Fudan Materials and methods University Shanghai Cancer Center, No. 270, Dongan Road; Xuhui District, Shanghai 200032, China. E-mail: [email protected] Specimen source, collection and processing Received 4 November 2010; revised 4 January 2011; accepted 6 This study was carried out according to the institutional January 2011; published online 15 February 2011 review board-approved study protocol. Written in- Efforts to solve controversy in sarcosine D-L Cao et al 167 Table 1 Clinicopathological characteristics of patients Characteristics PSA: o20 ng mlÀ1 PSA: not limited PCa (n ¼ 59) NEM (n ¼ 38) P-value PCa (n ¼ 71) NEM (n ¼ 39) P-value Age (year) 0.717a 0.614a Range 53–79 50–79 53–82 50–79 Mean±s.e. 68.14±0.70 67.68±1.10 68.21±0.69 67.59±1.07 Serum PSA (ng mlÀ1) 0.545b 0.079b Range 1.67–17.50 1.27–19.27 1.67–219.52 1.27–28.31 Mean±s.e. 7.57±0.44 7.40±0.60 14.90±3.26 7.94±0.80 %fPSA 0.000b 0.000b Range 2.69–30.60 3.68–39.75 1.76–30.60 3.68–39.75 Mean±s.e. 13.00±0.57 16.86±1.09 13.05±0.54 17.10±1.10 Prostate volume (cm3) 0.294b 0.415b Range 19.31–55.62 22.55–40.31 19.31–55.62 22.55–40.31 Mean±s.e. 31.07±0.78 29.82±0.72 31.00±0.70 29.84±0.70 Biopsy Gleason score PSAo4 PSAX4 — 1.000c PSAo4 PSAX4 — 1.000c p6 3 28 3 30 ¼ 7 2 22 2 28 X804 08 cT stage PSAo4 PSAX4 — 0.495c PSAo4 PSAX4 — 0.592c pcT2a 1 15 1 17 ¼ cT2b 4 25 4 33 XcT2c 0 14 0 16 Abbreviations: %fPSA, the percent ratio of free to total PSA; cT stage, clinical T stage; NEM, no evidence of malignancy; PCa, prostate cancer. aIndependent sample t-test. bMann–Whitney’s U-test. cFisher’s exact test was calculated with PCa patients classified as cases with PSAo4 and PSAX4. formed consent for each study participant was also Shimadzu LC-20AD UFLC system (Shimadzu, Kyoto, obtained. Between February and August 2010, a total of Japan) in conjunction with an 3200 QTrap mass spectro- 110 consecutive patients with PSA44ngmlÀ1 or abnor- metry (Applied Biosystems, Carlsbad, CA, USA) as mal digital rectal examination, out of which 71 patients previously described.18 Urinary creatinine concentra- with PCa and 39 patients with no evidence of malig- tions were measured by a standard assay on the Hitachi nancy (NEM), as confirmed by 10 core prostate biopsy 7020 analyzer (Hitachi, Tokyo, Japan). These results samples at Shanghai Cancer Center (Shanghai, China), obtained were then used to calculate four kinds of were enrolled. At the time of enrollment and at 1 week sarcosine algorithms (supernatant and sediment sarco- later, the first-void urines from these 110 patients were sine/creatinine, supernatant and sediment log2 (sarco- collected, respectively, after standardized digital rectal sine/alanine)). The expression levels of PSA mRNA and examination17 in about 5 min. The second-morning void PCA3 were determined as previously described.18 urines from 20 healthy men and women were also obtained. In addition, clinicopathological features of all patients investigated were recorded and presented Statistical analysis in Table 1. Statistical analyses were performed using the R software Following collection, 40–50 ml urine sample was cooled (The University of Auckland, Auckland, New Zealand) immediately on ice and centrifuged at 4 1C and at 700 g for and SPSS 17.0 (SPSS, Chicago, IL, USA). As only subjects 10minwithin1h.Uponcentrifugation, the first urinary with PSA o20 ng mlÀ1 were included in the study by sediment collected at the time of enrollment was mixed with Jentzmik et al.,9 patients in this study were divided into a TRIzol reagent (Invitrogen, Carlsbad, CA, USA) to measure subgroup of all patients and a subgroup of patients with PSA mRNA and PCA3; the second urinary sediment PSA o20 ng mlÀ1 to facilitate comparison. collected at 1 week later was added to 5 ml of 1 M boric Independent sample t-test or Mann–Whitney’s U-test acid to analyze sarcosine, and urinary supernatant was also was used to compare differences between two sets of collected to analyze sarcosine. After treatment, these samples continuous variables, and Fisher’s exact test for the were stored at À80 1C until analysis. analysis of n  n tables. Spearman’s or Pearson’s rank correlation and linear regression analysis were per- formed to determine the relationships between clinico- Determination of sarcosine, alanine, creatinine and other pathological features and any of sarcosine algorithms. analytes Logistic regression analysis was used to analyze correla- Sarcosine and alanine were derivatized and isolated tion between PCa diagnostic status and tested marker. using propyl chloroformate, and measured using a Diagnostic performance of investigated marker was Prostate Cancer and Prostatic Diseases Efforts to solve controversy in sarcosine D-L Cao et al 168 evaluated using the receiver operating characteristic above for the subgroup of all patients (data not shown). curve analysis, and the overfitting bias for the area Not only in the cohort of all patients but also in the under curve (AUC) calculations was estimated using cohort of patients with PSA o20 ng mlÀ1, there was no special bootstrap software. A two-tailed P-value o0.05 significant difference between supernatant sarcosine/ was considered statistically significant. creatinine and sediment sarcosine/creatinine in the subgroup of NEM patients, PCa patients, Gleason score o7 patients, Gleason scoreX7 patients, cT stage o2b Results patients or cT stageX2b patients (all P40.05); the same is true for the comparison between supernatant and As shown in Table 1, equalities regarding clinicopatho- sediment log2 (sarcosine/alanine) levels (all P40.05).
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