Purpose: To compare the levels of metabolites in the urine samples of chronic prostatitis patients with that of PCa and HC by using ¹H NMR spectroscopy. Introduction: Prostate cancer (PCa) is the second most common malignancy in men older than 50 years and it is fifth cause of mortality among the elderly men worldwide. Diagnosis of PCa is challenging due to limitation in both the sensitivity and the specificity using conventional methods like digital rectum examination (DRE), prostate specific antigen (PSA) test and trans-rectal ultrasound (TRUS). Further, it is difficult to differentiate PCa from chronic prostatitis (PT), as PSA shows an increase in both the cases. In this direction, NMR metabolomic provides both the identification and the quantification of metabolites and their concentration and thus may help identification of biomarkers in a non-invasive way with high specificity. This study aims to investigate the NMR metabolomics of urine samples of PT patients and compare it with patients suffering from PCa and HC.

Methods: Pre-prandial urine samples of normal volunteer (HC; n=12; Age = 30.5 ± 2.72 yrs), patients with chronic prostatitis (PT; n=17; Age = 64 ± 11 yrs; PSA= 6.57 ± 3.81 ng/mL) and PCa (n=20; Age = 69.68 ± 9.6 yrs; PSA= 29.58 ± 31.86 ng/mL) were collected in a sterile vial followed by immediate freezing below -20˚C. The ¹H NMR experiments of urine samples was carried out at 400 MHz (Bruker, Switzerland) by using solvent suppression sequence namely exciting sculpting. Typical 1D ¹H NMR acquisition parameters used were: spectral width 16 ppm, relaxation delay 5 s, number of transients 128 with 32K data points at 25 ̊C. Two-dimensional (2D) total correlation spectroscopy (TOCSY) was carried out with the following parameters: data points = 2K, spectral width = 11 ppm, relaxation delay = 1 s, 256 number of experiments (time-domain points) in t1 dimension using a number of scans = 16 with an 90 ms mixing time. NMR spectra were processed by using Topspin and Amix software. For referencing the chemical shifts, 5 mM of trimethylsilyl propanoic acid (TSP) was added. Statistical analysis was performed by using Metaboanalyst (v3.0). Principal component analysis (PCA), multivariate (partial least squares–discriminant analysis (PLS-DA) and Orthogonal projections to latent structures–discriminant analysis (OPLS-DA) were employed for analysis of urine samples of PCa patients, PT and HC for better discrimination. Institute ethics committee approved the study and informed consent was obtained from all individuals.

Results: Figure 1 shows the stack plot of the aliphatic region of ¹H NMR spectra of urine samples from (A) PCa, (B) PT, and (C) HC. Assignment of metabolites was carried out by using 1D and 2D NMR experiments and also based on previous literature data and databases. A total of 12 metabolites were uniquely identified in PCa, 13 metabolites in PT and in HC. The following metabolites isoleucine, leucine, valine, lactate, alanine, glutamine, glycine, hippurate, citrate, dimethyl amine, dimethylglycine, and creatine were common in all the three categories of subjects studied, while in 7/17 PT patients who were on acetaminophen treatment showed resonances due to acetaminophen and its derivatives. Figure 2 shows (A) OPLS-DA model-based discriminatory analysis that shows distinction between three groups and (B) the VIP score.

Discussion: The key observation is the significantly reduced concentration of citrate and creatine in PCa compared to patients with chronic prostatitis (PT) and HC that are closely linked to the biochemical changes associated with the zinc levels^1-3. The urine metabolites such as creatine, glycine and urea have high VIP score facilitating differentiation of PCa from PT and HC. PLS-DA score plot indicated the separation between PCa from prostatitis and HC. Conclusions: This pilot study showed that it is possible to use NMR metabolomics for differentiating HC and patients with PCa from chronic prostatitis (PT) patients.

Conclusion: This pilot study showed that it is possible to use NMR metabolomics for differentiating HC and patients with PCa from chronic prostatitis (PT) patients.

Acknowledgements

NRJ acknowledge the Science and Engineering Research Board, Department of Science and Technology, Government of India for the award of J. C. Bose Fellowship. We also acknowledge the use of 400 MHz NMR facility available at the CSIR- Central Leather Research Institute, Chennai.

References

(1). Pérez RC, Puchades CL, García FM et al. Metabolomics. 2017;13:52; (2). Struck-Lewicka W, Kordalewska M, Bujak R et al. J Pharm Biomed Anal. 2015;111:351-361; (3) Dereziński P, Klupczynska A, Sawicki W et al. Int J Med Sci. 2017;14:1-122.