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. 2017;13(5):52.
doi: 10.1007/s11306-017-1194-y. Epub 2017 Mar 9.

Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia

Clara Pérez-Rambla #  1 , Leonor Puchades-Carrasco #  1 , María García-Flores  2 , José Rubio-Briones  3 , José Antonio López-Guerrero  2 , Antonio Pineda-Lucena  1   4
Affiliations

Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia

Clara Pérez-Rambla et al. Metabolomics. 2017.

Abstract

Introduction: Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results.

Objectives: In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH.

Methods: Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using 1H nuclear magnetic resonance (1H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches.

Results: The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH.

Conclusion: PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.

Keywords: Benign prostatic hyperplasia; Biomarkers; Metabolomics; Nuclear magnetic resonance; Prostate cancer.

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Conflict of interest statement

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the Declaration of Helsinki and applicable local regulatory requirements and laws and after approval from the Ethics Committee of the Instituto Valenciano de Oncología.

Ethical requirements

The manuscript is in compliance with ethical requirement of the journal.

Informed consent

Written informed consent was obtained from each participant before being included in this study.

Figures

Fig. 1
Fig. 1
General scheme of the data modeling and statistical analysis procedures with the main steps highlighted (n number of samples, k number of variables)
Fig. 2
Fig. 2
Representative 500 MHz 1H-NMR spectrum and assignment of a urine sample from a PCa patient. Assigned metabolites: 1 branched-chain amino acids; 2 3-hydroxyisovalerate; 3 lactate; 4 2-hydroxyisobutyrate; 5 alanine; 6 acetate; 7 N-acetyl groups; 8 glutamate; 9 2-hydroxy-glutarate; 10 pyruvate; 11 citrate; 12 dimethylamine; 13 sarcosine; 14 dimethylglycine; 15 creatinine; 16 cis-aconitic acid; 17 trimethylamine-N-oxide; 18 methanol; 19 trans-aconitic acid; 20 taurine; 21 glycine; 22 serine; 23 hippurate; 24 pseudouridine; 25 threonine; 26 dihydroxyacetone; 27 trigonelline; 28 U1; 29 fumarate; 30 2-furoylglycine; 31 4-hydroxybenzoate; 32 3-methylhistidine; 33 phenylalanine; 34 histidine; 35 hypoxanthine; 36 formate; 37 4-imidazole-acetate
Fig. 3
Fig. 3
Multivariate modelling resulting from the analysis of urine 1H-NMR spectra before variable selection (823 variables). a OPLS-DA score plot for the comparison between PCa patients (red circle) vs. individuals diagnosed with BPH (blue circle); b internal validation of the corresponding OPLS-DA model by permutation analysis (n = 100), R2 (green diamond), Q2 (blue square)
Fig. 4
Fig. 4
Multivariate modelling resulting from the analysis of urine 1H-NMR spectra after variable selection (108 variables). a OPLS-DA score plot for the comparison between PCa patients (red circle) vs. individuals diagnosed with BPH (blue circle); b internal validation of the corresponding OPLS-DA model by permutation analysis (n = 100), R2 (green diamond), Q2 (blue square)
See this image and copyright information in PMC

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