Plasma metabolomic profile in prostatic intraepithelial neoplasia and prostate cancer and associations with the prostate-specific antigen and the Gleason score.

INTRODUCTION: The metabolic alterations reflecting the influence of prostate cancer cells can be captured through metabolomic profiling. OBJECTIVE: To characterize the plasma metabolomic profile in prostatic intraepithelial neoplasia (PIN) and prostate cancer (PCa). METHODS: Metabolomics analyses were performed in plasma samples from individuals classified as non-cancerous control (n = 36), with PIN (n = 16), or PCa (n = 27). Untargeted [26 moieties identified after pre-processing by gas chromatography/mass spectrometry (GC/MS)] and targeted [46 amino acids, carbohydrates, organic acids and fatty acids by GC/MS, and 16 nucleosides and amino acids by ultra performance liquid chromatography-triple quadrupole/mass spectrometry (UPLC-TQ/MS)] analyses were performed. Prostate specific antigen (PSA) concentrations were measured in all samples. In PCa patients, the Gleason scores were determined. RESULTS: The metabolites that were best discriminated (p < 0.05, FDR < 0.2) for the Kruskal-Wallis test with Dunn's post-hoc comparing the control versus the PIN and PCa groups included isoleucine, serine, threonine, cysteine, sarcosine, glyceric acid, among several others. PIN was mainly characterized by alterations on steroidogenesis, glycine and serine metabolism, methionine metabolism and arachidonic acid metabolism, among others. In the case of PCa, the most predominant metabolic alterations were ubiquinone biosynthesis, catecholamine biosynthesis, thyroid hormone synthesis, porphyrin and purine metabolism. In addition, we identified metabolites that were correlated to the PSA [i.e. hypoxanthine (r = - 0.60, p < 0.05; r = - 0.54, p < 0.01) and uridine (r = - 0.58, p < 0.05; r = - 0.50, p < 0.01) in PIN and PCa groups, respectively] and metabolites that were significantly different in PCa patients with Gleason score < 7 and ≥ 7 [i.e. arachidonic acid, median (P25-P75) = 883.0 (619.8-956.4) versus 570.8 (505.6-651.8), respectively (p < 0.01)]. CONCLUSIONS: This human plasma metabolomic assessment contributes to the understanding of the unique metabolic features exhibited in PIN and PCa and provides a list of metabolites that can have the potential to be used as biomarkers for early detection of disease progression and management.

Plasma Sarcosine Measured by Gas Chromatography-Mass Spectrometry Distinguishes Prostatic Intraepithelial Neoplasia and Prostate Cancer from Benign Prostate Hyperplasia.

OBJECTIVE: Sarcosine was postulated in 2009 as a biomarker for prostate cancer (PCa). Here, we assess plasma sarcosine as a biomarker that is complementary to prostate-specific antigen (PSA). METHODS: Plasma sarcosine was measured using gas chromatography-mass spectrometry (GC-MS) in adults classified as noncancerous controls (with benign prostate hyperplasia [BPH], n = 36), with prostatic intraepithelial neoplasia (PIN, n = 16), or with PCa (n = 27). Diagnostic accuracy was assessed using receiver operating characteristic curve analysis. RESULTS: Plasma sarcosine levels were higher in the PCa (2.0 µM [1.3-3.3 µM], P <.01) and the PIN (1.9 µM [1.2-6.5 µM], P <.001) groups than in the BPH (0.9 µM [0.6-1.4 µM]) group. Plasma sarcosine had "good" and "very good" discriminative capability to detect PIN (area under the curve [AUC], 0.734) and PCa (AUC, 0.833) versus BPH, respectively. The use of PSA and sarcosine together improved the overall diagnostic accuracy to detect PIN and PCa versus BPH. CONCLUSION: Plasma sarcosine measured by GC-MS had "good" and "very good" classification performance for distinguishing PIN and PCa, respectively, relative to noncancerous patients diagnosed with BPH.