Deciphering metabolomic networks has been demonstrated to provide valuable information for diagnosing and monitoring diseases. Herein, we report a technique to monitor untargeted urine metabolites to evaluate prostate cancer aggressiveness and treatment outcome. Direct chemical profiling of urine was achieved by a combined procedure of hyphenating laser diode thermal desorption with atmospheric pressure chemical ionization mass spectrometry (LDTD-APCI-MS). We describe a conceptually new approach to monitoring preoperative urinary metabolic alterations associated with prostate cancer recurrence. By evaluating mass/charge (m/z) ratios and peak intensities of ions detected by mass spectroscopy of urine samples, we revealed that intensities at m/z 313.2740 (±0.0003) and 341.3054 (±0.0006) attributable to monoacylglycerol backbone fragments from glycerides can be statistically correlated to disease progression.