This work contributes to fill in some existing gaps in the knowledge of human plasma degradability during handling and storage, a paramount issue in Nuclear Magnetic Resonance (NMR) metabolomics. Regarding the comparison between heparin and EDTA anti-coagulant collection tubes, the former showed no interference of the polysaccharide, while conserving full spectral information. In relation to time/temperature conditions, room temperature was seen to have a large impact on lipoproteins and choline compounds from 2.5 hours. In addition, short-term storage at −20 °C was found suitable up to 7 days but, for periods up to 1 month, −80 °C was recommended. Furthermore, in the case of reusing plasma samples, no more than 3 consecutive freeze–thaw cycles were found advisable. Finally, the impact of long-term −80 °C storage (up to 2.5 years) was found almost negligible, as evaluated on a partially matched non-fasting cohort (n = 49), after having investigated the possible confounding nature of the particular non-fasting conditions employed.

Background: The lack of sensitive and specific biomarkers for the early detection of prostate cancer (PCa) is a major hurdle to improve patient management. Methods: A metabolomics approach based on GC-MS was used to investigate the performance of volatile organic compounds (VOCs) in general and, more specifically, volatile carbonyl compounds (VCCs) present in urine as potential markers for PCa detection. Results: Results showed that PCa patients (n = 40) can be differentiated from cancer-free subjects (n = 42) based on their urinary volatile profile in both VOCs and VCCs models, unveiling significant differences in the levels of several metabolites. The models constructed were further validated using an external validation set (n = 18 PCa and n = 18 controls) to evaluate sensitivity, specificity and accuracy of the urinary volatile profile to discriminate PCa from controls. The VOCs model disclosed 78% sensitivity, 94% specificity and 86% accuracy, whereas the VCCs model achieved the same sensitivity, a specificity of 100% and an accuracy of 89%. Our findings unveil a panel of 6 volatile compounds significantly altered in PCa patients’ urine samples that was able to identify PCa, with a sensitivity of 89%, specificity of 83%, and accuracy of 86%. Conclusions: It is disclosed a biomarker panel with potential to be used as a non-invasive diagnostic tool for PCa.