Rapid Noninvasive Classification of Prostatic Disease Using Paper Spray Ionization Mass Spectrometry (PSI-MS)-Based...

Area of Science:

• Analytical Chemistry
• Biochemistry
• Oncology

Background:

• Accurate and rapid diagnosis of prostate health conditions is crucial for effective patient management.
• Current diagnostic methods can be invasive or lack specificity.
• Metabolomics offers a promising avenue for noninvasive disease detection through biomarker discovery.

Purpose of the Study:

• To employ paper spray ionization mass spectrometry (PSI-MS)-based nontargeted metabolomics for rapid classification of prostate health conditions.
• To identify unique metabolic signatures in urine associated with benign prostatic hyperplasia (BPH), prostatitis, and prostate cancer (PC).
• To evaluate the diagnostic accuracy of metabolomic profiles for distinguishing between healthy controls and different prostate conditions.

Main Methods:

• Urine samples from healthy volunteers and patients with BPH, prostatitis, and PC were analyzed using PSI-MS.
• Nontargeted metabolomics identified over 1000 distinct metabolic features.
• Multivariate analysis (PLS-DA, hierarchical clustering) and machine learning (random forest) were used for data interpretation.
• Receiver Operating Characteristic (ROC) analysis assessed predictive accuracy.

Main Results:

• Distinct metabolic profiles were observed among healthy controls and patients with BPH, prostatitis, and PC.
• Machine learning identified key discriminatory metabolic features.
• High predictive accuracy was achieved: BPH (AUC = 0.90), prostatitis (AUC = 0.75), and PC (AUC = 0.98).
• Condition-specific metabolic alterations were identified, including stress responses in BPH, infection markers in prostatitis, and metabolic reprogramming in PC.

Conclusions:

• PSI-MS-based nontargeted metabolomics is a rapid and noninvasive tool for prostate health assessment.
• Metabolomic signatures provide molecular insights into disease-specific alterations.
• This approach shows potential for clinical application in diagnosing and differentiating prostate conditions.