Background: In clinical care of prostate cancer patients, an improved method to assess the risk of recurrence after surgical treatment is urgently needed. We aim to retrospectively evaluate the ability of ex vivo tissue magnetic-resonance-spectroscopy-based metabolomic profiles to estimate the risk of recurrence.
Methods: PCa recurrence is defined biochemically as the detection of serum PSA after radical prostatectomy. Sixteen consecutive PCa-recurrent cases, those with an initial PSA increase of 0.69 +/- 0.26 ng/ml monitored 47.7 +/- 2.6 months after prostatectomy were paired by age and Gleason score with cases without recurrence of the same pathological and clinical stages (n = 16/each). We analyzed ex vivo intact-tissue spectroscopy results from these 48 individuals at the time of prostatectomy at 14T. From these spectra, we identified the 27 most common and intense spectral metabolic regions for statistical analyses.
Results: Principal component analysis (PCA) on these spectral regions from cases of clinical-stage-matched groups with and without recurrence identified four pathology-related principal components. Canonical analysis of these four and the first nine principal components for cases in the two groups defined metabolomic profiles as the canonical score that can differentiate the two groups with statistical significance. By applying the coefficients from PCA and canonical analysis to the pathological-stage-matched groups, recurrence was predicted with an accuracy of 78%.
Conclusions: Results indicate the potential of tissue metabolomic profiles measured with ex vivo spectroscopy to identify PCa aggressiveness in terms of cancer recurrence. With further study, this may greatly contribute to the future design of clinical strategy for personalized treatment of PCa patients.