Abstract
Our group recently developed a urinary 6-biomarker panel for the diagnosis of prostate cancer (PCa) which has a higher level of accuracy compared to the serum prostate specific antigen (PSA) test. Herein, urine from an independent cohort of PCa patients and cancer-free controls was analyzed to further validate the discriminative power of that panel. Additionally, urine from patients diagnosed with bladder cancer (BC) and renal cancer (RC) were included to evaluate the site-specificity of the panel. Results confirmed the ability of the 6-biomarker panel to discriminate PCa patients from controls, but not from other urological cancers. To overcome this limitation, an untargeted approach was performed to unveil discriminant metabolites among the three cancer types. A 10-biomarker panel comprising the original panel plus four new metabolites was established to discriminate PCa from controls, BC, and RC, with 76% sensitivity, 90% specificity, and 92% accuracy. This improved panel also disclosed better accuracy than serum PSA test and provides the basis for a new non-invasive early detection tool for PCa.
Highlights
Prostate cancer (PCa) ranks first amongst all male urological cancers and second in incidence of all cancers in men [1]
The classification model confirmed that this 6-biomarker panel was able to discriminate prostate cancer (PCa) from controls (Figure S1A), as validated by permutation tests (Figure S2A), with 84% sensitivity, 80% specificity, 82% accuracy, and an area under the curve (AUC) of
The major novelty of this study design was the inclusion of patients with other urological cancers to evaluate the performance of the biomarker panel to discriminate PCa vs. cancer-free individuals, and PCa vs. bladder cancer (BC) and renal cancer (RC) (2nd and 3rd most common urological cancers in males, respectively) [18]
Summary
Prostate cancer (PCa) ranks first amongst all male urological cancers and second in incidence of all cancers in men [1]. The standard serum PSA cut-off of 4 ng/mL has failed to meet the criteria required for an effective biomarker due to its limited sensitivity (20.5%), specificity (51–91%) [5,6], area under the curve (AUC) (0.53–0.83), and accuracy (62–75%) [7]. Based on these limitations, several research groups have proposed new candidate biomarkers for PCa detection (e.g., prostate cancer antigen 3 (PCA3) and prostate health index (PHI)) [8,9,10]. The definition of the ideal cut-off for this biomarker remains controversial [8]
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