Low- and High-Grade Bladder Cancer Determination via Human Serum-Based Metabolomics Approach.
ABSTRACT To address the shortcomings of urine cytology and cystoscopy for probing and grading of urinary bladder cancer (BC), we applied 1H-nuclear magnetic resonance (NMR) spectroscopy as a surrogate method for identification of BC. This study includes 99 serum samples; comprising low-grade (LG, n=36) and high-grade (HG, n=31) of BC, and healthy controls (HC, n=32). 1H NMR-derived serum data were analyzed using orthogonal partial least-squares discriminant analysis (OPLS-DA). OPLS-DA-derived model validity was confirmed using an internal and external cross-validation. Internal validation was performed using initial samples (n=99) data set. External validation was performed on new batch of suspected BC patients (n=106) through double blind study. Receiver operating characteristic (ROC) curve analysis was also performed. OPLS-DA-derived serum metabolomics (6 biomarkers, ROC; 0.99) were able to discriminate 95% of BC cases with 96% sensitivity and 94% specificity when compared to HC. Likewise (3 biomarkers, ROC; 0.99), 98% of cases of LG were able to differentiate from HG with 97% sensitivity and 99% specificity. External validation reveals comparable results to internal validation. 1H NMR-based serum metabolic screening appears to be a promising and least-invasive approach for probing and grading of BC in contrast to the highly invasive and painful cystoscopic approach of BC detection.