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 urinary bladder cancer (BC), we applied (1)H nuclear magnetic resonance (NMR) spectroscopy as a surrogate method for the identification of BC. This study includes 99 serum samples comprising low-grade (LG; n = 36) and high-grade (HG; n = 31) BC as well as healthy controls (HC; n = 32). (1)H 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 the initial samples (n = 99) data set. External validation was performed on a new batch of suspected BC patients (n = 106) through a double-blind study. Receiver operating characteristic (ROC) curve analysis was also performed. OPLS-DA-derived serum metabolomics (six biomarkers, ROC; 0.99) were able to discriminate 95% of BC cases with 96% sensitivity and 94% specificity when compared to HC. Likewise (three 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 the internal validation. (1)H NMR-based serum metabolic screening appears to be a promising and less invasive approach for probing and grading BC in contrast to the highly invasive and painful cystoscopic approach for BC detection.

Nuclear magnetic resonance spectroscopy as a new approach for improvement of early diagnosis and risk stratification of prostate cancer

“…NMR analytics have been used for biomarker detection in humans in several tumor entities other than PCa (Table 2): non-small-cell lung cancer (Doskocz et al, 2015), oral squamous cell carcinoma (OSCC) , gastric cancer (Jung et al, 2014), myeloma (Lodi et al, 2013), pancreatic ductal adenocarcinoma (Davis et al, 2013), lung cancer (Carrola et al, 2011), and BCa (Bansal et al, 2013).…”

“…One study on serum 1 H-NMR revealed good separation of low-and high-grade BCa from healthy controls (AUC 0.95, sensitivity 96% and specificity 94%) (Bansal et al, 2013). A panel of six metabolites (dimethylamine (DMA), malonate, lactate, glutamine, histidine, and valine) was derived from the orthogonal projection to latent structure discriminant analysis (OPLS-DA) model.…”

“…A panel of six metabolites (dimethylamine (DMA), malonate, lactate, glutamine, histidine, and valine) was derived from the orthogonal projection to latent structure discriminant analysis (OPLS-DA) model. Low-and high-grade BCa could be best separated (AUC 0.97) by using a panel of three metabolites (DMA, malonate, and lactate) (Bansal et al, 2013). Another 1 H-NMR study showed altered levels of citrate, DMA, taurine, phenylalanine, and hippurate in BCa compared to healthy controls in urine (Srivastava et al, 2010).…”

Lipid Metabolism Profiling and Bladder Cancer

“…While glycerophosphocholines, linoleic acid, oleic acid and arachidonic acid were demonstrated to be elevated in bladder cancer tissue, sphingomyelin was only found in normal bladder tissue (Table 1). In a study conducted by Bansal et al [14], serum metabolism profiling of 36 low grades BC and 32 high grades BC patients were compared with 32 healthy subjects using H-NMR analytical method. Malonate level was found significantly higher in patients with BC.…”

The Effect of Arvanil on Prostate Cancer Cells Studied by Whole Cell High Resolution Magic Angle Spinning NMR

“…These changes can be observed in the metabolite profiles by NMR or MS and metabolite biomarkers can be identified [1][2][3][4][5][6][7]. High-Resolution Magic Angle Spinning (HRMAS) NMR has been used to study prostate cancer tissues and cells with much successfulness since its introduction in the late 1990s [8][9][10][11][12].…”