NMR-based metabolomics study of canine bladder cancer

Abstract

Bladder cancer is one of the leading lethal cancers worldwide. With the high risk of recurrence for bladder cancer following the initial diagnoses, lifelong monitoring of patients is necessary. The lack of adequate sensitivity and specificity of current noninvasive monitoring approaches including urine cytology, other urine tests, and imaging, underlines the importance of studies that focus on the detection of more reliable biomarkers for this cancer. The emerging area of metabolomics, which deals with the analysis of a large number of small molecules in a single step, promises immense potential for discovering metabolite markers for screening and monitoring treatment response and recurrence in patients with bladder cancer. Since naturally-occurring canine transitional cell carcinoma of the urinary bladder is very similar to human invasive bladder cancer, spontaneous canine transitional cell carcinoma has been applied as a relevant animal model of human invasive transitional cell carcinoma. In this study, we have focused on profiling the metabolites in urine from dogs with transitional cell carcinoma and healthy control dogs combining nuclear magnetic resonance spectroscopy and statistical analysis methods. (1)H NMR-based metabolite profiling analysis was shown to be an effective approach for differentiating samples from dogs with transitional cell carcinoma and healthy controls based on a partial least square-discriminant analysis of the NMR spectra. In addition, there were significant differences in the levels of six individual metabolites between samples from dogs with transitional cell carcinoma and the control group based on the Student's t-test. These metabolites were selected to build a separate partial least square-discriminant analysis model that was then used to test the classification accuracy. The result showed good classification between transitional cell carcinoma and control groups with the area under the receiver operating characteristic curve of 0.85. The sensitivity and specificity of the model were 86% and 78%, respectively. These results suggest that urine metabolic profiling may have potential for early detection of bladder cancer and of bladder cancer recurrence following treatment, and may enhance our understanding of the mechanisms involved.

Alteration of the fecal microbiota and serum metabolite profiles in dogs with idiopathic inflammatory bowel disease

“…14,15 Using mass spectrometry platforms, an untargeted metabolomics approach can identify hundreds of metabolites in biological samples simultaneously, and therefore provides a comprehensive functional overview of biochemical pathways that are being up-or downregulated during different physiologic or pathophysiologic state. 16 In veterinary medicine, only few studies have utilized this approach in clinical patients, 17,18 and to our knowledge, no studies using an untargeted metabolomics approach have been reported in dogs with IBD. Therefore, we aimed to characterize the fecal microbiota and serum metabolite profiles in healthy dogs and compare those to dogs with IBD.…”

The utility of metabolomics in natural product and biomarker characterization

“…Metabolomics enables analysis of a significant number of small molecules in one step, which presents vast potential for exploring marker compounds to monitor a treatment response and recurrence in patients suffering from bladder cancer [44]. Zhang et al,[44] profiled the metabolites in urine of dogs with transitional cell carcinoma (TCC) which was verified to be similar with human invasive bladder cancer [45] and control dogs utilizing NMR and statistical analysis methods. For the NMR approach, dog urine was stabilized with phosphate buffer to produce adequate 1 H NMR spectra and twenty-one metabolites were subsequently dereplicated by comparison of the acquired and reported NMR spectroscopic data.…”

Comparison of GC-MS and GC×GC-MS in the Analysis of Human Serum Samples for Biomarker Discovery

“…Frequently, biological samples are analyzed on both LC-MS and GC-MS platforms to achieve higher metabolite coverage, 1–3 while NMR is generally best suited to quantitatively measure the most abundant metabolites or for structure elucidation. 4,5 …”