Urine metabolite profiling offers potential early diagnosis of oral cancer

Xie, Guo X.; Chen, Tian L.; Qiu, Yunping; Peng, Shi; Zheng, Xiao J.; Ming, Su; Zhao, Ai; Zhou, Zubin; Wang, Jia

doi:10.1007/s11306-011-0302-7

Cited by 54 publications

(31 citation statements)

References 32 publications

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“…Urinary metabolomics has been shown to be a powerful screening approach to separate diseased individuals from controls, e.g. in Barrett's oesophagus and oesophageal carcinoma 30, or in separating oral squamous cell carcinomas from oral leukoplakia patients and control groups 31. However, neither of those studies included a separate validation cohort, leaving open the possibility of co-incidence in the models generated.…”

Section: Discussionmentioning

confidence: 99%

Early Diagnosis of Brain Metastases Using a Biofluids-Metabolomics Approach in Mice

et al. 2016

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Over 20% of cancer patients will develop brain metastases. Prognosis is currently extremely poor, largely owing to late-stage diagnosis. We hypothesized that biofluid metabolomics could detect tumours at the micrometastatic stage, prior to the current clinical gold-standard of blood-brain barrier breakdown.Metastatic mammary carcinoma cells (4T1-GFP) were injected into BALB/c mice via intracerebral, intracardiac or intravenous routes to induce differing cerebral and systemic tumour burdens. B16F10 melanoma and MDA231BR-GFP human breast carcinoma cells were used for additional modelling. Urine metabolite composition was analysed by 1H NMR spectroscopy. Statistical pattern recognition and modelling was applied to identify differences or commonalities indicative of brain metastasis burden.Significant metabolic profile separations were found between control cohorts and animals with tumour burdens at all time-points for the intracerebral 4T1-GFP time-course. Models became stronger, with higher sensitivity and specificity, as the time-course progressed indicating a more severe tumour burden. Sensitivity and specificity for predicting a blinded testing set were 0.89 and 0.82, respectively, at day 5, both rising to 1.00 at day 35. Significant separations were also found between control and all 4T1-GFP injected mice irrespective of route. Likewise, significant separations were observed in B16F10 and MDA231BR-GFP cell line models. Metabolites underpinning each separation were identified. These findings demonstrate that brain metastases can be diagnosed in an animal model based on urinary metabolomics from micrometastatic stages. Furthermore, it is possible to separate differing systemic and CNS tumour burdens, suggesting a metabolite fingerprint specific to brain metastasis. This method has strong potential for clinical translation.

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Section: Discussionmentioning

confidence: 99%

Early Diagnosis of Brain Metastases Using a Biofluids-Metabolomics Approach in Mice

et al. 2016

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“…From patient urine samples, Xie and colleagues identified a panel of differentially expressed metabolites and demonstrated their utility by logistic regression (LR) modeling (Xie et al, 2012; Table 1). When two metabolites, valine and 6-hydroxynicotic acid, were inputted together in the LR prediction model,the authors were able to identify OSCC with a 98.9% accuracy, and a greater than 90% sensitivity, specificity and positive predictive value (Xie et al, 2012). However, similar to saliva and blood metabolomics, the use of urine samples for HNC metabolomics will require further validation through more independent studies.…”

Section: Introductionmentioning

confidence: 99%

Metabolomics of Head and Neck Cancer: A Mini-Review

et al. 2016

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Metabolomics is used in systems biology to enhance the understanding of complex disease processes, such as cancer. Head and neck cancer (HNC) is an epithelial malignancy that arises in the upper aerodigestive tract and affects more than half a million people worldwide each year. Recently, significant effort has focused on integrating multiple “omics” technologies for oncological research. In particular, research has been focused on identifying tumor-specific metabolite profiles using different sample types (biological fluids, cells and tissues) and a variety of metabolomic platforms and technologies. With our current understanding of molecular abnormalities of HNC, the addition of metabolomic studies will enhance our knowledge of the pathogenesis of this disease and potentially aid in the development of novel strategies to prevent and treat HNC. In this review, we summarize the proposed hypotheses and conclusions from publications that reported findings on the metabolomics of HNC. In addition, we address the potential influence of host-microbe metabolomics in cancer. From a systems biology perspective, the integrative use of genomics, transcriptomics and proteomics will be extremely important for future translational metabolomic-based research discoveries.

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“…These results suggest that metabolomics approach may complement with the clinical detection of OSCC. 32,33 In this study, we have demonstrated a highly efficient Cap IC-MS method for untargeted metabolomics analysis of head and neck cancer cells and stem-like cancer cells. By comparing the metabolomics profiles of oral stem-like cancer cells (CSCs) to nonstem cancer cells (NSCCs), we found the CSCs have a distinct metabolic phenotype from NSCCs.…”

mentioning

confidence: 99%

Metabolomic Profiling of Anionic Metabolites in Head and Neck Cancer Cells by Capillary Ion Chromatography with Orbitrap Mass Spectrometry

et al. 2014

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A highly sensitive platform coupling capillary ion chromatography (Cap IC) with Q Exactive mass spectrometer has been developed for metabolic profiling of head and neck squamous cell carcinoma (HNSCC) cells. The Cap IC allowed an excellent separation of anionic polar metabolites, and the sensitivities increased by up to 100-fold compared to reversed-phase liquid chromatography and hydrophilic interaction chromatography performed at either high- or capillary-flow rates. The detection limits for a panel of standard metabolites were between 0.04 to 0.5 nmol/L (0.2 to 3.4 fmol) at a signal-to-noise ratio of 3. This platform was applied to an untargeted metabolomic analysis of head and neck cancer cells and stem-like cancer cells. Differential metabolomics analysis identified significant changes in energy metabolism pathways (e.g., glycolysis and tricarboxylic acid cycle). These experiments demonstrate Cap IC/MS as a powerful metabolomics tool by providing enhanced separation and sensitivity of polar metabolites combined with high resolution and accurate mass measurement (HR/AM) capabilities to differentiate isobaric metabolites.

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Urine metabolite profiling offers potential early diagnosis of oral cancer

Cited by 54 publications

References 32 publications

Early Diagnosis of Brain Metastases Using a Biofluids-Metabolomics Approach in Mice

Early Diagnosis of Brain Metastases Using a Biofluids-Metabolomics Approach in Mice

Metabolomics of Head and Neck Cancer: A Mini-Review

Metabolomic Profiling of Anionic Metabolites in Head and Neck Cancer Cells by Capillary Ion Chromatography with Orbitrap Mass Spectrometry

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