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Urine metabolite profiling offers potential early diagnosis of oral cancer

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Abstract

Oral cancer is the sixth most common human cancer, with a high morbidity rate and an overall 5-year survival rate of less than 50%. It is often not diagnosed until it has reached an advanced stage. Therefore, an early diagnostic and stratification strategy is of great importance for oral cancer. In the current study, urine samples of patients with oral squamous cell carcinoma (OSCC, n = 37), oral leukoplakia (OLK, n = 32) and healthy subjects (n = 34) were analyzed by gas chromatography-mass spectrometry (GC–MS). Using multivariate statistical analysis, the urinary metabolite profiles of OSCC, OLK and healthy control samples can be clearly discriminated and a panel of differentially expressed metabolites was obtained. Metabolites, valine and 6-hydroxynicotic acid, in combination yielded an accuracy of 98.9%, sensitivity of 94.4%, specificity of 91.4%, and positive predictive value of 91.9% in distinguishing OSCC from the controls. The combination of three differential metabolites, 6-hydroxynicotic acid, cysteine, and tyrosine, was able to discriminate between OSCC and OLK with an accuracy of 92.7%, sensitivity of 85.0%, specificity of 89.7%, and positive predictive value of 91.9%. This study demonstrated that the metabolite markers derived from this urinary metabolite profiling approach may hold promise as a diagnostic tool for early stage OSCC and its differentiation from other oral conditions.

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Abbreviations

OSCC:

Oral squamous cell carcinoma

OLK:

Oral leukoplakia

GC–MS:

Gas chromatography–mass spectrometry

PCA:

Principal component analysis

OPLS-DA:

Orthogonal partial least squares-discriminant analysis

VIP:

Variable importance in the projection

ROC:

Receiver operating characteristic

LR:

Logistic regression

FDR:

False discovery rate

R2X:

Fraction of sum of squares (SS) of X explained by each component

R2Y:

Fraction of sum of squares (SS) of Y explained by each component

Q2cum:

The cumulative Q2 for the extracted components

V-plot:

Plot constructed with the VIP value versus p(corr) value of each metabolite

p(corr):

P scaled as correlation coefficient between X and T

t[2]O:

Score of the orthogonal component

t[1]P:

Score of the first non-orthogonal component

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Acknowledgments

This work was financially supported by the National Basic Research Program of China (2007CB914700), the National Science and Technology Major Project (2009ZX10005-020) and the National Science Foundation of China (20775048).

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Authors and Affiliations

  1. School of Pharmacy, Shanghai Jiao Tong University, Shanghai, 200240, People’s Republic of China

    Guo X. Xie, Xiao J. Zheng, Ming M. Su & Ai H. Zhao

  2. Department of Nutrition, The University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC, 28081, USA

    Guo X. Xie, Yun P. Qiu & Wei Jia

  3. Ministry of Education Key Laboratory of Systems Biomedicine, Shanghai Center for System Biomedicine and School of Pharmacy, Shanghai Jiao Tong University, Shanghai, 200240, China

    Tian L. Chen

  4. Department of Oral Mucosal Diseases, Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Stomatology, Shanghai, 200011, China

    Peng Shi & Zeng T. Zhou

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  1. Guo X. Xie
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  2. Tian L. Chen
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  3. Yun P. Qiu
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  4. Peng Shi
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  5. Xiao J. Zheng
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  6. Ming M. Su
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  7. Ai H. Zhao
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  8. Zeng T. Zhou
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  9. Wei Jia
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Correspondence to Zeng T. Zhou or Wei Jia.

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Xie, G.X., Chen, T.L., Qiu, Y.P. et al. Urine metabolite profiling offers potential early diagnosis of oral cancer. Metabolomics 8, 220–231 (2012). https://doi.org/10.1007/s11306-011-0302-7

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  • DOI: https://doi.org/10.1007/s11306-011-0302-7

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