Salivary metabolite signatures of oral cancer and leukoplakia

Oral cancer, one of the six most common human cancers with an overall 5‐year survival rate of <50%, is often not diagnosed until it has reached an advanced stage. The aim of the current study is to explore salivary metabolomics as a disease diagnostic and stratification tool for oral cancer and leukoplakia and evaluate the potential of salivary metabolome for detection of oral squamous cell carcinoma (OSCC). Saliva metabolite profiling for a group of 37 OSCC patients, 32 oral leukoplakia (OLK) patients and 34 healthy subjects was performed using ultraperformance liquid chromatography coupled with quadrupole/time‐of‐flight mass spectrometry in conjunction with multivariate statistical analysis. The OSCC, OLK and healthy control groups demonstrate characteristic salivary metabolic signatures. A panel of five salivary metabolites including γ‐aminobutyric acid, phenylalanine, valine, n‐eicosanoic acid and lactic acid were selected using OPLS‐DA model with S‐plot. The predictive power of each of the five salivary metabolites was evaluated by receiver operating characteristic curves for OSCC. Valine, lactic acid and phenylalanine in combination yielded satisfactory accuracy (0.89, 0.97), sensitivity (86.5% and 94.6%), specificity (82.4% and 84.4%) and positive predictive value (81.6% and 87.5%) in distinguishing OSCC from the controls or OLK, respectively. The utility of salivary metabolome diagnostics for oral cancer is successfully demonstrated in this study and these results suggest that metabolomics approach complements the clinical detection of OSCC and stratifies the two types of lesions, leading to an improved disease diagnosis and prognosis.

[1]  Tianlu Chen,et al.  Metabolic profiling reveals disorder of amino acid metabolism in four brain regions from a rat model of chronic unpredictable mild stress , 2008, FEBS letters.

[2]  F. Entschladen,et al.  The neurotransmitter gamma-aminobutyric acid is an inhibitory regulator for the migration of SW 480 colon carcinoma cells. , 2002, Cancer research.

[3]  T. Salo,et al.  Prognostic factors in tongue cancer – relative importance of demographic, clinical and histopathological factors , 2000, British Journal of Cancer.

[4]  H. Schuller,et al.  Gamma-aminobutyric acid, a potential tumor suppressor for small airway-derived lung adenocarcinoma , 2008, Carcinogenesis.

[5]  David Elashoff,et al.  Salivary Transcriptome Diagnostics for Oral Cancer Detection , 2004, Clinical Cancer Research.

[6]  Mark Stitt,et al.  From measurements of metabolites to metabolomics: an 'on the fly' perspective illustrated by recent studies of carbon-nitrogen interactions. , 2003, Current opinion in biotechnology.

[7]  W. Hong,et al.  Focus on head and neck cancer. , 2004, Cancer cell.

[8]  D. Wong,et al.  RNA Profiling of Cell-free Saliva Using Microarray Technology , 2004, Journal of dental research.

[9]  Stefano Tiziani,et al.  Early stage diagnosis of oral cancer using 1H NMR-based metabolomics. , 2009, Neoplasia.

[10]  R. Gillies,et al.  Why do cancers have high aerobic glycolysis? , 2004, Nature Reviews Cancer.

[11]  Yan Ni,et al.  Application of ultra-performance LC-TOF MS metabolite profiling techniques to the analysis of medicinal Panax herbs , 2008, Metabolomics.

[12]  J. Myers,et al.  Squamous cell carcinoma of the tongue in young adults: Increasing incidence and factors that predict treatment outcomes , 2000, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[13]  D. Fuchs,et al.  Serum phenylalanine concentrations in patients with ovarian carcinoma correlate with concentrations of immune activation markers and of isoprostane-8. , 2008, Cancer letters.

[14]  Liying Xiao,et al.  1H NMR-based metabonomic and pattern recognition analysis for detection of oral squamous cell carcinoma. , 2009, Clinica chimica acta; international journal of clinical chemistry.

[15]  David Elashoff,et al.  Salivary Proteomics for Oral Cancer Biomarker Discovery , 2008, Clinical Cancer Research.

[16]  U. Edlund,et al.  Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. , 2008, Analytical chemistry.

[17]  Dorothy D. Sears,et al.  Mechanisms of human insulin resistance and thiazolidinedione-mediated insulin sensitization , 2009, Proceedings of the National Academy of Sciences.

[18]  J. Cole,et al.  Dietary branched chain amino acids ameliorate injury-induced cognitive impairment , 2009, Proceedings of the National Academy of Sciences.

[19]  Julien Verrax,et al.  Targeting lactate-fueled respiration selectively kills hypoxic tumor cells in mice. , 2008, The Journal of clinical investigation.

[20]  J. Trygg,et al.  Evaluation of the orthogonal projection on latent structure model limitations caused by chemical shift variability and improved visualization of biomarker changes in 1H NMR spectroscopic metabonomic studies. , 2005, Analytical chemistry.

[21]  A. Bordey,et al.  GABA's control of stem and cancer cell proliferation in adult neural and peripheral niches. , 2009, Physiology.

[22]  I. Mustea,et al.  Modification de quelques acides aminés libres du sérum des malades cancéreux dans les conditions de l'influence exercée par la glucose sur le métabolisme tumoral , 1969 .

[23]  Zeng-Tong Zhou,et al.  A metabonomic approach to the diagnosis of oral squamous cell carcinoma, oral lichen planus and oral leukoplakia. , 2008, Oral oncology.

[24]  S. Wold,et al.  Orthogonal projections to latent structures (O‐PLS) , 2002 .

[25]  M. Navazesh,et al.  Methods for Collecting Saliva , 1993, Annals of the New York Academy of Sciences.

[26]  John D. Storey.  A direct approach to false discovery rates , 2002 .

[27]  Oliver Fiehn,et al.  Combining Genomics, Metabolome Analysis, and Biochemical Modelling to Understand Metabolic Networks , 2001, Comparative and functional genomics.

[28]  J. Lindon,et al.  'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. , 1999, Xenobiotica; the fate of foreign compounds in biological systems.

[29]  R. Nagler,et al.  Concomitant Analysis of Salivary Tumor Markers—A New Diagnostic Tool for Oral Cancer , 2006, Clinical Cancer Research.

[30]  M. Gibala.  Regulation of skeletal muscle amino acid metabolism during exercise. , 2001, International journal of sport nutrition and exercise metabolism.

[31]  M. Tomita,et al.  Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles , 2009, Metabolomics.

[32]  T. Toporcov,et al.  Fat food habitual intake and risk of oral cancer. , 2004, Oral oncology.

[33]  V. Baracos,et al.  Investigations of branched-chain amino acids and their metabolites in animal models of cancer. , 2006, The Journal of nutrition.

[34]  Joel B Epstein,et al.  Advances in the diagnosis of oral premalignant and malignant lesions. , 2002, Journal.

[35]  Tianlu Chen,et al.  Urinary metabonomic study on colorectal cancer. , 2010, Journal of proteome research.

[36]  Rachel Cavill,et al.  Metabolic profiling of human colorectal cancer using high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy and gas chromatography mass spectrometry (GC/MS). , 2009, Journal of proteome research.

[37]  David Elashoff,et al.  Serum circulating human mRNA profiling and its utility for oral cancer detection. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[38]  Tianlu Chen,et al.  Serum metabolite profiling of human colorectal cancer using GC-TOFMS and UPLC-QTOFMS. , 2009, Journal of proteome research.

[39]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[40]  C. Scully,et al.  Oral Medicine — Update for the dental practitioner Oral Cancer , 2005, British Dental Journal.

[41]  U. G. Dailey.  Cancer,Facts and Figures about. , 2022, Journal of the National Medical Association.

[42]  J. Jansson,et al.  Metabolomics Reveals Metabolic Biomarkers of Crohn's Disease , 2009, PloS one.

[43]  F. Entschladen,et al.  The Neurotransmitter γ-Aminobutyric Acid Is an Inhibitory Regulator for the Migration of SW 480 Colon Carcinoma Cells , 2002 .

[44]  D. Wong.  Towards a simple, saliva-based test for the detection of oral cancer. , 2006, Expert review of molecular diagnostics.

[45]  Yan Ni,et al.  Metabolic profiling using combined GC–MS and LC–MS provides a systems understanding of aristolochic acid‐induced nephrotoxicity in rat , 2007, FEBS letters.

[46]  W. Dunn,et al.  Measuring the metabolome: current analytical technologies. , 2005, The Analyst.

[47]  M. Latorre,et al.  Impact of comorbidity, symptoms, and patients' characteristics on the prognosis of oral carcinomas. , 2000, Archives of otolaryngology--head & neck surgery.