Citation:
Nirbhay S. Jain, Ulrich H. N. Dürr, Ayyalusamy Ramamoorthy. Bioanalytical methods for metabolomic profiling: Detection of head and neck cancer, including oral cancer[J]. Chinese Chemical Letters,
;2015, 26(4): 407-415.
doi:
10.1016/j.cclet.2015.03.001
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Metabolomics is an emerging field dealing with the measurement and interpretation of small molecular byproducts of biochemical processes, or metabolites, which can be used to generate profiles from biological samples. Promising for use in pathophysiology, metabolomic profiles give the immediate biological state of a sample. These profiles are altered in diseases and are detectable in biological samples, such as tissue, blood, urine, saliva, and others. Most remarkably, metabolic profiles usually are altered before symptoms appear in a patient. For this reason, metabolomics has potential as a reliable method for an early diagnosis of diseases through disease biomarker identification. This application is most prevalent in cancer, such as head and neck cancer (HNC). Metabolomic studies offer avenues to improve on current medical techniques through the application of mass spectrometry (MS), nuclear magnetic resonance spectroscopy (NMR), and statistical analysis to determine better biomarkers than those currently known. In this review, we discuss the use of MS and NMR tools for detecting biomarkers in tissue and fluid samples, and the appropriateness of metabolomics in analyzing cancer. Advantages, disadvantages, and recent studies on metabolomic profiling techniques in HNC analysis are also discussed herein.
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Keywords:
- Metabolomics,
- NMR,
- MS,
- Cancer,
- Biomarker discovery,
- Metabolites
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[1]
[1] B.S. Somashekar, A.G. Amin, P. Tripathi, et al., Metabolomic signatures in guinea pigs infected with epidemic associated W-Beijing strains of Mycobacterium tuberculosis, J. Proteome Res. 10 (2012) 4873-4884.
-
[2]
[2] B.S. Somashekar, A.G. Amin, C.D. Rithner, et al., Metabolic profiling of lung granuloma in Mycobacterium tuberculosis infected guinea pigs: ex vivo 1H magic angle spinning NMR studies, J. Proteome Res. 10 (2011) 4186-4195.
-
[3]
[3] A.P. Zhou, J.J. Ni, Z.H. Xu, et al., Application of 1H NMR spectroscopy-based metabolomics to sera of tuberculosis patients, J. Proteome Res. 12 (2013) 4642- 4649.
-
[4]
[4] A. Villaseñor, A. Ramamoorthy, M. Silva Dos Santos, et al., A pilot study of plasma metabolomic patterns from patients treated with ketamine for bipolar depression: evidence for a response-related difference in mitochondrial networks, Br. J. Pharmacol. 171 (2014) 2230-2242.
-
[5]
[5] M.P. Lorenzo, A. Villaseñor, A. Ramamoorthy, A. Garcia, Optimization and validation of a capillary electrophoresis laser-induced fluorescence method for amino acids determination in human plasma: application to bipolar disorder study, Electrophoresis 34 (2013) 1701-1709.
-
[6]
[6] M. Assflaq, I. Bertini, D. Colangiuli, et al., Evidence of different metabolic phenotypes in humans, Proc. Natl. Acad. Sci. U. S. A. 105 (2008) 1420-1424.
-
[7]
[7] P. Bernini, I. Bertini, C. Luchinat, et al., Individual human phenotypes in metabolic space and time, J. Proteome Res. 8 (2009) 4264-4271.
-
[8]
[8] C. Hafner, R. Kneuchel, L. Zanardo, et al., Evidence for oligoclonality and tumor spread by intraluminal seeding in multifocal urothelial carcinomas of the upper and lower urinary tract, Oncogene 20 (2001) 4910-4915.
-
[9]
[9] S. Krug, G. Kastenmüller, F. Stückler, et al., The dynamic range of the human metabolome revealed by challenges, FASEB J. 26 (2012) 2607-2619.
-
[10]
[10] M.J. Rist, C. Muhle-Goll, B. Görling, et al., Influence of freezing and storage procedure on human urine samples in NMR-based metabolomics, Metabolites 3 (2013) 243-258.
-
[11]
[11] D. Sidransky, Emerging molecular markers of cancer, Nat. Rev. Cancer 2 (2002) 210-219.
-
[12]
[12] C. Schmidt, Metabolomics takes its place as latest up-and-coming "omic" science, J. Nat. Cancer Inst. 96 (2004) 732-734.
-
[13]
[13] J.L. Griffin, J.P. Shockcor, Metabolic profiles of cancer cells, Nat. Rev. Cancer 4 (2004) 551-561.
-
[14]
[14] N.S. Nagaraj, Evolving ‘omics' technologies for diagnostics of head and neck cancer, Brief Funct. Genomics Proteomics 8 (2009) 49-59.
-
[15]
[15] E.E. Vokes, R.R. Weichselbaum, S.M. Lippman, W.K. Hong, Head and neck cancer, N. Engl. J. Med. 328 (1993) 184-194.
-
[16]
[16] Macmillan Cancer Support, Types of Head and Neck Cancer, 2015.
-
[17]
[17] American Cancer Society, Cancer Facts & Figures, 2014.
-
[18]
[18] S. Schmitz, J.P. Machiels, Molecular biology of squamous cell carcinoma of the head and neck: relevance and therapeutic implications, Expert Rev. Anticancer Ther. 10 (2010) 1471-1484.
-
[19]
[19] Head and neck cancer. http://www.cel-sci.com/head_and_neck_cancer.html.
-
[20]
[20] J.P. Pignon, A. le Maítre, E. Maillard, J. Bourhis, Meta-analysis of chemotherapy in head and neck cancer (MACH-NC): an update on 93 randomised trails and 17,346 patients, Radiother. Oncol. 92 (2009) 4-14.
-
[21]
[21] J. Bernier, S.M. Betnzen, J.B. Vermorken, Molecular therapy in head and neck oncology, Nat. Rev. Clin. Oncol. 6 (2009) 266-277.
-
[22]
[22] V.C. Sandaluche, T.J. Ow, C.R. Pickering, et al., Glucose, not glutamine, is the dominant energy source required for proliferation and survival of head and neck squamous carcinoma cells, Cancer 117 (2011) 2926-2938.
-
[23]
[23] T. Jiffar, T. Yilmaz, J. Lee, et al., KiSS1 mediates platinum sensitivity and metastasis suppression in head and neck squamous cell carcinoma, Oncogene 30 (2011) 3163-3173.
-
[24]
[24] S. Karahatay, K. Thomas, S. Koybasi, et al., Clinical relevance of ceramide metabolism in the pathogenesis of human head and neck squamous cell carcinoma (HNSCC): attentuation of C(18)-ceramide in HNSCC tumors correlates with lymphovascular invasion and nodal metastasis, Cancer Lett. 256 (2007) 101-111.
-
[25]
[25] T. Ziebart, S. Walenta, M. Kunkel, et al., Metabolic and proteomic differentials in head and neck squamous cell carcinomas and normal gingival tissue, J. Cancer Res. Clin. Oncol. 137 (2011) 193-199.
-
[26]
[26] Y.S. Kim, P. Maruvada, J.A. Milner, Metabolomics in biomarker discovery: future uses for cancer prevention, Future Oncol. 4 (2008) 93-102.
-
[27]
[27] C.B. Newgard, Finding mechanisms from metabolic signatures of diseases, BMC Proc. 6 (2012), O19.
-
[28]
[28] B.R. Konety, Molecular markers in bladder cancer: a critical appraisal, Urol. Oncol. 24 (2006) 326-337.
-
[29]
[29] A. Matta, R. Ralhan, L.V.W. De Souza, K.W. Michael Siu, Mass spectrometry-based clinical proteomics: head-and-neck cancer biomarkers and drug discovery, Mass. Spectrom. Rev. 29 (2010) 945-961.
-
[30]
[30] E.M. Reis, E.P. Ojopi, F.L. Alberto, et al., Large-scale transcriptome analyses reveal new genetic marker candidates of head, neck, and thyroid cancer, Cancer Res. 65 (2005) 1693-1699.
-
[31]
[31] J.Y. Engwegen, M.C.W. Gast, J.H.M. Schellens, J.H. Beijnen, Clinical proteomics: searching for better tumour markers with SELDI-TOF mass spectrometry, Trends. Pharmacol. Sci. 27 (2006) 251-259.
-
[32]
[32] J.T. Wadsworth, K.D. Somers, J. Stack, et al., Identification of patients with head and neck cancer using serum protein profiles, Arch. Otolaryngol. Head Neck Surg. 130 (2004) 98-104.
-
[33]
[33] E.P. Diamandis, Serum proteomic profiling by matrix-assisted laser desorptionionization time of flight mass spectrometry for cancer diagnosis: next steps, Cancer Res. 66 (2006) 5540-5541.
-
[34]
[34] E.P. Diamandis, Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems, J. Nat. Cancer Inst. 49 (2004) 353-356.
-
[35]
[35] W.C.S. Cho, Contribution of oncoproteomics to cancer biomarker discovery, Mol. Cancer 6 (2007) 6-25.
-
[36]
[36] A.A. Forastiere, Chemotherapy in the treatment of locally advanced head and neck cancer, J. Surg. Oncol. 97 (2008) 701-707.
-
[37]
[37] A. Forastiere, R. Weber, K. Ang, Treatment of head and neck cancer, N. Engl. J. Med. 358 (2008) 1076-1077.
-
[38]
[38] A.A. Forastiere, A. Trotti, D.G. Pfister, et al., Head and neck cancer: recent advances and new standards of care, J. Clin. Oncol. 24 (2006) 2603-2605.
-
[39]
[39] G. Graça, I.F. Duarte, B.J. Goodfellow, et al., Metabolite profiling of human amniotic fluid by hyphenated nuclear magnetic resonance spectroscopy, Anal. Chem. 80 (2008) 6085-6092.
-
[40]
[40] G. Graça, I.F. Duarte, B.J. Goodfellow, et al., Potential of NMR spectroscopy for the study of human amniotic fluid, Anal. Chem. 79 (2007) 8367-8375.
-
[41]
[41] J.C. Lindon, J.K. Nicholson, Spectroscopic and statistical techniques for information recovery in metabonomics and metabolomics, Annu. Rev. Anal. Chem. 1 (2008) 45-69.
-
[42]
[42] B. Sitter, T.F. Bathen, M.B. Tessem, I.S. Gribbestad, High-resolution magic angle spinning (HR MAS) MR spectroscopy in metabolic characterization of human cancer, Prog. Nucl. Magn. Reson. Spectrosc. 54 (2009) 239-254.
-
[43]
[43] T.J. Waybright, Q.N. Van, G.M. Muschik, et al., LC-MS in Metabonomics: optimization of Experimental Conditions for the Analysis of Metabolites in Human Urine, J. Liq. Chromatogr. Relat. Technol. 29 (2006) 2475-2497.
-
[44]
[44] M.P. Gonthier, L.Y. Rios, M.A. Verny, C. Rémésy, A. Scalbert, Novel liquid chromatography- electrospray ionization mass spectrometry method for the quantification in human urine of microbial aromatic acid metabolites derived from dietary polyphenols, J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 789 (2003) 247-255.
-
[45]
[45] E.J. Want, G. O'Maille, C.A. Smith, et al., Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry, Anal. Chem. 78 (2006) 743-752.
-
[46]
[46] A. Sreekumar, L.M. Poisson, T.M. Rajendiran, et al., Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression, Nature 457 (2009) 910-914.
-
[47]
[47] U. Theobald, W. Mailinger, M. Reuss, M. Rizzi, in vivo analysis of glucose-induced fast changes in yeast adenine nucleotide pool applying a rapid sampling technique, Anal. Biochem. 214 (1993) 31-37.
-
[48]
[48] R.P. Maharjan, T. Ferenci, Global metabolite analysis: the influence of extraction methodology on metabolome profiles of Escherichia coli, Anal. Biochem. 313 (2003) 145-154.
-
[49]
[49] G.A. Mills, V. Walker, Headspace solid-phase microextraction profiling of volatile compounds in urine: application to metabolic investigations, J. Chromatogr. B: Biomed. Sci. Appl. 753 (2001) 259-268.
-
[50]
[50] K. Dettmer, P.A. Aronov, B.D. Hammock, Mass spectrometry-based metabolomics, Mass Spectrom. Rev. 26 (2007) 51-78.
-
[51]
[51] I. Tkac, P.G. Henry, P. Andersen, et al., Highly resolved in vivo 1H NMR spectroscopy of the mouse brain at 9.4 T, Magn. Reson. Med. 52 (2004) 478-484.
-
[52]
[52] J.D. Xu, P.Z. Zhu, Z.H. Gan, et al., Natural-abundance 43Ca solid-state NMR spectroscopy of bone, J. Am. Chem. Soc. 132 (2010) 11504-11509.
-
[53]
[53] L. Da Silva, M. Godejohann, F.P. Martin, et al., High-resolution quantitative metabolome analysis of urine by automated flow injection NMR, Anal. Chem. 12 (2013) 5801-5809.
-
[54]
[54] N. MacKinnon, W. Ge, A.P. Khan, et al., Variable reference alignment: an improved peak alignment protocol for NMR spectral data with large intersample variation, Anal. Chem. 84 (2012) 5372-5379.
-
[55]
[55] T.L. James, Fundamentals of NMR (Chapter 1). https://www.biophysics.org/ Portals/1/PDFs/Education/james.pdf.
-
[56]
[56] R. Godelmann, F. Fang, E. Humpfer, et al., Targeted and nontargeted wine analysis by 1H-NMR spectroscopy combined with multivariate statistical analy-sis. Differentiation of important parameters: grape variety, geographical origin, year of vintage, J. Agric. Food. Chem. 61 (2013) 5610-5619.
-
[57]
[57] M. Spraul, B. Schütz, P. Rinke, et al., NMR-based multi parametric quality control of fruit juices: SGF profiling, Nutrients 1 (2009) 148-155.
-
[58]
[58] O. Beckonert, H.C. Keun, T.M. Ebbels, et al., Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts, Nat. Protoc. 2 (2007) 2692-2703.
-
[59]
[59] T. Fujiwara, A. Ramamoorthy, How far can the sensitivity of NMR be increased? Ann. Rep. NMR Spectrosc. 58 (2006) 155-175.
-
[60]
[60] E.J. Saude, C.M. Slupsky, B.D. Sykes, Optimization of NMR analysis of biological fluids for quantitative accuracy, Metabolomics 2 (2006) 113-123.
-
[61]
[61] D. Wu, A. Chen, C.S. Johnson, An improved diffusion-ordered spectroscopy experiment incorporating bipolar-gradient pulses, J. Magn. Reson. 115 (1995) 260-264.
-
[62]
[62] P. Sandusky, D. Raftery, Use of selective TOCSY NMR experiments for quantifying minor components in complex mixtures: application to the metabonomics of amino acids in honey, Anal. Chem. 77 (2005) 2455-2463.
-
[63]
[63] Y. Xi, J.S. de Ropp, M.R. Viant, D.L. Woodruff, P. Yu, Automated screening for metabolites in complex mixtures using 2D COSY NMR spectroscopy, Metabolomics 2 (2006) 221-233.
-
[64]
[64] G.A. Gowda, S. Zhang, H.W. Gu, et al., Metabolomics-based methods for early disease diagnostic: a review, Expert Rev. Mol. Diagn. 8 (2008) 617-633.
-
[65]
[65] O. Beckonert, M. Coen, H.C. Keun, et al., High-resolution magic-angle spinning NMR spectroscopy for metabolic profiling of intact tissues, Nat. Protoc. 5 (2010) 1019-1032.
-
[66]
[66] K.H. Mroue, R.C. Zhang, P.Z. Zhu, et al., Acceleration of natural-abundance solidstate MAS NMR measurements on bone by paramagnetic relaxation from gadolinium-DTPA, J. Magn. Reson. 244 (2014) 90-97.
-
[67]
[67] I.C. Smith, R. Baert, Medical diagnosis by high resolution NMR of human specimens, IUBMB Life 55 (2003) 273-277.
-
[68]
[68] A.L. Merz, N.J. Serkova, Use of nuclear magnetic resonance-based metabolomics in detecting drug resistance in cancer, Biomark. Med. 3 (2009) 289-306.
-
[69]
[69] H.J. Issaq, Q.N. Van, T.J. Waybright, G.M. Muschik, T.D. Veenstra, Analytical and statistical approaches to metabolomics research, J. Sep. Sci. 32 (2009) 2186-2199.
-
[70]
[70] M. Yuan, S.B. Breitkopf, X.M. Yang, J.M. Asara, A positive/negative ion-switching, targeted mass spectrometry-based metabolomics platform for bodily fluids, cells, and fresh and fixed tissue, Nat. Protoc. 7 (2012) 872-881.
-
[71]
[71] S.C. Brown, G. Kruppa, J.L. Dasseux, Metabolomics applications of FT-ICR mass spectrometry, Mass Spectrom. Rev. 24 (2005) 223-231.
-
[72]
[72] W.Y. Lu, M.F. Clasquin, E. Melamud, et al., Metabolomic analysis via reversedphase ion-pairing liquid chromatography coupled to a stand alone orbitrap mass spectrometer, Anal. Chem. 82 (2010) 3212-3221.
-
[73]
[73] J.H. Wang, T.T. Christison, K. Misuno, et al., Metabolomic profiling of anionic metabolites in head and neck cancer cells by capillary ion chromatography with orbitrap mass spectrometry, Anal. Chem. 86 (2014) 5116-5124.
-
[74]
[74] S. Ma, S.K. Chowdhury, K.B. Alton, Application of mass spectrometry for metabolite identification, Curr. Durg Metab. 7 (2006) 503-523.
-
[75]
[75] E.P. Diamandis, Mass spectrometry as a diagnostic and a cancer biomarker discovery tool: opportunities and potential limitations, Mol. Cell. Proteomics 3 (2004) 367-378.
-
[76]
[76] R.B. Cody, J.A. Laramée, H.D. Durst, Versatile new ion source for the analysis of materials in open air under ambient conditions, Anal. Chem. 77 (2005) 2297-2302.
-
[77]
[77] KnowItAll Enterprise Server. http://www.bio-rad.com/en-us/product/ spectroscopy-software/knowitall-enterprise-server.
-
[78]
[78] A. O'Sullivan, D. Avizonis, J.B. German, C.M. Slupsky, Software tools for NMR metabolomics, eMagRes (2011), http://dx.doi.org/10.1002/9780470034590. emrstm1232.
-
[79]
[79] M. Vinaixa, S. Samino, I. Saez, et al., A guideline to univariate statistical analysis for LC/MS-based untargeted metabolomics-derived data, Metabolites 2 (2012) 775-795.
-
[80]
[80] R.A. Johnson, D.W. Wichern, Applied Multivariate Statistical Analysis, Prentice Hall, 1999.
-
[81]
[81] M. Barker, W. Rayens, Partial least squares for discrimination, J. Chemom. 17 (2003) 166-173.
-
[82]
[82] B.M. Beckwith-Hall, J.T. Brindle, R.H. Barton, et al., Application of orthogonal signal correction to minimize the effects of physical and biological variation in high resolution 1H NMR spectra of biofluids, Analyst 127 (2002) 1283-1288.
-
[83]
[83] O. Cloarec, M.E. Dumas, A. Craig, et al., Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identification from metabolic 1H NMR data sets, Anal. Chem. 77 (2005) 1282-1289.
-
[84]
[84] D.J. Crockford, E. Holmes, J.C. Lindon, et al., Statistical heterospectroscopy, an approach to the integrated analysis of NMR and UPLC-MS data sets: application in metabonomic toxicology studies, Anal. Chem. 78 (2006) 363-371.
-
[85]
[85] H.W. Chen, Z.Z. Pan, N. Talaty, D. Raftery, R.G. Cooks, Combining desorption electrospray ionization mass spectrometry and nuclear magnetic resonance for differential metabolomics without sample preparation, Rapid Commun. Mass Spectrom. 20 (2006) 1577-1584.
-
[86]
[86] HMBD. http://www.hmdb.ca/.
-
[87]
[87] METAGENE. http://www.metabolomicssociety.org/databases.
-
[88]
[88] H. Horai, M. Arita, S. Kanaya, et al., MassBank: a public repository for sharing mass spectral data for life sciences, J. Mass Spectrom. 45 (2010) 703-714.
-
[89]
[89] E.L. Ulrich, H. Akutsu, J.F. Doreleijers, et al., BioMagResBank, Nucleic Acids Res. 36 (2008) 402-408.
-
[90]
[90] N. MacKinnon, B.S. Somashekar, P. Tripathi, MetaboID: a graphical user interface package for assignment of 1H NMR spectra of bodyfluids and tissues, J. Magn. Reson. 226 (2013) 93-99.
-
[91]
[91] AMIX. http://www.bruker.com/products/mr/nmr/nmr-software/software/ amix/overview.html.
-
[92]
[92] CHENOMX. http://www.chenomx.com/software/software.php?pageID=65.
-
[93]
[93] J.L. Griffin, R.A. Kauppinen, Tumour metabolomics in animal models of human cancer, J. Proteome. Res. 6 (2007) 498-505.
-
[94]
[94] D. Moka, R. Vorreuther, H. Schicha, et al., Biochemical classification of kidney carcinoma biopsy samples using magic-angle spinning 1H nuclear magnetic resonance spectroscopy, J. Pharm. Biomed. Anal. 17 (1998) 125-132.
-
[95]
[95] S. Srivastava, R. Roy, V. Gupta, et al., Proton HR-MAS MR spectroscopy of oral squamous cell carcinoma tissues: an ex vivo study to identify malignancy induced metabolic fingerprints, Metabolomics 7 (2011) 278-288.
-
[96]
[96] B.S. Somashekar, P. Kamarajan, T. Danciu, et al., Magic angle spinning NMRbased metabolic profiling of head and neck squamous cell carcinoma tissues, J. Proteome Res. 10 (2011) 5232-5241.
-
[97]
[97] T. Bezabeth, O. Odlum, R. Nason, et al., Prediction of treatment response in head and neck cancer by magnetic resonance spectroscopy, Am. J. Neuroadiol. 26 (2005) 2108-2113.
-
[98]
[98] A. Shukla-Dave, H. Poptani, L.A. Loevner, et al., Prediction of treatment response of head and neck cancers wtih P31 MR spectroscopy from pretreatment relative phosphomonoester levels, Acad. Radiol. 9 (2002) 688-694.
-
[99]
[99] S.K. Mukherji, S. Schiro, M. Castillo, et al., Proton MR spectroscopy of squamous cell carcinoma of the extracranial head and neck: in vitro and in vivo Studies, Am. J. Neuroadiol. 18 (1997) 1057-1072.
-
[100]
[100] L. Torregrossa, L. Shintu, J.N. Chandran, et al., Toward the reliable diagnosis of indeterminate thyroid lesions: a HRMAS NMR-based metabolomics case study, J. Proteome Res. 11 (2012) 3317-3325.
-
[101]
[101] P. Tripathi, P. Kamarajan, B.S. Somashekar, et al., Delineating metabolic signatures of head and neck squamous cell carcinoma: phospholipase A2, a potential therapeutic target, Int. J. Biochem. Cell. Biol. 44 (2012) 1852-1861.
-
[102]
[102] J.L. Zhou, B. Xu, J. Huang, et al., 1H NMR-based metabonomic and pattern recognition analysis for detection of oral squamous cell carcinoma, Clin. Chim. Acta 401 (2009) 8-13.
-
[103]
[103] S. Tiziani, V. Lopes, U.L. Günther, Early stage diagnosis of oral cancer using 1H NMR-based metabolomics, Neoplasia 11 (2009) 269-276.
-
[104]
[104] K. Yonezawa, S. Nishiumii, J. Kitamoto-Matsuda, et al., Serum and tissue metabolomics of head and neck cancer, Cancer Genomics Proteomics 10 (2013) 233-238.
-
[105]
[105] G.X. Xie, T.L. Chen, Y.P. Qui, et al., Urine metabolite profiling offers potential early diagnosis of oral cancer, Metabolomics 8 (2012) 220-231.
-
[106]
[106] S. Aygen, U. Dürr, P. Hegele, et al., NMR-based screening for inborn errors of metabolism: initial results from a study on Turkish neonates, JIMD Rep. 16 (2014) 101-111.
-
[107]
[107] J. Wei, G. Xie, Z. Zhou, et al., Salivary metabolite signatures of oral cancer and leukoplakia, Int. J. Cancer 129 (2011) 2207-2217.
-
[108]
[108] S.K. Yan, B.J. Wei, Z.Y. Lin, et al., A metabonomic approach to the diagnosis of oral squamous cell carcinoma, oral lichen planus, and oral leukoplakia, Oral Oncol. 44 (2008) 477-483.
-
[109]
[109] M. Sugimoto, D.T. Wong, A. Hirayama, T. Soga, M. Tomita, Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles, Metabolomics 6 (2010) 78-95.
-
[110]
[110] A. Aimetti, S. Cacciatore, A. Graziano, L. Tenori, Metabonomic analysis of saliva reveals generalized chronic periodontitis signature, Metabolomics 8 (2012) 465-474.
-
[111]
[111] S. Meier, M. Karlsson, P.R. Jensen, M.H. Lerche, J. Duus, Metabolic pathway visualization in living yeast by DNP-NMR, Mol. BioSyst. 7 (2011) 2834-2836.
-
[1]
-
-
-
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-
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[7]
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-
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