Metabonomic signature analysis of cervical carcinoma and precancerous lesions in women by 1H NMR spectroscopy

Hasim,Ayshamgul; Ali,Mayinuer; Mamtimin,Batur; Ma,Jun‑Qi; Li,Qiao-Zhi; Abudula,Abulizi

doi:10.3892/etm.2012.509

Metabonomic signature analysis of cervical carcinoma and precancerous lesions in women by 1H NMR spectroscopy

Authors:
- Ayshamgul Hasim
- Mayinuer Ali
- Batur Mamtimin
- Jun‑Qi Ma
- Qiao-Zhi Li
- Abulizi Abudula
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Affiliations: Department of Pathology, College of Basic Medicine, Medical University of Xinjiang, Urumqi, P.R. China, Department of Oncology, The First Affiliated Hospital, Medical University of Xinjiang, Urumqi, P.R. China, Centers of Pharmaceutical Analysis, College of Pharmacy, Medical University of Xinjiang, Urumqi, P.R. China, Department of Gynecology, The First Affiliated Hospital, Medical University of Xinjiang, Urumqi, P.R. China, Key Laboratories of Molecular Biology and Endemic Diseases, Medical University of Xinjiang, Urumqi, P.R. China
Published online on: March 12, 2012 https://doi.org/10.3892/etm.2012.509
Pages: 945-951

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Abstract

1H nuclear magnetic resonance (NMR)-based metabonomics has been used to characterize the metabolic profiles of cervical intraepithelial neoplasia (CIN) and cervical squamous cell carcinoma (CSCC). Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were used to model the systematic variation related to patients with CIN or CSCC with healthy controls. Potential metabolic biomarkers were identified using database comparisons, and the one‑way analysis of variance (ANOVA) test was used to examine the significance of the metabolites. Compared with plasma obtained from the healthy controls, plasma from patients with CIN had higher levels of very-low density lipoprotein (VLDL), acetone, unsaturated lipid and carnitine, together with lower levels of creatine, lactate, isoleucine, leucine, valine, alanine, glutamine, histidine, glycine, acetylcysteine, myo-inositol, choline and glycoprotein. Plasma from patients with CSCC had higher levels of acetate and formate, together with lower levels of creatine, lactate, isoleucine, leucine, valine, alanine, glutamine, histidine and tyrosine compared with the plasma of the healthy controls. In addition, compared with the plasma of patients with CIN, the plasma of CSCC patients had higher levels of acetate, formate, lactate, isoleucine, leucine, valine, alanine, glutamine, histidine, tyrosine, acetylcysteine, myo‑inositol, glycoprotein, α-glucose and β-glucose, together with lower levels of acetone, unsaturated lipid and carnitine. Moreover, the profiles showed high feasibility and specificity by statistical analysis with OPLS-DA compared to the Thinprep cytology test (TCT) by setting the histopathological outcome as standard. The metabolic profile obtained for cervical cancer is significant, even for the precancerous disease. This suggests a systemic metabolic response to cancer, which may be used to identify potential early diagnostic biomarkers of the cancer and to establish clinical diagnostic methods.

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1.	Parkin DM, Whelan SL, Ferlay J, Teppo L and Thomas DB: Cancer Incidence in Five Continents. 8. International Agency for Research on Cancer Scientific Publications; Lyon: 2002
2.	Yang B, Bray F, Parkin D, Sellors J and Zhang Z: Cervical cancer as a priority for prevention in different world regions: an evaluation using years of life lost. Int J Cancer. 109:418–424. 2004.PubMed/NCBI
3.	Suzuke Lalai, Peng YH, Zhou K, Fang X and Wang L: Analysis of the cervical cancer distribution in Xinjiang. J Xinjiang Med Univ. 29:569–571. 2006.(In Chinese).
4.	Ma D and Ling XI: Advances in the epidemiology and etiology of cervical cancer. J Practical Obstet Gynecol. 17:61–63. 2001.(In Chinese).
5.	Abulafia O, Pezzullo JC and Sherer DM: Perfomance of Thinprep liquid-based cervical cytology in comparison with conventionally prepared Papaniclaou smears: a quantitative survey. Gynecol Oncol. 90:137–144. 2003. View Article : Google Scholar : PubMed/NCBI
6.	Monsonego J, Autillo-Touati A, Bergeron C, Dachez R, Liaras J, Saurel J, Zerat L, Chatelain P and Mottot C: Liquid-based cytology for primary cervical cancer screening: a multi-centre study. Br J Cancer. 84:360–366. 2001. View Article : Google Scholar : PubMed/NCBI
7.	Waters NJ, Waterfield CJ, Farrant RD, Holmes E and Nicholson JK: Integrated metabonomic analysis of bromobenzene-induced novel hepatic 5-oxoprolinosis. J Proteome Res. 5:1448–1459. 2006. View Article : Google Scholar : PubMed/NCBI
8.	Nicholson JK, Foxall PJ, Spraul M, Farrant RD and Lindon JC: 750 MHz 1H and 1H-13C NMR spectroscopy of human blood plasma. Anal Chem. 67:793–811. 1995. View Article : Google Scholar : PubMed/NCBI
9.	Parvizi J: Metabolomics: key to understanding human individuality. J Bone Joint Surg Am. 93:1–3. 2011.
10.	Odunsi K, Wollman RM, Ambrosone CB, Hutson A, McCann SE, Tammela J, Geisler JP, Miller G, Sellers T, Cliby W, et al: Detection of epithelial ovarian cancer using 1H-NMR-based metabonomics. Int J Cancer. 113:782–788. 2005. View Article : Google Scholar : PubMed/NCBI
11.	Fossel ET, Carr JM and McDonagh J: Detection of malignant tumors. Water suppressed proton nuclear magnetic resonance spectroscopy of plasma. N Engl J Med. 315:1369–1376. 1986.PubMed/NCBI
12.	Carraro S, Rezzi S, Reniero F, Héberger K, Giordano G, Zanconato S, Guillou C and Baraldi E: Metabolomics applied to exhaled breath condensate in childhood asthma. Am J Respir Crit Care Med. 175:986–990. 2007. View Article : Google Scholar : PubMed/NCBI
13.	Duarte IF, Goodfellow BJ, Barros A, Jones JG, Barosa C, Diogo L, Garcia P and Gil AM: Metabolic characterisation of plasma in juveniles with glycogen storage disease type 1a (GSD1a) by high-resolution 1H NMR spectroscopy. NMR Biomed. 20:401–412. 2007. View Article : Google Scholar : PubMed/NCBI
14.	Bhawal UK, Ozaki Y, Nishimura M, Sugiyama M, Sasahira T, Nomura Y, Sato F, Fujimoto K, Sasaki N, Ikeda MA, et al: Association of expression of receptor for advanced glycation end products and invasive activity of oral squamous cell carcinoma. Oncology. 69:246–255. 2005. View Article : Google Scholar : PubMed/NCBI
15.	Lindon JC and Holcholson JK: Metabonomics technologies and their applications in physiological monitoring, drug safety assessment and disease diagnosis. Biomarkers. 9:1–31. 2004. View Article : Google Scholar : PubMed/NCBI
16.	Hollywood K, Brison DR and Goodace R: Metabolomics: current technologies and future trends. Proteomics. 6:4716–4723. 2006. View Article : Google Scholar : PubMed/NCBI
17.	Ala-Korpela M: 1H-NMR spectroscopy of human blood plasma. Prog Nucl Magn Reson Spectros. 27:475–484. 1995. View Article : Google Scholar
18.	Sitter B, Bathen T, Hagen B, Arentz C, Skjeldestad FE and Gribbestad IS: Cervical cancer tissue characterized by high-resolution magic angle spinning MR spectroscopy. MAGMA. 16:174–181. 2004. View Article : Google Scholar : PubMed/NCBI
19.	Mahon MM, deSouza NM, Dina R, Soutter WP, McIndoe GA, Williams AD and Cox IJ: Preinvasive and invasive cervical cancer: an ex vivo proton magic angle spinning magnetic resonance spectroscopy study. NMR Biomed. 17:144–153. 2004. View Article : Google Scholar : PubMed/NCBI
20.	Lyng H, Sundfor K and Rofstad EK: Changes in tumor oxygen tension during radiotherapy of uterine cervical cancer: relationships to changes in vascular density, cell density, and frequency of mitosis and apoptosis. Int J Radiat Oncol Biol Phys. 46:935–946. 2000. View Article : Google Scholar : PubMed/NCBI
21.	Walenta S, Wetterling M, Lehrke M, Schwickert G, Sundfør K, Rofstad EK and Mueller-Klieser W: High lactate levels predict likelihood of metastases, tumor recurrence, and restricted patient survival in human cervical cancers. Cancer Res. 60:916–921. 2000.PubMed/NCBI
22.	Woo HM, Kim KM, Choi MH, Jung BH, Lee J, Kong G, Nam SJ, Kim S, Bai SW and Chung BC: Mass spectrometry based metabolomic approaches in urinary biomarker study of women's cancers. Clinica Chimica Acta. 400:63–69. 2009.PubMed/NCBI
23.	Coen M, Lenz EM, Nicholson JK, Wilson ID, Pognan F and Lindon JC: An integrated metabonomic investigation of acetaminophen toxicity in the mouse using NMR spectroscopy. Chem Res Toxicol. 16:295–303. 2003. View Article : Google Scholar : PubMed/NCBI
24.	Smilde AK, Jansen JJ, Hoefsloot HC, Lamers RJ, van der Greef J and Timmerman ME: ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data. J Bio Informatics. 21:3043–3048. 2005.PubMed/NCBI
25.	Nicholson JK, Connelly J, Lindon JC and Holmes E: Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov. 1:153–161. 2002. View Article : Google Scholar : PubMed/NCBI
26.	Holmes E and Antti H: Chemometric contributions to the evolution of metabonomics: mathematical solutions to characterizing and interpreting complex biological NMR spectra. Analyst. 127:1549–1557. 2002. View Article : Google Scholar : PubMed/NCBI
27.	Viant MR: Improved methods for the acquisition and interpretation of NMR metabolomic data. BMC Bioinformatics. 310:943–948. 2003.PubMed/NCBI
28.	Fan W: Metabolite profiling by one-and two-dimensional NMR analysis of complex mixtures. Prog NMR Spectrosc. 28:161–219. 1996. View Article : Google Scholar
29.	Airu Zhou and Xiliang Zha: Biology [M]. People Health Publishing House; Beijing: 2004
30.	Morvan D and Demidem A: Metabolomics by proton nuclear magnetic resonance spectroscopy of the response to chloroethylnitrosourea reveals drug efficacy and tumor adaptive metabolic pathways. Cancer Res. 67:2150–2159. 2007. View Article : Google Scholar
31.	Tiziani S, Lopes V and Günther UL: Early stage diagnosis of oral cancer using 1H NMR-based metabolomics. Neoplasia. 11:269–276. 2009.PubMed/NCBI
32.	Garber K: Energy boost: the Warburg effect returns in a new theory of cancer. J Natl Cancer Inst. 96:1805–1806. 2004. View Article : Google Scholar : PubMed/NCBI
33.	Goodacre R, Vaidyanathan S, Dunn WB, Harrigan GG and Kell DB: Metabolomics by numbers: Acquiring and understanding global metabolite data. Trends Biotechnol. 22:245–252. 2004. View Article : Google Scholar : PubMed/NCBI
34.	Walenta S and Mueller-Klieser WF: Lactate: mirror and motor of tumor malignancy. Semin Radiat Oncol. 14:267–274. 2004. View Article : Google Scholar : PubMed/NCBI
35.	Miller BL: A review of chemical issues in H NMR spectroscopy: N-acetyl-L-aspartate, creatine and choline. NMR Biomed. 4:47–52. 1991. View Article : Google Scholar : PubMed/NCBI
36.	Foster DA and Xu L: Phospholipase D in cell proliferation and cancer. Mol Cancer Res. 1:789–800. 2003.PubMed/NCBI
37.	Ackerstaff E, Glunde K and Bhujwalla ZM: Choline phospholipid metabolism: A target in cancer cells. J Cell Biochem. 90:525–533. 2003. View Article : Google Scholar : PubMed/NCBI
38.	Kubota A, Meguid MM and Hitch DC: Amino-acid profiles correlate diagnostically with organ site in 3 kinds of malignant tumors. Cancer. 69:2343–2348. 1992. View Article : Google Scholar : PubMed/NCBI