A metabonomic approach to chemosensitivity prediction of cisplatin plus 5-fluorouracil in a human xenograft model of gastric cancer

International Journal of Cancer

Volumn 127, Issue 12, 2010, Pages 2841-2850

  Wang, Xi ^a   Yan, Shi Kai ^b   Dai, Wei Xing ^c   Liu, Xin Ru ^c   Zhang, Wei Dong ^b,c   Wang, Jie Jun ^a  

^a SECOND MILITARY MEDICAL UNIVERSITY   (China)

^b SHANGHAI JIAO TONG UNIVERSITY   (China)

^c SECOND MILITARY MEDICAL UNIVERSITY   (China)

Author keywords

Chemosensitivity; Gastric cancer; HPLC MS; Metabonomics; Prediction model

Indexed keywords

2 LYSOPHOSPHATIDYLCHOLINE; CISPLATIN; FLUOROURACIL; POLYUNSATURATED FATTY ACID; UNCLASSIFIED DRUG;

ANIMAL EXPERIMENT; ANIMAL MODEL; ARTICLE; CANCER CHEMOTHERAPY; CHEMOSENSITIVITY; CONTROLLED STUDY; HIGH PERFORMANCE LIQUID CHROMATOGRAPHY; HUMAN; HUMAN CELL; MOUSE; NONHUMAN; PRIORITY JOURNAL; STOMACH CANCER; TIME OF FLIGHT MASS SPECTROMETRY; XENOGRAFT;

ADENOCARCINOMA; ANIMALS; ANTINEOPLASTIC COMBINED CHEMOTHERAPY PROTOCOLS; CISPLATIN; DRUG RESISTANCE, NEOPLASM; FLUOROURACIL; HUMANS; METABOLOMICS; MICE; MICE, INBRED BALB C; MICE, NUDE; SPECTROMETRY, MASS, MATRIX-ASSISTED LASER DESORPTION-IONIZATION; STOMACH NEOPLASMS; TUMOR CELLS, CULTURED; TUMOR MARKERS, BIOLOGICAL; XENOGRAFT MODEL ANTITUMOR ASSAYS;

EID: 78249261828     PISSN: 00207136     EISSN: 10970215     Source Type: Journal    
DOI: 10.1002/ijc.25294     Document Type: Article

References (45)

1. Wagner AD, Grothe W, Haerting J, Kleber G, Grothey A, Fleig WE,. Chemotherapy in advanced gastric cancer: a systematic review and meta-analysis based on aggregate data. J Clin Oncol 2006; 24: 2903 -9.
2. Park DJ, Lenz HJ,. Determinants of chemosensitivity in gastric cancer. Curr Opin Pharmacol 2006; 6: 337 -44.
3. Sikora K,. Personalized cancer therapy-the key to the future. Pharmacogenomics 2004; 5: 225 -8.
4. Jain KK,. Personalised medicine for cancer: from drug development into clinical practice. Expert Opin Pharmacother 2005; 6: 1463 -76.
5. Kubota T, Weisenthal L,. Chemotherapy sensitivity and resistance testing: to be "standard" or to be individualized, that is the question. Gastric Cancer 2006; 9: 82 -7.
6. Blumenthal RD, Goldenberg DM,. Methods and goals for the use of in vitro and in vivo chemosensitivity testing. Mol Biotechnol 2007; 35: 185 -97.
7. Schrag D, Garewal HS, Burstein HJ, Samson DJ, Von Hoff DD, Somerfield MR,. American Society of Clinical Oncology Technology Assessment: chemotherapy sensitivity and resistance assays. J Clin Oncol 2004; 22: 3631 -8.
8. Lenz HJ, Leichman CG, Danenberg KD, Danenberg PV, Groshen S, Cohen H, Laine L, Crookes P, Silberman H, Baranda J, Garcia Y, Li J, et al. Thymidylate synthase mRNA level in adenocarcinoma of the stomach: a predictor for primary tumor response and overall survival. J Clin Oncol 1996; 14: 176 -82.
9. Boku N, Chin K, Hosokawa K, Ohtsu A, Tajiri H, Yoshida S, Yamao T, Kondo H, Shirao K, Shimada Y, Saito D, Hasebe T, et al. Biological markers as a predictor for response and prognosis of unresectable gastric cancer patients treated with 5-fluorouracil and cis-platinum. Clin Cancer Res 1998; 4: 1469 -74.
10. Terashima M, Fujiwara H, Takagane A, Abe K, Irinoda T, Nakaya T, Yonezawa H, Oyama K, Saito K, Kanzaki N, Ohtani S, Nemoto T, et al. Prediction of sensitivity to fluoropyrimidines by metabolic and target enzyme activities in gastric cancer. Gastric Cancer 2003; 6 (Suppl 1): 71 -81.
11. Ichikawa W,. Prediction of clinical outcome of fluoropyrimidine-based chemotherapy for gastric cancer patients, in terms of the 5-fluorouracil metabolic pathway. Gastric Cancer 2006; 9: 145 -55.
12. Kodera Y, Ito S, Fujiwara M, Mochizuki Y, Nakayama G, Ohashi N, Koike M, Yamamura Y, Nakao A,. Gene expression of 5-fluorouracil metabolic enzymes in primary gastric cancer: correlation with drug sensitivity against 5-fluorouracil. Cancer Lett 2007; 252: 307 -13.
13. Metzger R, Leichman CG, Danenberg KD, Danenberg PV, Lenz HJ, Hayashi K, Groshen S, Salonga D, Cohen H, Laine L, Crookes P, Silberman H, et al. ERCC1 mRNA levels complement thymidylate synthase mRNA levels in predicting response and survival for gastric cancer patients receiving combination cisplatin and fluorouracil chemotherapy. J Clin Oncol 1998; 16: 309 -16.
14. Kwon HC, Roh MS, Oh SY, Kim SH, Kim MC, Kim JS, Kim HJ,. Prognostic value of expression of ERCC1, thymidylate synthase, and glutathione S-transferase P1 for 5-fluorouracil/oxaliplatin chemotherapy in advanced gastric cancer. Ann Oncol 2007; 18: 504 -9.
15. Matsubara J, Nishina T, Yamada Y, Moriwaki T, Shimoda T, Kajiwara T, Nakajima TE, Kato K, Hamaguchi T, Shimada Y, Okayama Y, Oka T, et al. Impacts of excision repair cross-complementing gene 1 (ERCC1), dihydropyrimidine dehydrogenase, and epidermal growth factor receptor on the outcomes of patients with advanced gastric cancer. Br J Cancer 2008; 98: 832 -9.
16. McLeod HL,. Individualized cancer therapy: molecular approaches to the prediction of tumor response. Expert Rev Anticancer Ther 2002; 2: 113 -9.
17. Fareed KR, Kaye P, Soomro IN, Ilyas M, Martin S, Parsons SL, Madhusudan S,. Biomarkers of response to therapy in oesophago-gastric cancer. Gut 2009; 58: 127 -43.
18. Garman KS, Nevins JR, Potti A,. Genomic strategies for personalized cancer therapy. Hum Mol Genet 2007; 16 (Spec No. 2): R226 -R32.
19. Ma Y, Ding Z, Qian Y, Shi X, Castranova V, Harner EJ, Guo L,. Predicting cancer drug response by proteomic profiling. Clin Cancer Res 2006; 12: 4583 -9.
20. Roukos DH,. Innovative genomic-based model for personalized treatment of gastric cancer: integrating current standards and new technologies. Expert Rev Mol Diagn 2008; 8: 29 -39.
21. Schmidt C,. Metabolomics takes its place as latest up-and-coming "omic" science. J Natl Cancer Inst 2004; 96: 732 -4.
22. Odunsi K, Wollman RM, Ambrosone CB, Hutson A, McCann SE, Tammela J, Geisler JP, Miller G, Sellers T, Cliby W, Qian F, Keitz B, et al. Detection of epithelial ovarian cancer using 1H-NMR-based metabonomics. Int J Cancer 2005; 113: 782 -8.
23. Yan SK, Wei BJ, Lin ZY, Yang Y, Zhou ZT, Zhang WD,. A metabonomic approach to the diagnosis of oral squamous cell carcinoma, oral lichen planus and oral leukoplakia. Oral Oncol 2008; 44: 477 -83.
24. Ippolito JE, Xu J, Jain S, Moulder K, Mennerick S, Crowley JR, Townsend RR, Gordon JI,. An integrated functional genomics and metabolomics approach for defining poor prognosis in human neuroendocrine cancers. Proc Natl Acad Sci USA 2005; 102: 9901 -6.
25. Nicholson JK, Connelly J, Lindon JC, Holmes E,. Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov 2002; 1: 153 -61.
26. Lindon JC, Holmes E, Nicholson JK,. Metabonomics: systems biology in pharmaceutical research and development. Curr Opin Mol Ther 2004; 6: 265 -72.
27. Lindon JC, Holmes E, Bollard ME, Stanley EG, Nicholson JK,. Metabonomics technologies and their applications in physiological monitoring, drug safety assessment and disease diagnosis. Biomarkers 2004; 9: 1 -31.
28. Clayton TA, Lindon JC, Cloarec O, Antti H, Charuel C, Hanton G, Provost JP, Le Net JL, Baker D, Walley RJ, Everett JR, Nicholson JK,. Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature 2006; 440: 1073 -7.
29. Di Leo A, Claudino W, Colangiuli D, Bessi S, Pestrin M, Biganzoli L,. New strategies to identify molecular markers predicting chemotherapy activity and toxicity in breast cancer. Ann Oncol 2007; 18 (Suppl 12): xii8 -14.
30. Wold S, Kettaneh N, Tjessem K,. Hierarchical multi-block PLS and PC models, for easier interpretation, and as an alternative to variable selection. J Chemometr 1996; 10: 463 -82.
31. Wold S, Sjostrom M, Eriksson L,. PLS-regression: a basic tool of chemometrics. Chemometr Intell Lab 2001; 58: 109 -30.
32. Brereton RG,. Chemometrics: data analysis for the laboratory and chemical plant. Chichester: John Wiley, 2003.
33. Staunton JE, Slonim DK, Coller HA, Tamayo P, Angelo MJ, Park J, Scherf U, Lee JK, Reinhold WO, Weinstein JN, Mesirov JP, Lander ES, et al. Chemosensitivity prediction by transcriptional profiling. Proc Natl Acad Sci USA 2001; 98: 10787 -92.
34. Blumenthal RD,. Chemosensitivity, vol. 2: in vivo models, imaging and molecular regulators. Totowa, NJ: Humana Press, 2005.
35. Nicholson JK, Lindon JC, Holmes E,. Metabonomics: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 1999; 29: 1181 -9.
36. Ruzzo A, Graziano F, Kawakami K, Watanabe G, Santini D, Catalano V, Bisonni R, Canestrari E, Ficarelli R, Menichetti ET, Mari D, Testa E, et al. Pharmacogenetic profiling and clinical outcome of patients with advanced gastric cancer treated with palliative chemotherapy. J Clin Oncol 2006; 24: 1883 -91.
37. Eriksson L, Antti H, Gottfries J, Holmes E, Johansson E, Lindgren F, Long I, Lundstedt T, Trygg J, Wold S,. Using chemometrics for navigating in the large data sets of genomics, proteomics, and metabonomics (gpm). Anal Bioanal Chem 2004; 380: 419 -29.
38. Kettaneh-Wold N,. Analysis of mixture data with partial least squares. Chemometr Intell Lab 1992; 14: 57 -69.
39. Lu X, Zhao X, Bai C, Zhao C, Lu G, Xu G,. LC-MS-based metabonomics analysis. J Chromatogr B 2008; 866: 64 -76.
40. Wilm M, Mann M,. Analytical properties of the nanoelectrospray ion source. Anal Chem 1996; 68: 1 -8.
41. Smith RD, Loo JA, Edmonds CG, Barinaga CJ, Udseth HR,. New developments in biochemical mass spectrometry: electrospray ionization. Anal Chem 1990; 62: 882 -99.
42. Burke JE, Dennis EA,. Phospholipase A2 biochemistry. Cardiovasc Drugs Ther 2009; 23: 49 -59.
43. Kent C,. Regulatory enzymes of phosphatidylcholine biosynthesis: a personal perspective. Biochim Biophys Acta 2005; 1733: 53 -66.
44. Lands WE,. Stories about acyl chains. Biochim Biophys Acta 2000; 1483: 1 -14.
45. Jackson SK, Abate W, Tonks AJ,. Lysophospholipid acyltransferases: novel potential regulators of the inflammatory response and target for new drug discovery. Pharmacol Ther 2008; 119: 104 -14.