Analysis of the raw serum peptidomic pattern in glioma patients

Clinica Chimica Acta

Volumn 425, Issue , 2013, Pages 221-226

  Li, Zheng ^a   Lu, Hongmei ^a   Yang, Jing ^a   Zeng, Xi ^b   Zhao, Lian ^a   Li, Hongdong ^a   Liao, Qianjing ^b   Peng, Shuping ^a   Zhou, Ming ^a   Wu, Minghua ^a   Xiang, Juanjuan ^a   Wang, Yanjin ^c   Li, Guiyuan ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b UNIVERSITY OF SOUTH CHINA   (China)

^c CENTRAL SOUTH UNIVERSITY   (China)

Author keywords

Glioma; Pattern recognition; Peptide; Variable selection

Indexed keywords

BIOLOGICAL MARKER; PEPTIDE;

ACCURACY; ADULT; AREA UNDER THE CURVE; ARTICLE; CANCER DIAGNOSIS; CANCER GRADING; CANCER PROGNOSIS; CANCER STAGING; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; FEMALE; GLIOMA; HUMAN; MAJOR CLINICAL STUDY; MALE; MATRIX ASSISTED LASER DESORPTION IONIZATION TIME OF FLIGHT MASS SPECTROMETRY; PEPTIDE ANALYSIS; PEPTIDOMICS; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; SERUM PEPTIDE;

CARS; COMPETITIVE ADAPTIVE REWEIGHTED SAMPLING; GLIOMA; HCCA; MALDI-TOF MS; MASS SPECTROMETRY; MATRIX ASSISTED LASER DESORPTION/IONIZATION TIME-OF-FLIGHT MASS SPECTROMETRY; MB-WCX; MS; PARTIAL LEAST-SQUARES-LINEAR DISCRIMINATE ANALYSIS; PATTERN RECOGNITION; PEPTIDE; PLS-LDA; SELDI; SURFACE-ENHANCED LASER DESORPTION/IONIZATION; VARIABLE SELECTION; WEAK CATION EXCHANGE CHROMATOGRAPHY MAGNETIC BEAD; Α-CYANO-4-HYDROXYCINNAMIC ACID;

ADULT; BLOOD PROTEINS; BRAIN NEOPLASMS; CASE-CONTROL STUDIES; DISCRIMINANT ANALYSIS; EARLY DIAGNOSIS; FEMALE; GLIOMA; HUMANS; MAGNETS; MALE; MICROSPHERES; MIDDLE AGED; NEOPLASM PROTEINS; NEOPLASM STAGING; PEPTIDE FRAGMENTS; PROTEOMICS; ROC CURVE; SPECTROMETRY, MASS, MATRIX-ASSISTED LASER DESORPTION-IONIZATION;

EID: 84883506147     PISSN: 00098981     EISSN: 18733492     Source Type: Journal    
DOI: 10.1016/j.cca.2013.08.002     Document Type: Article

References (43)

1. Ohgaki H., Kleihues P. Population-based studies on incidence, survival rates, and genetic alterations in astrocytic and oligodendroglial gliomas. J Neuropathol Exp Neurol 2005, 64:479-489.
2. Cowan W.M., Harter D.H., Kandel E.R. The emergence of modern neuroscience: some implications for neurology and psychiatry. Annu Rev Neurosci 2000, 23:343-391.
3. Doetsch F. The glial identity of neural stem cells. Nat Neurosci 2003, 6:1127-1134.
4. Eng L.F., Vanderhaeghen J.J., Bignami A., Gerstl B. An acidic protein isolated from fibrous astrocytes. Brain Res 1971, 28:351-354.
5. Jung C.S., Foerch C., Schänzer A., et al. Serum GFAP is a diagnostic marker for glioblastoma multiforme. Brain 2007, 130:3336-3341.
6. Yan H., Parsons D.W., Jin G., et al. IDH1 and IDH2 mutations in gliomas. N Engl J Med 2009, 360:765-773.
7. Sanson M., Marie Y., Paris S., et al. Isocitrate dehydrogenase 1 codon 132 mutation is an important prognostic biomarker in gliomas. J Clin Oncol 2009, 27:4150-4154.
8. Petricoin E.F., Belluco C., Araujo R.P., Liotta L.A. The blood peptidome: a higher dimension of information content for cancer biomarker discovery. Nat Rev Cancer 2006, 6:961-967.
9. Liotta L.A., Ferrari M., Petricoin E. Clinical proteomics: written in blood. Nature 2003, 425:905.
10. Tirumalai R.S., Chan K.C., Prieto D.A., Issaq H.J., Conrads T.P., Veenstra T.D. Characterization of the low molecular weight human serum proteome. Mol Cell Proteomics 2003, 2:1096-1103.
11. Petricoin E.F., Ardekani A.M., Hitt B.A., et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet 2002, 359:572-577.
12. Petricoin E.F., Ornstein D.K., Paweletz C.P., et al. Serum proteomic patterns for detection of prostate cancer. J Natl Cancer Inst 2002, 94:1576-1578.
13. Cheng A.J., Chen L.C., Chien K.Y., et al. Oral cancer plasma tumor marker identified with bead-based affinity-fractionated proteomic technology. Clin Chem 2005, 51:2236-2244.
14. Noo M.E., Deelder A., Werff M., Özalp A., Mertens B., Tollenaar R. MALDI-TOF serum protein profiling for the detection of breast cancer. Onkologie 2006, 29:501-506.
15. de Noo M.E., Mertens B.J.A., Özalp A., et al. Detection of colorectal cancer using MALDI-TOF serum protein profiling. Eur J Cancer 2006, 42:1068-1076.
16. Orvisky E., Drake S.K., Martin B.M., et al. Enrichment of low molecular weight fraction of serum for MS analysis of peptides associated with hepatocellular carcinoma. Proteomics 2006, 6:2895-2902.
17. Anderson N.L., Anderson N.G. The human plasma proteome: history, character, and diagnostic prospects. Mol Cell Proteomics 2002, 1:845-867.
18. Rai A.J., Zhang Z., Rosenzweig J., et al. Proteomic approaches to tumor marker discovery. Arch Pathol Lab Med 2009, 126:1518-1526.
19. Baumann S., Ceglarek U., Fiedler G.M., Lembcke J., Leichtle A., Thiery J. Standardized approach to proteome profiling of human serum based on magnetic bead separation and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Clin Chem 2005, 51:973-980.
20. Zeng X., Zhao L., Li Z., et al. Impact of experimental and demographic variables in serum peptide profiling based on magnetic bead and MALDI-TOF mass spectrometry. Clin Chim Acta 2010, 412:112-119.
21. Li H., Liang Y., Xu Q., Cao D. Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration. Anal Chim Acta 2009, 648:77-84.
22. Boguski M.S., McIntosh M.W. Biomedical informatics for proteomics. Nature 2003, 422:233-237.
23. de Noo M.E., Tollenaar R.A., Ozalp A., et al. Reliability of human serum protein profiles generated with C8 magnetic beads assisted MALDI-TOF mass spectrometry. Anal Chem 2005, 77:7232-7241.
24. Villanueva J., Martorella A.J., Lawlor K., et al. Serum peptidome patterns that distinguish metastatic thyroid carcinoma from cancer-free controls are unbiased by gender and age. Mol Cell Proteomics 2006, 5:1840-1852.
25. Shamsipur M., Zare-shahabadi V., Hemmateenejad B., Akhond M. Combination of ant colony optimization with various local search strategies. A novel method for variable selection in multivariate calibration and QSPR study. QSAR Comb Sci 2009, 28:1263-1275.
26. Horchner U., Kalivas J.H. Further investigation on a comparative study of simulated annealing and genetic algorithm for wavelength selection. Anal Chim Acta 1995, 311:1-13.
27. Yi-Zeng L., Yu-Long X., Ru-Qin Y. Accuracy criteria and optimal wavelength selection for multicomponent spectrophotometric determinations. Anal Chim Acta 1989, 222:347-357.
28. Chen T., Martin E. Bayesian linear regression and variable selection for spectroscopic calibration. Anal Chim Acta 2009, 631:13-21.
29. Tan C., Wang J., Wu T., Qin X., Li M. An ensemble method based on uninformative variable elimination and mutual information for spectral multivariate calibration. Spectrochim Acta A Mol Biomol Spectrosc 2010, 77:960-964.
30. Bangalore A.S., Shaffer R.E., Gary W., Arnold M.A. Genetic algorithm-based method for selecting wavelengths and model size for use with partial least-squares regression: application to near-infrared spectroscopy. Anal Chem 1996, 68:4200-4212.
31. Khajehsharifi H., Pourbasheer E. Genetic-algorithm-based wavelength selection in multi-component spectrophotometric determination by PLS: application on ascorbic acid and uric acid mixture. J Chin Chem Soc Taip 2008, 55:163.
32. Osborne S.D., Künnemeyer R., Jordan R.B. Method of wavelength selection for partial least squares. Analyst 1997, 122:1531-1537.
33. Centner V., Massart D.L., de Noord O.E., de Jong S., Vandeginste B.M., Sterna C. Elimination of uninformative variables for multivariate calibration. Anal Chem 1996, 68:3851-3858.
34. Cai W., Li Y., Shao X. A variable selection method based on uninformative variable elimination for multivariate calibration of near-infrared spectra. Chemom Intell Lab 2008, 90:188-194.
35. Han Q.J., Wu H.L., Cai C.B., Xu L., Yu R.Q. An ensemble of Monte Carlo uninformative variable elimination for wavelength selection. Anal Chim Acta 2008, 612:121-125.
36. Jiang J.H., Berry R.J., Siesler H.W., Ozaki Y. Wavelength interval selection in multicomponent spectral analysis by moving window partial least-squares regression with applications to mid-infrared and near-infrared spectroscopic data. Anal Chem 2002, 74:3555-3565.
37. Zhang H., Wu G., Tu H., Huang F. Discovery of serum biomarkers in astrocytoma by SELDI-TOF MS and proteinchip technology. J Neuro Oncol 2007, 84:315-323.
38. Liu J., Zheng S., Yu J., Zhang J., Chen Z. Serum protein fingerprinting coupled with artificial neural network distinguishes glioma from healthy population or brain benign tumor. J Zhejiang Univ Sci B 2005, 4-10.
39. Villanueva J., Philip J., Entenberg D., et al. Serum peptide profiling by magnetic particle-assisted, automated sample processing and MALDI-TOF mass spectrometry. Anal Chem 2004, 76:1560-1570.
40. Petrik V., Saadoun S., Loosemore A., et al. Serum alpha2-HS glycoprotein predicts survival in patients with glioblastoma. Clin Chem 2008, 54:713-722.
41. Ku B.M., Lee Y.K., Ryu J., et al. CHI3L1 (YKL-40) is expressed in human gliomas and regulates the invasion, growth and survival of glioma cells. Int J Cancer 2011, 128:1316-1326.
42. Francescone R.A., Scully S., Faibish M., et al. Role of YKL-40 in the angiogenesis, radioresistance, and progression of glioblastoma. J Biol Chem 2011, 286:15332-15343.
43. Pelloski C.E., Mahajan A., Maor M., et al. YKL-40 expression is associated with poorer response to radiation and shorter overall survival in glioblastoma. Clin Cancer Res 2005, 11:3326-3334.