Isolation and identification of mannose-binding proteins and estimation of their abundance in sera from hepatocellular carcinoma patients

Proteomics

Volumn 13, Issue 5, 2013, Pages 878-892

  Yang, Ganglong ^a   Chu, Wei ^a   Zhang, Hua ^b   Sun, Xiuxuan ^a   Cai, Tanxi ^c   Dang, Liuyi ^a   Wang, Qinzhe ^a   Yu, Hanjie ^a   Zhong, Yaogang ^a   Chen, Zhuo ^a   Yang, Fuquan ^c   Li, Zheng ^a  

^a NORTHWEST UNIVERSITY   (China)

^b SHAANXI PROVINCIAL PEOPLE S HOSPITAL   (China)

^c INSTITUTE OF BIOPHYSICS   (China)

Author keywords

Biomedicine; Exponentially modified protein abundance index; Glycan binding proteins; Hepatocellular Carcinoma; Mannose binding proteins; Mannose magnetic particle conjugates

Indexed keywords

MANNOSE; MANNOSE BINDING PROTEIN;

AMINO ACID SEQUENCE; ARTICLE; CELL DEATH; CONTROLLED STUDY; DOWN REGULATION; HUMAN; LIQUID CHROMATOGRAPHY; LIVER CELL CARCINOMA; MACROMOLECULE; MAJOR CLINICAL STUDY; NUCLEOTIDE SEQUENCE; POLYACRYLAMIDE GEL ELECTROPHORESIS; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN BLOOD LEVEL; PROTEIN ISOLATION; PROTEIN MICROARRAY; PROTEIN MOTIF; PROTEIN STRUCTURE; REAL TIME POLYMERASE CHAIN REACTION; TANDEM MASS SPECTROMETRY; TUMOR GROWTH; UPREGULATION; WESTERN BLOTTING;

AMINO ACID MOTIFS; AMINO ACID SEQUENCE; BLOTTING, WESTERN; CARCINOMA, HEPATOCELLULAR; CASE-CONTROL STUDIES; CHROMATOGRAPHY, LIQUID; HUMANS; LIVER NEOPLASMS; MANNOSE-BINDING LECTINS; MOLECULAR SEQUENCE DATA; NEOPLASM PROTEINS; PROTEIN ARRAY ANALYSIS; REAL-TIME POLYMERASE CHAIN REACTION; TANDEM MASS SPECTROMETRY;

EID: 84874813850     PISSN: 16159853     EISSN: 16159861     Source Type: Journal    
DOI: 10.1002/pmic.201200018     Document Type: Article

References (51)

1. Varki, A., Etzler, M. E., Cummings, R. D., Esko, J. D., in: Varki, A., Cummings, R. D., Esko, J. D., Freeze, H. H. (Eds.), Discovery and Classification of Glycan-Binding Proteins, Cold Spring Harbor Laboratory Press, New York 1999, pp. 527-543.
2. Kulkarni, A. A., Weiss, A. A., Iyer, S. S., Glycan-based high-affinity ligands for toxins and pathogen receptors. Med. Res. Rev. 2010, 30, 327-393.
3. Rillahan, C. D., Paulson, J. C., Glycan microarrays for decoding the glycome. Annu. Rev. Biochem. 2011, 80, 797-823.
4. Varki, A., Glycan-based interactions involving vertebrate sialic-acid-recognizing proteins. Nature 2007, 446, 1023-1029.
5. Blixt, O., Functional glycan microarrays-moving glycomics forward. Ebook published in BTi, November 2005, http://www.biotech-online.com.
6. Paulson, J. C., Blixt, O., Collins, B. E., Sweet spots in functional glycomics. Nat. Chem. Biol. 2006, 2, 238-248.
7. Ji, X., Gewurz, H., Spear, G. T., Mannose binding lectin (MBL) and HIV. Mol. Immunol. 2005, 42, 145-152.
8. Christiansen, O. B., Nielsen, H. S., Lund, M., Steffensen, R. et al., Mannose-binding lectin-2 genotypes and recurrent late pregnancy losses. Hum. Reprod. 2009, 24, 291-299.
9. Holmskov, U., Malhotra, R., Sim, R. B., Jensenius, J. C., Collectins: collagenous C-type lectins of the innate immune defense system. Immunol. Today 1994, 15, 67-74.
10. Hatakeyama, T., Unno, H., Kouzuma, Y., Uchida, T. et al., C-type lectin-like carbohydrate recognition of the hemolytic lectin CEL-III containing Ricin-type Trefoil folds. J. Bio. Chem. 2007, 282, 37826-37835.
11. Endeman, H., Herpers, B. L., de Jong, B. A. W., Voorn, G. P. et al., Mannose-binding lectin genotypes in susceptibility to community-acquired Pneumonia. Chest 2008, 134, 1135-1140.
12. Worthley, D. L., Johnson, D. F., Eisen, D. P., Dean, M. M. et al., Donor mannose-binding lectin deficiency increases the likelihood of clinically significant infection after liver transplantation. Clin. Infect. Dis. 2009, 48, 410-417.
13. Kilpatrick, D. C., Mannan-binding lectin: clinical significance and applications. Biochim. Biophys. Acta 2002, 1572, 401-413.
14. Osthoff, M., Rovó, A., Stern, M., Danner, D. et al., Mannose-binding lectin levels and major infections in a cohort of very long-term survivors after allogeneic stem cell transplantation. Haematology 2010, 95, 1389-1396.
15. Rong, Y., Jin, D., Hou, C., Hu, J. et al., Proteomics analysis of serum protein profiling in pancreatic cancer patients by DIGE: up-regulation of mannose-binding lectin 2 and myosin light chain kinase 2. BMC Gastroenterol. 2010, 10, 1-9.
16. Garred, P., Larsen, F., Seyfarth, J., Fujita, R. et al., Mannose-binding lectin and its genetic variants. Genes Immun. 2006, 7, 85-94.
17. Database of human proteins containing CTLDs [http://www.imperial.ac.uk/research/animallectins/ctld/mammals/humandata.html]
18. Wu, C., Hsu, C., Chen, C., Yu, C. et al., Candidate serological biomarkers for cancer identified from the secretomes of 23 cancer cell lines and the human protein atlas. Mol. Cell. Proteomics 2010, 9, 1100-1117.
19. Sun, X., Yang, G., Sun, S., Li, Z. et al., The hydroxyl-functionalized magnetic particles for purification of glycan-binding proteins. Curr. Pharm. Biotechnol. 2009, 10, 753-760.
20. Lasonder, E., Ishihama, Y., Andersen, J. S., Mann, M. et al., Analysis of the Plasmodium Falciparum proteome by high-accuracy mass spectrometry. Nature 2002, 419, 537-542.
21. Ishihama, Y., Oda, Y., Tabata, T., Mann, M. et al., Exponentially modified protein abundance index (emPAI) for estimation of absolute protein amount in proteomics by the number of sequenced peptides per protein. Mol. Cell. Proteomics 2005, 4, 1265-1272.
22. Nan, G., Yan, H., Yang, G., Li, Z. et al., The hydroxyl-modified surfaces on glass support for fabrication of carbohydrate microarrays. Curr. Pharm. Biotechnol. 2009, 10, 138-146.
23. Shinoda, K., Tomita, M., Ishihama, Y., emPAI Calc-for the estimation of protein abundance from large-scale identification data by liquid chromatography-tandem mass spectrometry. Bioinformatics 2010, 26, 576-577.
24. Liu, Y., He, J., Li, C., Lubman, D. M. et al., Identification and confirmation of biomarkers using an integrated platform for quantitative analysis of glycoproteins and their glycosylations. J. Proteome Res. 2010, 9, 798-805.
25. Qin, Y., Zhong, Y., Dang, L., Li, Z. et al., Alteration of protein glycosylation in human hepatic stellate cells activated with transforming growth factor-β1. J. Proteomics 2012, 75, 4114-4123.
26. Heimburg-Molinaro, J., Song, X., Smith, D. F., Cummings, R. D., Preparation and analysis of glycan microarrays. Curr. Protoc. Protein Sci. 2011, 64, 1-29.
27. Cummings, R. D., Mcever, R. P., in: Varki, A., Cummings, R. D., Esko, J. D., Freeze, H. H. (Eds.), C-type Lectins, Cold Spring Harbor Laboratory Press, New York 1999, pp. 610-634.
28. Schwartz, D., Gygi, S. P., An iterative statistical approach to the identification of protein phosphorylation motifs from large-scale data sets. Nat. Biotechnol. 2005, 23, 1391-1398.
29. Yachie, N., Saito, R., Sugahara, J., Ishihama, Y. et al., In silico analysis of phosphoproteome data suggests a rich-get-richer process of phosphosite accumulation over evolution. Mol. Cell. Proteomics 2009, 8, 1061-1071.
30. Zielinska, D. F., Gnad, F., Wisniewski, J. R., Mann, M., Precision mapping of an in vivo N-glycoproteome reveals rigid topological and sequence constraints. Cell 2010, 141, 897-907.
31. Bendtsen, J. D., Nielsen, H., von Heijne, G., Brunak, S., Improved prediction of signal peptides: SignalP. 3.0. J. Mol. Biol. 2004, 340, 783-795.
32. Nielsen, H., Krogh, A., Prediction of signal peptides and signal anchors by a hidden Markov model. Proc. Int. Conf. Intell. Syst. Mol. Biol. 1998, 6, 122-130.
33. Bendtsen, J. D., Jensen, L. J., Blom, N., von Heijne, G. et al., Feature-based prediction of non-classical and leaderless protein secretion. Protein Eng. Des. Sel. 2004, 17, 349-356.
34. Moller, S., Croning, M. D., Apweiler, R., Evaluation of methods for the prediction of membrane spanning regions. Bioinformatics 2001, 17, 646-653.
35. Conesa, A., Götz, S., García-Gómez, J. M., Robles, M. et al., Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 2005, 21, 3674-3676.
36. Götz, S., García-Gómez, J. M., Terol, J., Williams, T. D. et al., High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res. 2008, 20, 3420-3435.
37. Huang, D. W., Sherman, B. T., Tan, Q., Lempicki, R. A. et al., DAVID bioinformatics resources: expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Res. 2007, 35, 169-175.
38. Huang, D. W., Sherman, B. T., Lempicki, R. A., Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 2009, 4, 44-57.
39. Dennis, G., Sherman, B. T., Hosack, D. A., Lempicki, R. A. et al., DAVID: database for annotation, visualization, and integrated discovery. Gen. Bio. 2003, 4, 1-11.
40. van Kooyk, Y., Rabinovich, G. A., Protein-glycan interactions in the control of innate and adaptive immune responses. Nat. Immunol. 2008, 9, 593-601.
41. Endo, Y., Nonaka, M., Saiga, H., Fujita, T. et al., Origin of mannose-binding lectin-associated serine protease (MASP)-1 and MASP-3 involved in the lectin complement pathway traced back to the invertebrate, amphioxus. J. Immunol. 2003, 170, 4701-4707.
42. Matsushita, M., Thiel, S., Jensenius, J. C., Fujita, T. et al., Proteolytic activities of two types of mannose-binding lectin-associated serine protease. J. Immunol. 2000, 165, 2637-2642.
43. Bosch, F. X., Ribes, J., Diaz, M., Cleries, R., Primary liver cancer: worldwide incidence and trends. Gastroenterology 2004, 127, S5-S16.
44. Gupta, S., Bent, S., Kohlwes, J., Test characteristics of α-fetoprotein for detecting hepatocellular carcinoma in patients with hepatitis C. A systematic review and critical analysis. Ann. Intern. Med. 2003, 139, 46-50.
45. Filmus, J., Capurro, M., Glypican-3 and α-fetoprotein as diagnostic tests for hepatocellular carcinoma. Mol. Diagn. 2004, 8, 207-212.
46. Chignard, N., Shang, S., Wang, H., Beretta, L. et al., Cleavage of endoplasmic reticulum proteins in hepatocellular carcinoma: detection of generated fragments in patient sera. Gastroenterology 2006, 130, 2010-2022.
47. Szendröi, M., Lapis, K., Distribution of fibronectin and laminin in human liver tumors. J. Cancer Res. Clin. 1985, 109, 60-64.
48. Ooi, K., Shiraki, K., Sakurai, Y., Nobori, T. et al., Clinical significance of abnormal lipoprotein patterns in liver diseases. Int. J. Mol. Med. 2005, 15, 655-660.
49. Yokoyama, Y., Kuramitsu, Y., Takashima, M., Sakaida, I. et al., Protein level of apolipoprotein E increased in human hepatocellular carcinoma. Int. J. Oncol. 2006, 28, 625-631.
50. Lawlor, K., Nazarian, A., Lacomis, L., Villanueva, J. et al., Pathway-based biomarker search by high-throughput proteomics profiling of secretomes. J. Proteome Res. 2009, 8, 1489-1503.
51. Jovanovic, M., Reiter, L., Picotti, P., Hengartner, M. O. et al., A quantitative targeted proteomics approach to validate predicted microRNA targets in C. elegans. Nat. Methods 2010, 7, 837-846.