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Glycomic profiling of invasive and non-invasive breast cancer cells

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Abstract

Quantitative profiling of glycans with different structures appears essential for a better understanding of the cellular adhesion phenomena associated with malignant transformation and the underlying aberrant glycosylation of cancer cells. Using the recently developed glycomic techniques and mass-spectrometric measurements, we compare the N-linked and O-linked oligosaccharide profiles for different breast cancer cell lines with those of normal epithelial cells. Statistically significant differences in certain neutral, sialylated and fucosylated structures are readily discerned through quantitative measurements, indicating a potential of distinguishing invasive and non-invasive cancer attributes. The glycomic profile data cluster accordingly using Principal Component Analysis, verifying further glycobiological differences due to the differences between normal and cancer cell lines.

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References

  1. Tang, D.G., Honn, K.V.: Adhesion molecules and tumor metastasis: an update. Invasion Metastasis 14(1–6), 109–122 (1994)

    PubMed  CAS  Google Scholar 

  2. Kannagi, R.: Carbohydrate-mediated cell adhesion involved in hematogenous metastasis of cancer. Glycoconj. J. 14(5), 577–584 (1997)

    Article  PubMed  CAS  Google Scholar 

  3. Fukuda, M.: Possible roles of tumor-associated carbohydrate antigens. Cancer Res. 56(10), 2237–2244 (1996)

    PubMed  CAS  Google Scholar 

  4. Kansas, G.S.: Selectins and their ligands: current concepts and controversies. Blood 88(9), 3259–3287 (1996)

    PubMed  CAS  Google Scholar 

  5. Leong, S.P., et al.: Clinical patterns of metastasis. Cancer Metastasis Rev. 25(2), 221–232 (2006)

    Article  PubMed  Google Scholar 

  6. Kang, P., et al.: Comparative glycomic mapping through quantitative permethylation and stable-isotope labeling. Anal. Chem. 79(16), 6064–6073 (2007)

    Article  PubMed  CAS  Google Scholar 

  7. Kyselova, Z., et al.: Breast cancer diagnosis and prognosis through quantitative measurements of serum glycan profiles. Clin. Chem. 54, 1166–1175 (2008)

    Article  PubMed  CAS  Google Scholar 

  8. Hathout, Y., et al.: Proteomic phenotyping: metastatic and invasive breast cancer. Cancer Lett. 210(2), 245–253 (2004)

    Article  PubMed  CAS  Google Scholar 

  9. Jiang, D., et al.: Identification of metastasis-associated proteins by proteomic analysis and functional exploration of interleukin-18 in metastasis. Proteomics 3(5), 724–737 (2003)

    Article  PubMed  CAS  Google Scholar 

  10. Kluger, H.M., et al.: cDNA microarray analysis of invasive and tumorigenic phenotypes in a breast cancer model. Lab. Invest. 84(3), 320–331 (2004)

    Article  PubMed  CAS  Google Scholar 

  11. Nishizuka, I., et al.: Analysis of gene expression involved in brain metastasis from breast cancer using cDNA microarray. Breast Cancer 9(1), 26–32 (2002)

    Article  PubMed  Google Scholar 

  12. Tanaka, H., et al.: Differential gene expression screening between parental and highly metastatic pancreatic cancer variants using a DNA microarray. J. Exp. Clin. Cancer. Res. 22(2), 307–313 (2003)

    PubMed  CAS  Google Scholar 

  13. Bjerner, J., et al.: MUC1 serum assays in breast cancer: tumor specificities and reference levels. Tumour Biol. 23(6), 315–323 (2002)

    Article  PubMed  CAS  Google Scholar 

  14. Rakha, E.A., et al.: Expression of mucins (MUC1, MUC2, MUC3, MUC4, MUC5AC and MUC6) and their prognostic significance in human breast cancer. Mod. Pathol. 18(10), 1295–1304 (2005)

    Article  PubMed  CAS  Google Scholar 

  15. Miyamoto, S.: Clinical applications of glycomic approaches for the detection of cancer and other diseases. Curr. Opin. Mol. Ther. 8(6), 507–513 (2006)

    PubMed  CAS  Google Scholar 

  16. Novotny, M.V., Mechref, Y.: New hyphenated methodologies in high-sensitivity glycoprotein analysis. J. Sep. Sci. 28(15), 1956–1968 (2005)

    Article  PubMed  CAS  Google Scholar 

  17. Raman, R., et al.: Glycomics: an integrated systems approach to structure–function relationships of glycans. Nat. Methods 2(11), 817–824 (2005)

    Article  PubMed  CAS  Google Scholar 

  18. An, H.J., et al.: Profiling of glycans in serum for the discovery of potential biomarkers for ovarian cancer. J. Proteome Res. 5(7), 1626–1635 (2006)

    Article  PubMed  CAS  Google Scholar 

  19. Kirmiz, C., et al.: A serum glycomics approach to breast cancer biomarkers. Mol. Cell Proteomics 6, 43–55 (2007)

    PubMed  CAS  Google Scholar 

  20. Kyselova, Z., et al.: Alterations in the serum glycome due to metastatic prostate cancer. J. Proteome Res. 6, 1822–1832 (2007)

    Article  PubMed  CAS  Google Scholar 

  21. Kang, P., et al.: Solid-phase permethylation of glycans for mass spectrometric analysis. Rapid Commun. Mass Spectrom. 19(23), 3421–3428 (2005)

    Article  PubMed  CAS  Google Scholar 

  22. Mechref, Y., Kang, P., Novotny, M.V.: Differentiating structural isomers of sialylated glycans by matrix-assisted laser desorption/ionization time-of-flight/time-of-flight tandem mass spectrometry. Rapid Commun. Mass Spectrom. 20(8), 1381–1389 (2006)

    Article  PubMed  CAS  Google Scholar 

  23. Huang, Y., et al.: Matrix-assisted laser desorption/ionization mass spectrometry compatible beta-elimination of O-linked oligosaccharides. Rapid Commun. Mass Spectrom. 16(12), 1199–1204 (2002)

    Article  PubMed  CAS  Google Scholar 

  24. Huang, Y., Mechref, Y., Novotny, M.V.: Microscale nonreductive release of O-linked glycans for subsequent analysis through MALDI mass spectrometry and capillary electrophoresis. Anal. Chem. 73(24), 6063–6069 (2001)

    Article  PubMed  CAS  Google Scholar 

  25. Wada, Y., Azadi, P., Costello, C., Dell, E.A., Dwek, R.A., Geyer, H., et al.: Glycobiology 17, 411–422 (2007)

    Article  PubMed  CAS  Google Scholar 

  26. Kui Wong, N., et al.: Characterization of the oligosaccharides associated with the human ovarian tumor marker CA125. J. Biol. Chem. 278(31), 28619–28634 (2003)

    Article  PubMed  CAS  Google Scholar 

  27. Nuck, R., et al.: Comparative study of high-mannose-type oligosaccharides in membrane glycoproteins of rat hepatocytes and different rat hepatoma cell lines. Eur. J. Biochem. 216(1), 215–221 (1993)

    Article  PubMed  CAS  Google Scholar 

  28. Asada, M., et al.: Increased expression of highly branched N-glycans at cell surface is correlated with the malignant phenotypes of mouse tumor cells. Cancer Res. 57(6), 1073–1080 (1997)

    PubMed  CAS  Google Scholar 

  29. Fuster, M.M., et al.: A disaccharide precursor of sialyl Lewis X inhibits metastatic potential of tumor cells. Cancer Res. 63(11), 2775–2781 (2003)

    PubMed  CAS  Google Scholar 

  30. Alper, J.: Glycobiology. Turning sweet on cancer. Science 301(5630), 159–160 (2003)

    Article  PubMed  CAS  Google Scholar 

  31. Brown, J.R., et al.: A disaccharide-based inhibitor of glycosylation attenuates metastatic tumor cell dissemination. Clin. Cancer Res. 12(9), 2894–2901 (2006)

    Article  PubMed  CAS  Google Scholar 

  32. Soule, H.D., et al.: Isolation and characterization of a spontaneously immortalized human breast epithelial cell line, MCF-10. Cancer Res. 50(18), 6075–6086 (1990)

    PubMed  CAS  Google Scholar 

  33. Nishizuka, S., et al.: Proteomic profiling of the NCI-60 cancer cell lines using new high-density reverse-phase lysate microarrays. Proc. Natl. Acad. Sci. U. S. A. 100(24), 14229–14234 (2003)

    Article  PubMed  CAS  Google Scholar 

  34. Bradford, M.M.: A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72, 248–254 (1976)

    Article  PubMed  CAS  Google Scholar 

  35. Verhoeckx, K.C., et al.: A combination of proteomics, principal component analysis and transcriptomics is a powerful tool for the identification of biomarkers for macrophage maturation in the U937 cell line. Proteomics 4(4), 1014–1028 (2004)

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by grants No. GM24349 from the National Institute of Health (NIH) and No. RR018942 from NCRR/NIH as a contribution from the National Center for Glycomics and Glycoproteomics at Indiana University. The initial stages of this investigation were also aided by a grant from the twenty-first Century Fund of the State of Indiana.

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Authors and Affiliations

  1. Department of Chemistry, Indiana University, 800 E. Kirkwood Ave., Bloomington, IN, 47405, USA

    John A. Goetz, Yehia Mechref, Pilsoo Kang & Milos V. Novotny

  2. National Center for Glycomics and Glycoproteomics, Indiana University, Bloomington, IN, 47405, USA

    John A. Goetz, Yehia Mechref, Meei-Huey Jeng & Milos V. Novotny

  3. Department of Medicine, Indiana University, Indianapolis, IN, 46202, USA

    Meei-Huey Jeng

Authors
  1. John A. Goetz
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  2. Yehia Mechref
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  3. Pilsoo Kang
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  4. Meei-Huey Jeng
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  5. Milos V. Novotny
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Correspondence to Yehia Mechref or Milos V. Novotny.

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Goetz, J.A., Mechref, Y., Kang, P. et al. Glycomic profiling of invasive and non-invasive breast cancer cells. Glycoconj J 26, 117–131 (2009). https://doi.org/10.1007/s10719-008-9170-4

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  • DOI: https://doi.org/10.1007/s10719-008-9170-4

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