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Use of High-Throughput Protein Array for Profiling of Differentially Expressed Proteins in Normal and Malignant Breast Tissue

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Abstract

cDNA arrays provide a powerful tool to identify gene expression pattern that are potentially associated with tumor invasion and metastasis. However, genes work at the protein level and, since the transcriptional activity of a gene does not necessarily reflect cellular protein expression, the identification and quantification of proteins is essential for the understanding of molecular events leading to malignant transformation. We have therefore employed a high-throughput protein microarray system which contains 378 well-characterized monoclonal antibodies in order to compare the gene expression pattern of malignant and adjacent normal breast tissue in a patient with primary breast cancer. Using this technique, we have identified a number of proteins that show increased expression levels in malignant breast tissues such as casein kinase Ie, p53, annexin XI, CDC25C, eIF-4E and MAP kinase 7. The expression of other proteins, such as the multifunctional regulator 14-3-3e was found to be decreased in malignant breast tissue, whereas the majority of proteins remained unchanged when compared to the corresponding non-malignant samples. The protein expression pattern was confirmed by immunohistochemistry, in which antibodies against 8 representative proteins known to be involved in carcinogenesis were employed in paraffin-embedded normal and malignant tissue sections deriving from the same patient. In each case, the results obtained by IHC matched the data obtained by antibody microarray system. Taken together, we have described for the first time a tumor cell specificity protein expression pattern by use of a novel commercially available antibody microarray system. We have thus demonstrated the feasibility of high-throughput protein arrays in the proteomic analysis of human breast tissue. We hypothesize that the use of protein arrays will not only increase our understanding of the molecular events, but could prove useful in evaluating prognosis and in determining optimal antineoplastic therapy.

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References

  1. Lockhart DJ, Winzeler EA: Genomics, gene expression and DNA arrays.Nature 405: 827–836, 2000

    Article  PubMed  Google Scholar 

  2. Young RA: Biomedical discovery with DNA arrays. Cell 102: 9–15, 2000

    Article  PubMed  Google Scholar 

  3. Ramaswamy S, Golub TR: DNA microarrays in clinical oncology. J Clin Oncol 20: 1932–1941, 2001

    Google Scholar 

  4. Shim C, Zhang W, Rhee CH, Lee JH: Profiling of differentially expressed genes in human primary cervical cancer by complementary DNA expression array. Clin Cancer Res 4: 3045–3050, 1998

    PubMed  Google Scholar 

  5. De Risi J, Penland L, Brown PO, Bittner ML, Meltzer PS, Ray M, Chen Y, Su YA, Trent JM: Use of cDNA microarray to analyse gene expression patterns in human cancer. Nat Genet 14: 457–460, 1996

    Article  PubMed  Google Scholar 

  6. Gygi SP, Rochon Y, Franza BR, Aebersold R: Correlation between protein and mRNA abundance in yeast. Mol Cell Biol 19: 1720–1730, 1999

    PubMed  Google Scholar 

  7. Steiner S, Witzmann FA: Proteomics: applications and opportunities in preclinical drug development. Electrophoresis 21: 2099–2104, 2000

    Article  PubMed  Google Scholar 

  8. Celis J, Kruhoffer M, Gromova I, Frederiksen C, Ostergaard M, Thykjaer T, Gromov P, Yu J, Palsdottir H, Magnusson N, Orntoft T: Gene expression profiling: monitoring transcription and translation products using DNA microarrays and proteomics. FEBS Lett 480: 2–16, 2000

    Article  PubMed  Google Scholar 

  9. Templin MF, Stoll D, Schrenk M, Traub PC, Vö hringer CF, Joos TO: Protein microarray technology. Drug Discovery Today 7: 815–822, 2002

    Article  PubMed  Google Scholar 

  10. Cahill D: Protein and antibody arrays and their medical applications. J Immunol Methods 250: 81–91, 2001

    Article  PubMed  Google Scholar 

  11. Zhu H, Bilgin M, Bangham R, Hall D, Casamayor A, Bertone P, Lan N, Jansen R, Bidlingmaier S, Houfek T, Mitchell T, Miller P, Dean RA, Gerstein M, Snyder M: Global analysis of protein activities using proteome chips. Science 293: 2101–2105, 2001

    Article  PubMed  Google Scholar 

  12. Walter G, Büssow K, Lueking A, Gö lker J: High–throughput protein arrays: prospects for molecular diagnostics. Trends Mol Med 8(6): 250–253, 2002

    Article  PubMed  Google Scholar 

  13. Kukar T, Eckenrode S, Gu Y, Lian W, Megginson M, She XJ, Wu D: Protein microarrays to detect protein–protein interactions using red and green fluorescent dyes. Anal Biochem 306: 50–54, 2002

    Article  PubMed  Google Scholar 

  14. Joos TA, Schrenk M, Hö pfl P, Kröger K, Chowdhury U, Stoll D, Schörner D, Dürr M, Herick K, Rupp S, Sohn K, Hämmerle H: A microarray enzyme–based immunosorbent assay for autoimmune diagnostics. Electrophoresis 21: 2641–2650, 2000

    Article  PubMed  Google Scholar 

  15. Haab B, Dunham MJ, Brown P: Protein microarrays for highly parallel detection and quantification of specific proteins and antibodies in complex solutions. Genome Biol 2: research0004.1–0004.13, 2001

  16. Huang RP, Huang R, Fan Y, Lin Y: Simultaneous detection of multiple cytokines from conditioned media and patient's sera by an antibody–based protein array system. Anal Biochem 294: 55–62, 2001

    Article  PubMed  Google Scholar 

  17. Sreekumar A, Mukesh K, Sooryanarayana V, Barrette TR, Debashis G, Lawrence TS, Chinnaiyan AM: Profiling of cancer cells using protein microarrays: Discovery of novel radiation–regulated proteins. Cancer Res 61: 7585–7593, 2001

    PubMed  Google Scholar 

  18. Hsu YT, Wolter KG, Youle RJ: Cytosol–to–membrane redistribution of Bax and Bcl–X(L) during apoptosis. Proc Natl Acad Sci USA 15(94): 3668–3672, 1997

    Article  Google Scholar 

  19. Reed JC: Bcl–2 and the regulation of programmed cell death. J Cell Biol 124(1–2): 1–6, 1994

    Article  PubMed  Google Scholar 

  20. Koeppen HK, Wright BD, Burt AD, Quirke P, McNicol AM, Dybdal NO, Sliwkowski MX, Hillan KJ: Overexpression of HER2/neu in solid tumours: An immunohistochemical survey. Histopathology 38: 96–104, 2001

    Article  PubMed  Google Scholar 

  21. Sainsbury JR, Farndon JR, Sherbet GV, Harris AL: Epidermal–growth–factor receptors and oestrogen receptors in human breast cancer. Lancet 16, 1(8425): 364–366, 1985

    Article  Google Scholar 

  22. Marchetti A, Buttitta F, Girlando S, Dalla Palma P, Pellegrini S, Fina P, Doglioni C, Bevilacqua G, Barbareschi M: Mdm2 gene alterations and mdm2 protein expression in breast carcinomas. J Pathol 175: 31–38, 1995

    PubMed  Google Scholar 

  23. Haitel A, Wiener HG, Blaschitz U, Marberger M, Susani M: Biologic behavior and p53 overexpression in multifocal renal cell carcinoma of clear cell type: An immunohistochemical study correlating grading, staging, and proliferation markers. Cancer 85: 1593–1598, 1999

    Article  PubMed  Google Scholar 

  24. El–Deiry WS, Tokino T, Waldman T, Oliner JD, Velculescu VE, Burrell M, Hill DE, Healy E, Rees JL, Hamilton SR: Topological control of p21WAF1/CIP1 expression in normal and neoplastic tissues. Cancer Res 55: 2910–2919, 1995

    PubMed  Google Scholar 

  25. McCormick D, Yu C, Hobbs C, Hall PA: The relevance of antibody concentration to the immunohistological quanti–fication of cell proliferation–associated antigens. Histopathology 22: 543–547, 1993

    PubMed  Google Scholar 

  26. Remmele W, Schicketanz KH: Immunohistochemical determination of estrogen and progesterone receptor content in human breast cancer. Computer–assisted image analysis (QIC score) vs. subjective grading (IRS). Pathol Res Pract 189: 862–866, 1993

    PubMed  Google Scholar 

  27. Li BD, Liu L, Dawson M, De Benedetti A: Overexpression of eukaryotic initiation factor 4E (eIF4E) in breast carcinoma. Cancer 79: 2385–2390, 1997

    Article  PubMed  Google Scholar 

  28. Li BD, McDonald JC, Nassar R, De Benedetti A: Clinical outcome in stage I to III breast carcinoma and eIF4E overexpression. Ann Surg 227: 756–761, 1998

    Article  PubMed  Google Scholar 

  29. Kerekatte V, Smiley K, Hu B, Smith A, Gelder F, De Benedetti A: The proto–oncogene/translation factor eIF4E: A survey of its expression in breast carcinomas. Int J Cancer 64: 27–31, 1995

    PubMed  Google Scholar 

  30. Jansen RL, Joosten–Achjanie SR, Volovics A, Arends JW, Hupperets PS, Hillen HF, Schouten HC: Relevance of the expression of bcl–2 in combination with p53 as a prognostic factor in breast cancer. Anticancer Res 18: 4455–4462, 1998

    PubMed  Google Scholar 

  31. Liu S, Edgerton S, Moore D, Shi Q, Thor A: Abberant expression of p21WAF1/CIP1 and p53 in human primary breast cancers: Associations with clinical, histological, molecular and outcome data. Breast Cancer Res Treat 46: 29, 1997

    Google Scholar 

  32. Elledge RM, Allred CD: Prognostic and predictive value of p53 and p21 in breast cancer. Breast Cancer Res Treat 52: 79–98, 1998

    Article  PubMed  Google Scholar 

  33. Slamon DJ, Clark GM, Wong SG, Levin WJ, Ullrich A, McGuire WL: Human breast cancer: Correlation of relapse and survival with amplification of the HER–2/neu oncogene. Science 235: 177–182, 1987

    PubMed  Google Scholar 

  34. Galaktionov K, Lee AK, Eckstein J, Draetta G, Meckler J, Loda M, Beach D: CDC25 phosphatases as potential human oncogenes. Science 269(5230): 1575–1577, 1995

    PubMed  Google Scholar 

  35. Lazo JS, Aslan DC, Southwick EC, Cooley KA, Ducruet AP, Joo B, Vogt A, Wipf P: Discovery and biological evaluation of a new family of potent inhibitors of the dual specificity protein phosphatase Cdc25. J Med Chem 44: 4042–4049, 2001

    Article  PubMed  Google Scholar 

  36. Fish KJ, Cegielska A, Getman ME, Landes GM, Virshup DM: Isolation and characterization of human casein kinase I epsilon (CKI), a novel member of the CKI gene family. J Biol Chem 270: 14875–14883, 1995

    Google Scholar 

  37. Masters SC, Haian Fu: 14–3–3 proteins mediate an essential anti–apoptotic signal. J Biol Chem 276: 45193–45200, 2001

    Article  PubMed  Google Scholar 

  38. Ferguson AT, Evron E, Umbricht CB, Pandita TK, Chan TA, Hermeking H, Marks JR, Lambers AR, Futreal PA, Stampfer MR, Sukumar S: High frequency of hypermethylation at the 14–3–3 sigma locus leads to gene silencing in breast cancer. Proc Natl Acad Sci USA 97: 6049–6054, 2000

    Article  PubMed  Google Scholar 

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Hudelist, G., Pacher-zavisin, M., Singer, C. et al. Use of High-Throughput Protein Array for Profiling of Differentially Expressed Proteins in Normal and Malignant Breast Tissue. Breast Cancer Res Treat 86, 283–293 (2004). https://doi.org/10.1023/B:BREA.0000036901.16346.83

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  • DOI: https://doi.org/10.1023/B:BREA.0000036901.16346.83

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