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Proteomics Analysis of Colorectal Cancer Cells

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Colorectal Cancer

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1765))

Abstract

Proteomics allows the simultaneous detection and identification of thousands of proteins within a sample. Here, we describe a quantitative method to compare protein expression and subcellular localization of different cell lines representative of different stages of colorectal cancer using stable isotope labeling with amino acids in culture, or SILAC. We also describe a biochemical fractionation approach to separate different cellular compartments and the necessary steps to obtain a specific proteomic profile of each cell line. This technique enables a comprehensive proteomic analysis of cancer cell lines and the identification of pathways that are deregulated in different cancer cell lines.

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References

  1. James P (1997) Protein identification in the post-genome era: the rapid rise of proteomics. Q Rev Biophys 30(4):279–331

    Article  CAS  PubMed  Google Scholar 

  2. Kenyon GL, DeMarini DM, Fuchs E, Galas DJ, Kirsch JF, Leyh TS, Moos WH, Petsko GA, Ringe D, Rubin GM, Sheahan LC, National Research Council Steering Committee (2002) Defining the mandate of proteomics in the post-genomics era: workshop report. Mol Cell Proteomics 1(10):763–780

    CAS  PubMed  Google Scholar 

  3. Patterson SD, Aebersold RH (2003) Proteomics: the first decade and beyond. Nat Genet 33(Suppl):311–323

    Article  CAS  PubMed  Google Scholar 

  4. Harsha HC, Molina H, Pandey A (2008) Quantitative proteomics using stable isotope labeling with amino acids in cell culture. Nat Protoc 3(3):505–516

    Article  CAS  PubMed  Google Scholar 

  5. Boisvert FM, Lam YW, Lamont D, Lamond AI (2010) A quantitative proteomics analysis of subcellular proteome localization and changes induced by DNA damage. Mol Cell Proteomics 9(3):457–470

    Article  CAS  PubMed  Google Scholar 

  6. Drissi R, Dubois ML, Boisvert FM (2013) Proteomics methods for subcellular proteome analysis. FEBS J 280:5626–5634

    Article  CAS  PubMed  Google Scholar 

  7. Hung MC, Link W (2011) Protein localization in disease and therapy. J Cell Sci 124(Pt.20):3381–3392

    Article  CAS  PubMed  Google Scholar 

  8. Mathieu AA, Ohl-Séguy E, Dubois ML, Jean D, Jones C, Boudreau F, Boisvert FM (2016) Subcellular proteomics analysis of different stages of colorectal cancer cell lines. Proteomics 23:3009–3018

    Article  Google Scholar 

  9. Leibovitz A, Stinson JC, McCombs WB, McCoy CE, Mazur KC, Mabry ND (1976) Classification of human colorectal adenocarcinoma cell lines. Cancer Res 36(12):4562–4569

    CAS  PubMed  Google Scholar 

  10. Fogh J, Fogh JM, Orfeo T (1977) One hundred and twenty-seven cultured human tumor cell lines producing tumors in nude mice. J Natl Cancer Inst 59(1):221–226

    Article  CAS  PubMed  Google Scholar 

  11. Bendall SC, Hughes C, Stewart MH, Doble B, Bhatia M, Lajoie GA (2008) Prevention of amino acid conversion in SILAC experiments with embryonic stem cells. Mol Cell Proteomics 7(9):1587–1597

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Perreault N, Beaulieu JF (1996) Use of the dissociating enzyme thermolysin to generate viable human normal intestinal epithelial cell cultures. Exp Cell Res 224(2):354–364

    Article  CAS  PubMed  Google Scholar 

  13. Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26:1367–1372

    Article  CAS  PubMed  Google Scholar 

  14. Cox J, Matic I, Hilger M, Nagaraj N, Selbach M, Olsen JV, Mann M (2009) A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomics. Nat Protoc 4:698–705

    Article  CAS  PubMed  Google Scholar 

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Correspondence to François-Michel Boisvert .

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Chauvin, A., Boisvert, FM. (2018). Proteomics Analysis of Colorectal Cancer Cells. In: Beaulieu, JF. (eds) Colorectal Cancer. Methods in Molecular Biology, vol 1765. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7765-9_9

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  • DOI: https://doi.org/10.1007/978-1-4939-7765-9_9

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7764-2

  • Online ISBN: 978-1-4939-7765-9

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