Analysis of Phosphoproteome Changes in MDA‑ MB‑ 468 Cancer Cell Line in Response to Expression of p63 Isoforms Using Mass Spectrometry
Authors:
P. Dvořáková; M. Nekulová; J. Holčáková; B. Vojtěšek; L. Hernychová
Authors place of work:
Regionální centrum aplikované molekulární onkologie, Masarykův onkologický ústav, Brno
Published in the journal:
Klin Onkol 2015; 28(Supplementum 2): 11-19
doi:
https://doi.org/10.14735/amko20152S11
Summary
Compared to normal cells, tumor cells can show different activity of kinases and phosphatases resulting in altered phosphorylation states of proteins affecting their activity within various signaling pathways. The detection of these alterations is essential for development of targeted therapy based on activation/ inhibition of specific signaling pathways. Various methods can be used for detection of protein phosphorylation; however, a comprehensive assessment of phosphoproteome is performed by mass spectrometry. The differences in phosphoproteome were studied using MDA MB 468 cell line (with incorporated genes encoding isoforms of p63) derived from breast carcinoma. Cells with tetracycline‑induced expression of the p63 isoforms were compared to control cells with wild‑type expression. Denatured proteins from cell lysates were digested to peptides, enriched for phosphopeptides and subsequently separated using liquid chromatograph coupled with mass spectrometer Orbitrap Elite. Three different mass spectrometric methods were used for each sample analysis to find the most suitable conditions for the detection of phosphorylated peptides. Then phosphoproteins were identified and quantified. The number of identified phosphoproteins using all chosen mass spectrometric methods was similar; however, each method showed several unique phosphorylated proteins. Our analysis revealed that both p63 isoforms (TAp63α a ∆Np63α) mainly affected phosphorylation of proteins associated with RNA splicing in MDA MB 468 cells.
Key words:
mass spectrometry – phosphoproteins – signaling pathways – p63 isoforms – breast cancer
This study was supported by the European Regional Development Fund and the State Budget of the Czech Republic (RECAMO, CZ.1.05/2.1.00/03.0101), by the project MEYS – NPS I – LO1413, by MH CZ – DRO (MMCI, 002 09805), by IGA NT/14602-3/2013 and BBMRI_CZ (LM2010004).
The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.
The Editorial Board declares that the manuscript met the ICMJE “uniform requirements” for biomedical papers.
Submitted:
9. 4. 2015
Accepted:
20. 7. 2015
Zdroje
1. Yates JR, Shabaz M, Heck AJ. Prosphoproteomics. Anal Chem 2014; 86(3): 1313. doi: 10.1021/ ac404019p.
2. Reimand J, Wagih O, Bader GD. The mutational landscape of phosphorylation signaling in cancer. Sci Rep 2013; 3: 2651. doi: 10.1038/ srep02651.
3. Zhang J, Yang PL, Gray NS. Targeting cancer with small molecule kinase inhibitors. Nat Rev Cancer 2009; 9(1): 28– 39. doi: 10.1038/ nrc2559.
4. Oda Y, Huang K, Cross FR et al. Accurate quantitation of protein expression and site‑ specific phosphorylation. Proc Natl Acad Sci USA 1999; 96(12): 6591– 6596.
5. Gygi SP, Rist B, Gerber SA et al. Quantitative analysis of complex protein mixtures using isotope‑ coded affinity tags. Nature Biotechnol 1999; 17(10): 994– 999.
6. Thompson A, Schafer J, Kuhn K et al. Tandem mass tag: a novel qunatification strategy for comparative analysis of complex protein mixture by MS/ MS. Anal Chem 2003; 75(8): 1895– 1904.
7. Fíla J, Honys D. Enrichment techniques employed in phosphoproteomics. Amino Acids 2011; 43(3): 1025– 1047. doi: 10.1007/ s00726‑ 011‑ 1111‑ z.
8. Pinkse MW, Uitto PM, Hilhorst MJ et al. Selective isolation at the femtomole level of phosphopeptides from proteolytic digests using 2D‑ nano LC‑ ESI‑ MS/ MS and titanium oxide precolumns. Anal Chem 2004; 76(14): 3935– 3943.
9. Ficarro SB, McCleland ML, Stukenberg PT et al. Phosphoproteome analysis by mass spectrometry and its application to Saccharomyces cerevisiae. Nature Biotechnol 2002; 20(3): 301– 305.
10. Mann M, Ong S, Grønborg M et al. Analysis of protein phosphorylation using mass spectrometry: deciphering the phosphoproteome. Trends Biotechnol 2002; 20(6): 261– 268.
11. Hoffert JD, Knepper MA. Taking aim at shotgun phosphoproteomics. Anal Biochem 2008; 375(1): 1– 10.
12. Boersema PJ, Mohammed S, Heck AJ. Phosphopeptide fragmentation and analysis by mass spectrometry. J Mass Specrom 2009; 44(6): 861– 878. doi: 10.1002/ jms.1599.
13. MaxQuant.org [homepage on the Internet]. MaxQuant. Max planck institute of biochemistry. Martinsried: Germany; c2015 [cited 2015 March 30]. Available from: http:/ / www.maxquant.org/ .
14. Taus T, Köcher T, Pichler P et al. Universal and confident phosphorylation site localization using phospho RS. J Proteome Res 2011; 10(12): 5354– 5362. doi: 10.1021/ pr200611n.
15. Pjechová M, Hernychová L, Tomašec P et al. Analýza fosfoproteínov a signálních dráh kvantitatívno‑ proteomickými metodami. Klin Onkol 2014; 27 (Suppl 1): S116– S120. doi: 10.14735/ amko20141S116.
16. Yang A, Schweitzer R, Sun D et al. p63 is essential for regenerative proliferation in limb, craniofacial and epithelial development. Nature 1999; 398(6729): 714– 718.
17. Hibi K, Trink B, Patturajan M et al. AIS is an oncogene amplified in squamous cell carcinoma. Proc Natl Acad Sci U S A 2000; 97(10): 5462– 5467.
18. Nylander K, Vojtesek B, Nenutil R et al. Differential expression of p63 isoforms in normal tissues and neoplastic cells. J Pathol 2002; 198(4): 417– 427.
19. Leong CO, Vidnovic N, DeYoung MP et al. The p63/ p73 network mediates chemosensitivity to cisplatin in a biologically defined subset of primary breast cancers. J Clin Invest 2007; 117(5): 1370– 1380.
20. Danilov AV, Neupane D, Nagaraja AS et al. Delta-Np63alpha‑ mediated induction of epidermal growth factor receptor promotes pancreatic cancer cell growth and chemoresistance. PLoS One 2011; 6(10): e26815. doi: 10.1371/ journal.pone.0026815.
21. Ramsey MR, Wilson C, Ory B et al. FGFR2 signaling underlies p63 oncogenic function in squamous cell carcinoma. J Clin Invest 2013; 123(8): 3525– 3538. doi: 10.1172/ JCI68899.
22. Wu N, Rollin J, Masse I et al. p63 regulates human keratinocyte proliferation via MYC‑ regulated gene network and differentiation commitment through cell adhesion‑related gene network. J Biol Chem 2012; 287(8): 5627– 5638. doi: 10.1074/ jbc.M111.328120.
23. Moll UM, Slade N. p63 and p73: roles in development and tumor formation. Mol Cancer Res 2004; 2(7): 371– 386.
24. Su X, Chakravarti D, Cho MS et al. TAp63 suppresses metastasis through coordinate regulation of dicer and miRNAs. Nature 2010; 467(7318): 986– 990. doi: 10.1038/ nature09459.
25. Yang A, Kaghad M, Wang Y et al. p63, a p53 homolog at 3q27- 29, encodes multiple products with transactivating, death‑ inducing, and dominant‑ negative activities. Mol Cell 1998; 2(3): 305– 316.
26. Ghioni P, Bolognese F, Duijf PH et al. Complex transcriptional effects of p63 isoforms: identification of novel activation and repression domains. Mol Cell Biol 2002; 22(24): 8659– 8668.
27. Wisniewski JR, Zougman A, Nagaraj N et al. Universal sample preparation method for proteome analysis. Nat Methods 2009; 6(5): 359– 362. doi: 10.1038/ nmeth.1322.
28. Aryal UK, Ross AR. Enrichment and analysis of phosphopeptides under different experimental conditions using titanium dioxide affinity chromatography and mass spektrometry. Rapid Commun Mass Spectrom 2010; 24(2): 219– 231. doi: 10.1002/ rcm.4377.
29. UniProt.org [homepage on the Internet]. UniProt, c2002– 2015 [cited 2015 March 30]. Available from: http:/ / www.uniprot.org/ .
30. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nature Protoc 2009; 4(1): 44– 57. doi: 10.1038/ nprot.2008.211.
31. Huang Y, Jeong JS, Okamura J et al. Global tumor protein p53/ p63 interactome. Cell Cycle 2012; 11(12): 2367– 2379. doi: 10.4161/ cc.20863.
32. Huang da DW, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 2009; 37(1): 1– 13. doi: 10.1093/ nar/ gkn923.
33. Amoresano A, Di Costanzo A, Leo G et al. Identification of deltaNp63alpha protein interactions by mass spectrometry. J Proteome Res 2010; 9(4): 2042– 2048. doi: 10.1021/ pr9011156.
34. Moore MJ, Wang Q, Kennedy CJ et al. An alternative splicing network links cell‑ cycle control to apoptosis. Cell 2010; 142(4): 625– 636. doi: 10.1016/ j.cell.2010.07.019.
35. David CJ, Manley JL. Alternative pre‑mRNA splicing regulation in cancer: pathways and programs unhinged. Genes Dev 2010; 24(21): 2343– 2364. doi: 10.1101/ gad.1973010.
36. Schwerk C, Schulze‑ Osthoff K. Regulation of apoptosis by alternative pre‑mRNA splicing. Mol Cell 2005; 19(1): 1– 13.
37. Liu S, Cheng C. Alternative RNA splicing and cancer. Wiley Interdiscip Rev RNA 2013; 4(5): 547– 566. doi: 10.1002/ wrna.1178.
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