Skip to main content
SpringerLink
Log in

Proteomic Profiling of Hsp90 Inhibitors

  • Protocol
  • First Online:
Chaperones

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1709))

Abstract

Mass spectrometry assays demonstrate that Hsp90 inhibitors alter the expression of approximately one-quarter of the assayable proteome in mammalian cells. These changes are extraordinarily robust and reproducible, making “proteomics profiling” the gold standard for validating the effects of new Hsp90 inhibitors on cultured cells. Proteomics assays can also suggest novel hypotheses regarding drug mechanisms. To assist investigators in adopting this approach, this Chapter provides detailed protocols for conducting simple proteomics assays of Hsp90 inhibition. The protocols present a robust label-free approach that utilizes pre-fractionation of protein samples by SDS-PAGE, thereby providing reasonably good penetration into the proteome while addressing common issues with sample quality. The actual programming and operation of liquid chromatography-tandem mass spectrometers is not covered, but expectations for achievable performance are discussed, as are alternative approaches, common challenges, and software for data analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Che Y, Best OG, Zhong L, Kaufman KL, Mactier S, Raftery M, Graves LM, Mulligan SP, Christopherson RI (2013) Hsp90 inhibitor SNX-7081 dysregulates proteins involved with DNA repair and replication and the cell cycle in human chronic lymphocytic leukemia (CLL) cells. J Proteome Res 12(4):1710–1722. https://doi.org/10.1021/pr301055y

    Article  CAS  PubMed  Google Scholar 

  2. Fierro-Monti I, Echeverria P, Racle J, Hernandez C, Picard D, Quadroni M (2013) Dynamic impacts of the inhibition of the molecular chaperone Hsp90 on the T-cell proteome have implications for anti-cancer therapy. PLoS One 8(11):e80425. https://doi.org/10.1371/journal.pone.0080425

    Article  PubMed  PubMed Central  Google Scholar 

  3. Jacobson C, Kopp N, Layer JV, Redd RA, Tschuri S, Haebe S, van Bodegom D, Bird L, Christie AL, Christodoulou A, Saur A, Tivey T, Zapf S, Bararia D, Zimber-Strobl U, Rodig SJ, Weigert O, Weinstock DM (2016) HSP90 inhibition overcomes ibrutinib resistance in mantle cell lymphoma. Blood. https://doi.org/10.1182/blood-2016-04-711176

  4. Samant RS, Clarke PA, Workman P (2012) The expanding proteome of the molecular chaperone HSP90. Cell Cycle 11(7):1301–1308. https://doi.org/10.4161/cc.19722

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Sharma K, Vabulas RM, Macek B, Pinkert S, Cox J, Mann M, Hartl FU (2012) Quantitative proteomics reveals that Hsp90 inhibition preferentially targets kinases and the DNA damage response. Mol Cell Proteomics 11(3):M111.014654. https://doi.org/10.1074/mcp.M111.014654

    Article  PubMed  Google Scholar 

  6. Voruganti S, Lacroix JC, Rogers CN, Rogers J, Matts RL, Hartson SD (2013) The anticancer drug AUY922 generates a proteomics fingerprint that is highly conserved among structurally diverse Hsp90 inhibitors. J Proteome Res 12(8):3697–3706. https://doi.org/10.1021/pr400321x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Wu Z, Gholami AM, Kuster B (2012) Systematic identification of the HSP90 candidate regulated proteome. Mol Cell Proteomics 11(6):M111.016675. https://doi.org/10.1074/mcp.M111.016675

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Hartson SD, Matts RL (2012) Approaches for defining the Hsp90-dependent proteome. Biochim Biophys Acta 1823(3):656–667. https://doi.org/10.1016/j.bbamcr.2011.08.013

    Article  CAS  PubMed  Google Scholar 

  9. Whitesell L, Mimnaugh EG, De Costa B, Myers CE, Neckers LM (1994) Inhibition of heat shock protein HSP90-pp60v-src heteroprotein complex formation by benzoquinone ansamycins: essential role for stress proteins in oncogenic transformation. Proc Natl Acad Sci U S A 91(18):8324–8328

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Schulte TW, Blagosklonny MV, Ingui C, Neckers L (1995) Disruption of the Raf-1-Hsp90 molecular complex results in destabilization of Raf-1 and loss of Raf-1-Ras association. J Biol Chem 270(41):24585–24588

    Article  CAS  PubMed  Google Scholar 

  11. Smith DF, Whitesell L, Nair SC, Chen S, Prapapanich V, Rimerman RA (1995) Progesterone receptor structure and function altered by geldanamycin, an hsp90-binding agent. Mol Cell Biol 15(12):6804–6812

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Hartson SD, Barrett DJ, Burn P, Matts RL (1996) Hsp90-mediated folding of the lymphoid cell kinase p56lck. Biochemistry 35(41):13451–13459. https://doi.org/10.1021/bi961332c

    Article  CAS  PubMed  Google Scholar 

  13. Schulte TW, Blagosklonny MV, Romanova L, Mushinski JF, Monia BP, Johnston JF, Nguyen P, Trepel J, Neckers LM (1996) Destabilization of Raf-1 by geldanamycin leads to disruption of the Raf-1-MEK-mitogen-activated protein kinase signalling pathway. Mol Cell Biol 16(10):5839–5845

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Aebersold R, Mann M (2016) Mass-spectrometric exploration of proteome structure and function. Nature 537(7620):347–355. https://doi.org/10.1038/nature19949

    Article  CAS  PubMed  Google Scholar 

  15. Blagoev B, Ong SE, Kratchmarova I, Mann M (2004) Temporal analysis of phosphotyrosine-dependent signaling networks by quantitative proteomics. Nat Biotechnol 22(9):1139–1145. https://doi.org/10.1038/nbt1005

    Article  CAS  PubMed  Google Scholar 

  16. Hubner NC, Ren S, Mann M (2008) Peptide separation with immobilized pI strips is an attractive alternative to in-gel protein digestion for proteome analysis. Proteomics 8(23–24):4862–4872. https://doi.org/10.1002/pmic.200800351

    Article  CAS  PubMed  Google Scholar 

  17. Richards AL, Merrill AE, Coon JJ (2015) Proteome sequencing goes deep. Curr Opin Chem Biol 24:11–17. https://doi.org/10.1016/j.cbpa.2014.10.017

    Article  CAS  PubMed  Google Scholar 

  18. Ong SE, Blagoev B, Kratchmarova I, Kristensen DB, Steen H, Pandey A, Mann M (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol Cell Proteomics 1(5):376–386

    Article  CAS  PubMed  Google Scholar 

  19. Batth TS, Olsen JV (2016) Offline high pH reversed-phase peptide fractionation for deep phosphoproteome coverage. Methods Mol Biol 1355:179–192. https://doi.org/10.1007/978-1-4939-3049-4_12

    Article  CAS  PubMed  Google Scholar 

  20. Lau KW, Jones AR, Swainston N, Siepen JA, Hubbard SJ (2007) Capture and analysis of quantitative proteomic data. Proteomics 7(16):2787–2799. https://doi.org/10.1002/pmic.200700127

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Remily-Wood ER, Liu RZ, Xiang Y, Chen Y, Thomas CE, Rajyaguru N, Kaufman LM, Ochoa JE, Hazlehurst L, Pinilla-Ibarz J, Lancet J, Zhang G, Haura E, Shibata D, Yeatman T, Smalley KS, Dalton WS, Huang E, Scott E, Bloom GC, Eschrich SA, Koomen JM (2011) A database of reaction monitoring mass spectrometry assays for elucidating therapeutic response in cancer. Proteomics Clin Appl 5(7–8):383–396. https://doi.org/10.1002/prca.201000115

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Hartson SD, Matts RL (1994) Association of Hsp90 with cellular Src-family kinases in a cell-free system correlates with altered kinase structure and function. Biochemistry 33(30):8912–8920

    Article  CAS  PubMed  Google Scholar 

  23. Cox J, Hein MY, Luber CA, Paron I, Nagaraj N, Mann M (2014) Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol Cell Proteomics 13(9):2513–2526. https://doi.org/10.1074/mcp.M113.031591

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. 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(12):1367–1372. https://doi.org/10.1038/nbt.1511

    Article  CAS  PubMed  Google Scholar 

  25. Beck S, Michalski A, Raether O, Lubeck M, Kaspar S, Goedecke N, Baessmann C, Hornburg D, Meier F, Paron I, Kulak NA, Cox J, Mann M (2015) The impact II, a very high-resolution quadrupole time-of-flight instrument (QTOF) for deep shotgun proteomics. Mol Cell Proteomics 14(7):2014–2029. https://doi.org/10.1074/mcp.M114.047407

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Tyanova S, Temu T, Sinitcyn P, Carlson A, Hein MY, Geiger T, Mann M, Cox J (2016) The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat Methods 13(9):731–740. https://doi.org/10.1038/nmeth.3901

    Article  CAS  PubMed  Google Scholar 

  27. Diz AP, Carvajal-Rodriguez A, Skibinski DO (2011) Multiple hypothesis testing in proteomics: a strategy for experimental work. Mol Cell Proteomics 10(3):M110.004374. https://doi.org/10.1074/mcp.M110.004374

    Article  PubMed  Google Scholar 

  28. Coscia F, Watters KM, Curtis M, Eckert MA, Chiang CY, Tyanova S, Montag A, Lastra RR, Lengyel E, Mann M (2016) Integrative proteomic profiling of ovarian cancer cell lines reveals precursor cell associated proteins and functional status. Nat Commun 7:12645. https://doi.org/10.1038/ncomms12645

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Cristobal A, Hennrich ML, Giansanti P, Goerdayal SS, Heck AJ, Mohammed S (2012) In-house construction of a UHPLC system enabling the identification of over 4000 protein groups in a single analysis. Analyst 137(15):3541–3548. https://doi.org/10.1039/c2an35445d

    Article  CAS  PubMed  Google Scholar 

  30. Hebert AS, Richards AL, Bailey DJ, Ulbrich A, Coughlin EE, Westphall MS, Coon JJ (2014) The one hour yeast proteome. Mol Cell Proteomics 13(1):339–347. https://doi.org/10.1074/mcp.M113.034769

    Article  CAS  PubMed  Google Scholar 

  31. Pirmoradian M, Budamgunta H, Chingin K, Zhang B, Astorga-Wells J, Zubarev RA (2013) Rapid and deep human proteome analysis by single-dimension shotgun proteomics. Mol Cell Proteomics 12(11):3330–3338. https://doi.org/10.1074/mcp.O113.028787

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Sacco F, Silvestri A, Posca D, Pirro S, Gherardini PF, Castagnoli L, Mann M, Cesareni G (2016) Deep proteomics of breast cancer cells reveals that metformin rewires signaling networks away from a pro-growth state. Cell Syst 2(3):159–171. https://doi.org/10.1016/j.cels.2016.02.005

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Biochemistry and Molecular Biology, Oklahoma State University, Stillwater, OK, 74078, USA

    Sudhakar Voruganti, Jake T. Kline, Maurie J. Balch, Janet Rogers, Robert L. Matts & Steven D. Hartson

  2. Bristol-Myers Squibb, Pennington, NJ, USA

    Sudhakar Voruganti

Authors
  1. Sudhakar Voruganti
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jake T. Kline
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Maurie J. Balch
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Janet Rogers
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Robert L. Matts
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Steven D. Hartson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Steven D. Hartson .

Editor information

Editors and Affiliations

  1. Department of Radiation, Oncology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA

    Stuart K. Calderwood

  2. Department of Urology, Weis Center for Research, Geisinger Clinic, Danville, Pennsylvania, USA

    Thomas L. Prince

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Voruganti, S., Kline, J.T., Balch, M.J., Rogers, J., Matts, R.L., Hartson, S.D. (2018). Proteomic Profiling of Hsp90 Inhibitors. In: Calderwood, S., Prince, T. (eds) Chaperones. Methods in Molecular Biology, vol 1709. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7477-1_11

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-7477-1_11

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7476-4

  • Online ISBN: 978-1-4939-7477-1

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation