Skip to main content
SpringerLink
Log in

Utilization of Proteomic Technologies for Precision Oncology Applications

  • Chapter
  • First Online:
Precision Medicine in Cancer Therapy

Part of the book series: Cancer Treatment and Research ((CTAR,volume 178))

Abstract

Genomic analysis of tumor specimens has revealed that cancer is fundamentally a proteomic disease at the functional level: driven by genomically defined derangements, but selected for in the proteins that are encoded and the aberrant activation of signaling and biochemical networks. This activation is measured by posttranslational modifications such as phosphorylation and other modifications that modulate cellular signaling, and these events cannot be effectively measured by genomic analysis alone. Moreover, these signaling networks by and large represent the targets for many FDA-approved and experimental molecularly targeted therapeutics. Consequently, it is important that we consider new classification schemas for oncology based not on tumor site of origin or histology under the microscope but on the functional protein signaling architecture. There are numerous proteomic technologies that could be discussed from a purely technological standpoint, but this chapter will concentrate on an overview of the main proteomic technologies available for conducting protein pathway activation analysis of clinical specimens such as multiplex immunoassays, phospho-specific flow cytometry, reverse phase protein microarrays, quantitative immunohistochemistry, and mass spectrometry. This chapter will focus on the application of these technologies to cancer-based clinical studies evaluating prognostic/predictive markers or for stratifying patients to personalized treatments.

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

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 16.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 129.99
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

References

  1. Lee CK, Brown C, Gralla RJ, Hirsh V, Thongprasert S et al (2013) Impact of EGFR inhibitor in non-small cell lung cancer on progression-free and overall survival: a meta-analysis. J Natl Cancer Inst 105(9):595–605

    Article  CAS  PubMed  Google Scholar 

  2. Rothschild SI, Gautschi O (2013) Crizotinib in the treatment of non-small-cell lung cancer. Clin Lung Cancer. 14(5):473–480

    Article  CAS  PubMed  Google Scholar 

  3. Rexer BN, Arteaga CL (2013) Optimal targeting of HER2-PI3K signaling in breast cancer: mechanistic insights and clinical implications. Cancer Res 73(13):3817–3820

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Cheng S, Koch WH, Wu L (2012) Co-development of a companion diagnostic for targeted cancer therapy. N Biotechnol 29(6):682–688

    Article  CAS  PubMed  Google Scholar 

  5. Janku F, Broaddus R, Bakkar R, Hong DS, Stepanek V et al (2012) PTEN assessment and PI3K/mTOR inhibitors: importance of simultaneous assessment of MAPK pathway aberrations. In: ASCO annual meeting, Abstract 10510, presented 5 June 2012

    Google Scholar 

  6. Ganesan P, Janku F, Naing A, Hong DS, Tsimberidou AM et al (2013) Target-based therapeutic matching in early-phase clinical trials in patients with advanced colorectal cancer and PIK3CA mutations. Mol Cancer Ther

    Google Scholar 

  7. Faivre S, Djelloul S, Raymond E (2006) New paradigms in anticancer therapy: targeting multiple signaling pathways with kinase inhibitors. Semin Oncol 33(4):407–420

    Article  CAS  PubMed  Google Scholar 

  8. Huang PH, Mukasa A, Bonavia R, Flynn RA, Brewer ZE et al (2007) Quantitative analysis of EGFRvIII cellular signaling networks reveals a combinatorial therapeutic strategy for glioblastoma. Proc Natl Acad Sci USA 104(31):12867–12872

    Article  CAS  PubMed  Google Scholar 

  9. Engelman JA, Zejnullahu K, Mitsudomi T, Song Y, Hyland C et al (2007) MET amplification leads to gefitinib resistance in lung cancer by activating ERBB3 signaling. Science 316(5827):1039–1043

    Article  CAS  PubMed  Google Scholar 

  10. Sawyers CL (2008) The cancer biomarker problem. Nature 452(7187):548

    Article  CAS  PubMed  Google Scholar 

  11. Parsons DW, Jones S, Zhang X, Lin JC, Leary RJ et al (2008) An integrated genomic analysis of human glioblastoma multiforme. Science 321(5897):1807–1812

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Jones S, Zhang X, Parsons DW, Lin JC, Leary RJ et al (2008) Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science 321(5897):1801–1806

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Wood LD, Parsons DW, Jones S, Lin J, Sjöblom T et al (2007) The genomic landscapes of human breast and colorectal cancers. Science 318(5853):1108–1113

    Article  CAS  PubMed  Google Scholar 

  14. Liotta LA, Kohn EC, Petricoin EF (2001) Clinical proteomics: personalized molecular medicine. JAMA 286(18):2211–2214

    Article  CAS  PubMed  Google Scholar 

  15. Petricoin EF III, Bichsel VE, Calvert VS, Espina V, Winters M et al (2005) Mapping molecular networks using proteomics: a vision for patient-tailored combination therapy. J Clin Oncol 23:3614–3621

    Article  CAS  PubMed  Google Scholar 

  16. Wulfkuhle JD, Edmiston KH, Liotta LA, Petricoin EF (2006) Technology insight: pharmacoproteomics for cancer-promises of patient-tailored medicine using protein microarrays. Nat Clin Pract Oncol 3(5):256–268

    Article  CAS  PubMed  Google Scholar 

  17. Emery IF, Battelli C, Auclair PL, Carrier K, Hayes DM (2009) Response to gefitinib and erlotinib in non-small cell lung cancer: a retrospective study. BMC Cancer 9:333

    Article  PubMed  PubMed Central  Google Scholar 

  18. Wang F, Wang S, Wang Z, Duan J, An T et al (2012) Phosphorylated EGFR expression may predict outcome of EGFR-TKIs therapy for the advanced NSCLC patients with wild-type EGFR. J Exp Clin Cancer Res 18(31):65

    Article  Google Scholar 

  19. Anderson L, Seilhamer J (1997) A comparison of selected mRNA and protein abundances in human liver. Electrophoresis 18(3–4):533–537

    Article  CAS  PubMed  Google Scholar 

  20. Gygi SP, Rochon Y, Franza BR, Aebersold R (1999) Correlation between protein and mRNA abundance in yeast. Mol Cell Biol 19(3):1720–1730

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Quaranta V, Tyson DR (2013) What lies beneath: looking beyond tumor genetics shows the complexity of signaling networks underlying drug sensitivity. Sci Signal 6(294)

    Article  PubMed  Google Scholar 

  22. Irish JM, Hovland R, Krutzik PO, Perez OD, Bruserud Ø, Gjertsen BT et al (2004) Single cell profiling of potentiated phospho-protein networks in cancer cells. Cell 118(2):217–228

    Article  CAS  PubMed  Google Scholar 

  23. Irish JM, Anensen N, Hovland R, Skavland J, Børresen-Dale AL et al (2007) Flt3 Y591 duplication and Bcl-2 overexpression are detected in acute myeloid leukemia cells with high levels of phosphorylated wild-type p53. Blood 109(6):2589–2596

    Article  CAS  PubMed  Google Scholar 

  24. Stern DF (2005) Phosphoproteomics for oncology discovery and treatment. Expert Opin Ther Targets 9(4):851–860

    Article  CAS  PubMed  Google Scholar 

  25. Moran MF, Tong J, Taylor P, Ewing RM (2006) Emerging applications for phospho-proteomics in cancer molecular therapeutics. Biochim Biophys Acta 1766(2):230–241

    CAS  PubMed  Google Scholar 

  26. Hunter T (2000) Signaling-2000 and beyond. Cell 100:113–127

    Article  CAS  PubMed  Google Scholar 

  27. Figlin RA (2008) Mechanisms of disease: survival benefit of temsirolimus validates a role for mTOR in the management of advanced RCC. Nat Clin Pract Oncol 5(10):601–609

    Article  CAS  PubMed  Google Scholar 

  28. Ramić S, Asić K, Balja MP, Paić F, Benković V, Knežević F (2013) Correlation of phosphorylated HER2 with clinicopathological characteristics and efficacy of trastuzumab treatment for breast cancer. Anticancer Res 33(6):2509–2515

    PubMed  Google Scholar 

  29. Krutzik PO, Trejo A, Schulz KR, Nolan GP (2011) Phospho flow cytometry methods for the analysis of kinase signaling in cell lines and primary human blood samples. Methods Mol Biol 699:179–202

    Article  CAS  PubMed  Google Scholar 

  30. Krutzik PO, Clutter MR, Trejo A, Nolan GP (2011) Fluorescent cell barcoding for multiplex flow cytometry. Curr Protoc Cytom (Chapter 6, Unit 6.31)

    Google Scholar 

  31. Perl AE, Kasner MT, Shank D, Luger SM, Carroll M (2012) Single-cell pharmacodynamic monitoring of S6 ribosomal protein phosphorylation in AML blasts during a clinical trial combining the mTOR inhibitor sirolimus and intensive chemotherapy. Clin Cancer Res 18(6):1716–1725

    Article  CAS  PubMed  Google Scholar 

  32. Camp RL, Chung GG, Rimm DL (2002) Automated subcellular localization and quantification of protein expression in tissue microarrays. Nature Med 8:1323–1327

    Article  CAS  PubMed  Google Scholar 

  33. Camp RL, Neumeister V, Rimm DL (2008) A decade of tissue microarrays: progress in the discovery and validation of cancer biomarkers. J Clin Oncol 26:5630–5637

    Article  PubMed  Google Scholar 

  34. Faratian D, Um IH, Wilson DS, Mullen P, Langdon SP, Harrison DJ (2011) Phosphoprotein pathway profiling of ovarian carcinoma for the identification of potential new targets for therapy. Eur J Cancer 47:1420–1431

    Article  CAS  PubMed  Google Scholar 

  35. Stasyk T, Huber LA (2012) Mapping in vivo signal transduction defects by phosphoproteomics. Trends Mol Med 18:43–51

    Article  CAS  PubMed  Google Scholar 

  36. Geiger T, Cox J, Ostasiewicz P, Wisniewski JR, Mann M (2010) Super-SILAC mix for proteomics of human tumor tissue. Nat Methods 7:383–385

    Article  CAS  PubMed  Google Scholar 

  37. Narumi R, Murakami T, Kuga T, Adachi J, Shriomizu T, Muraoka S et al (2012) A strategy of large-scale phosphoproteomics and SRM-based validation of human breast cancer tissue samples. J Proteome Res 11:5311–5322

    Article  CAS  PubMed  Google Scholar 

  38. Chowdhury F, Williams A, Johnson P (2009) Validation and comparison of two multiplex technologies, Luminex and Mesoscale Discovery, for human cytokine profiling. J Immunol Methods 340(1):55–64. https://doi.org/10.1016/j.jim.2008.10.002

    Article  CAS  PubMed  Google Scholar 

  39. Dahut WL, Scripture C, Posadas E, Jain L, Gulley JL, Arlen PM, Wright JJ, Yu Y, Cao L, Steinberg SM, Aragon-Ching JB, Venitz J, Jones E, Chen CC, Figg WD (2008) A phase II clinical trial of sorafenib in androgen-independent prostate cancer. Clin Cancer Res 14(1):209–214

    Article  CAS  PubMed  Google Scholar 

  40. Yap TA, Yan L, Patnaik A, Fearen I, Olmos D, Papadopoulos K, Baird RD, Delgado L, Taylor A, Lupinacci L, Riisnaes R, Pope LL, Heaton SP, Thomas G, Garrett MD, Sullivan DM, de Bono JS, Tolcher AW (2011) First-in-man clinical trial of the oral pan-AKT inhibitor MK-2206 in patients with advanced solid tumors. J Clin Oncol 29(35):4688–4695

    Article  CAS  PubMed  Google Scholar 

  41. Schwenk JM, Nilsson P (2011) Antibody suspension bead arrays. Methods Mol Biol 723:29–36

    Article  CAS  PubMed  Google Scholar 

  42. Perkins G, Lièvre A, Ramacci C, Méatchi T, de Reynies A, Emile JF, Boige V, Tomasic G, Bachet JB, Bibeau F, Bouché O, Penault-Llorca F, Merlin JL, Laurent-Puig P (2010) Additional value of EGFR downstream signaling phosphoprotein expression to KRAS status for response to anti-EGFR antibodies in colorectal cancer. Int J Cancer 127(6):1321–1331

    Article  CAS  PubMed  Google Scholar 

  43. Baselga J, Cervantes A, Martinelli E, Chirivella I, Hoekman K, Hurwitz HI, Jodrell DI, Hamberg P, Casado E, Elvin P, Swaisland A, Iacona R, Tabernero J (2010) Phase I safety, pharmacokinetics, and inhibition of SRC activity study of saracatinib in patients with solid tumors. Clin Cancer Res 16(19):4876–4883

    Article  CAS  PubMed  Google Scholar 

  44. Paweletz CP, Charboneau L, Roth MJ, Bichsel VE, Simone NL, Chen T et al (2001) Reverse phase proteomic microarrays which capture disease progression show activation of pro-survival pathways at the cancer invasion front. Oncogene 20(16):1981–1989

    Article  CAS  PubMed  Google Scholar 

  45. Pierobon M, Calvert V, Belluco C, Garaci E, Deng J, Lise M et al (2009) Multiplexed cell signaling analysis of metastatic and nonmetastatic colorectal cancer reveals COX2-EGFR signaling activation as a potential prognostic pathway biomarker. Clin Colorectal Cancer 8(2):110–117

    Article  CAS  PubMed  Google Scholar 

  46. Vanmeter AJ, Rodriguez AS, Bowman ED, Harris CC, Deng J, Calvert VS et al (2008) LCM and protein microarray analysis of human NSCLC: differential EGFR phosphorylation events associated with mutated EGFR compared to wild type. Mol Cell Proteomics 7(10):1902–1924

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Rapkiewicz A, Espina V, Zujewski JA, Lebowitz PF, Filie A, Wulfkuhle J et al (2007) The needle in the haystack: application of breast fine-needle aspirate samples to quantitative protein microarray technology. Cancer 111(3):173–184

    Article  CAS  PubMed  Google Scholar 

  48. Petricoin EF, Espina V, Araujo RP, Midura B, Yeung C, Wan X et al (2007) Phosphoprotein signal pathway mapping: Akt/mTOR pathway activation association with childhood rhabdomyosarcoma survival. Cancer Res 67(7):3431–3434

    Article  CAS  PubMed  Google Scholar 

  49. Calvert VS, Tang Y, Boveia V, Wulfkuhle J, Schutz-Geschwender Olive DM et al (2004) Development of multiplexed protein profiling and detection using near infrared detection of reverse-phase protein microarrays. Clin Proteomics 1(1):81–90

    Article  CAS  Google Scholar 

  50. Chiechi A, Mueller C, Boehm KM, Romano A, Benassi MS, Picci P, Liotta LA, Espina V (2012) Improved data normalization methods for reverse phase protein microarray analysis of complex biological samples. Biotechniques, 1–7

    Google Scholar 

  51. Stevens EV, Nishizuka S, Antony S et al (2008) Predicting cisplatin and trabectedin drug sensitivity in ovarian and colon cancers. Mol Cancer Ther 7:10–18

    Article  CAS  PubMed  Google Scholar 

  52. O’Reilly KE, Warycha M, Davies MA et al (2009) Phosphorylated 4E-BP1 is associated with poor survival in melanoma. Clin Cancer Res 15:2872–2878

    Article  PubMed  PubMed Central  Google Scholar 

  53. Boyd ZS, Wu QJ, O’Brien C et al (2008) Proteomic analysis of breast cancer molecular subtypes and biomarkers of response to targeted kinase inhibitors using reverse-phase protein microarrays. Mol Cancer Ther 7:3695–3706

    Article  CAS  PubMed  Google Scholar 

  54. Ihle NT, Lemos R, Wipf P et al (2009) Mutations I the phosphatidylinositol-3-kinase pathway predict for antitumor activity of the inhibitor PX-866 while oncogenic Ras is a dominant predictor for resistance. Cancer Res 69:143–150

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Xia W, Petricoin EF 3rd, Zhao S, Liu L, Osada T, Cheng Q, Wulfkuhle JD, Gwin WR, Yang X, Gallagher RI, Bacus S, Lyerly HK, Spector NL (2013) An heregulin-EGFR-HER3 autocrine signaling axis can mediate acquired lapatinib resistance in HER2+ breast cancer models. Breast Cancer Res 15(5):R85

    Article  PubMed  PubMed Central  Google Scholar 

  56. Wulfkuhle JD, Yau C, Wolf DM, Vis DJ, Gallagher RI, Brown-Swigart L, Hirst G, Voest EE, DeMichele A, Hylton H, Symmans F, Yee DT, Esserman L, Berry D, Liu M, Park JW, Wessels L, van’t Veer L, Petricoin III EF (2018) Evaluation of the HER/PI3K/AKT family signaling network as a predictive biomarker of pathologic complete response for patients with breast cancer treated with neratinib in the I-SPY 2 TRIAL JCO precision oncology (2):1–20

    Google Scholar 

  57. Mueller C, Decarvalho AC, Mikkelsen T, Lehman NL, Calvert V, Espina V, Liotta LA, Petricoin EF 3rd (2014) Glioblastoma cell enrichment is critical for analysis of phosphorylated drug targets and proteomic-genomic correlations. Cancer Res 74(3):818–828

    Article  CAS  PubMed  Google Scholar 

  58. Baldelli E, Haura EB, Crinò L, Cress WD, Ludovini V, Schabath MB, Liotta LA, Petricoin EF, Pierobon M (2015) Impact of upfront cellular enrichment by laser capture microdissection on protein and phosphoprotein drug target signaling activation measurements in human lung cancer: implications for personalized medicine. Proteomics Clin Appl

    Google Scholar 

  59. Espina V, Edmiston KH, Heiby M, Pierobon M, Sciro M, Merritt B, Banks S, Deng J, VanMeter AJ, Geho DH, Pastore L, Sennesh J, Petricoin EF 3rd, Liotta LA (2008) A portrait of tissue phosphoprotein stability in the clinical tissue procurement process. Mol Cell Proteomics 7(10):1998–2018

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Pinhel IF, Macneill FA, Hills MJ, Salter J, Detre S, A’hern R, Nerurkar A, Osin P, Smith IE, Dowsett M (2010) Extreme loss of immunoreactive p-Akt and p-Erk1/2 during routine fixation of primary breast cancer. Breast Cancer Res 12(5):R76

    Article  PubMed  PubMed Central  Google Scholar 

  61. Mueller C, Edmiston KH, Carpenter C, Gaffney E, Ryan C, Ward R, White S, Memeo L, Colarossi C, Petricoin EF 3rd, Liotta LA, Espina V (2011) One-step preservation of phosphoproteins and tissue morphology at room temperature for diagnostic and research specimens. PLoS ONE 6(8):e23780

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Center for Applied Proteomics and Molecular Medicine, George Mason University, 20110, Manassas, VA, USA

    Mariaelena Pierobon, Julie Wulfkuhle, Lance A. Liotta & Emanuel F. Petricoin III

Authors
  1. Mariaelena Pierobon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Julie Wulfkuhle
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lance A. Liotta
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Emanuel F. Petricoin III
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Emanuel F. Petricoin III .

Editor information

Editors and Affiliations

  1. Molecular Medicine Division, Translational Genomics Research Institute, Phoenix, AZ, USA

    Daniel D. Von Hoff

  2. Molecular Medicine Division, Translational Genomics Research Institute, Phoenix, AZ, USA

    Haiyong Han

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Pierobon, M., Wulfkuhle, J., Liotta, L.A., Petricoin III, E.F. (2019). Utilization of Proteomic Technologies for Precision Oncology Applications. In: Von Hoff, D., Han, H. (eds) Precision Medicine in Cancer Therapy . Cancer Treatment and Research, vol 178. Springer, Cham. https://doi.org/10.1007/978-3-030-16391-4_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-16391-4_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-16390-7

  • Online ISBN: 978-3-030-16391-4

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation