Skip to main content
SpringerLink
Log in

Reverse Phase Protein Arrays: Mapping the Path Towards Personalized Medicine

  • Review Article
  • Published:
Molecular Diagnosis & Therapy Aims and scope Submit manuscript

Abstract

Reverse phase protein array (RPPA) technology evolved from the advent of miniaturized immunoassays and gene microarray technology. Reverse phase protein arrays provide either a low throughput or high throughput methodology for quantifying proteins and their post-translationally modified forms in both cellular and non-cellular samples. As the demand for patient tailored therapies increases so does the need for precise and sensitive technology to accurately profile the molecular circuitry driving an individual patient’s disease. RPPAs are currently utilized in clinical trials for profiling and comparing the functional state of protein signaling pathways, either temporally within tumors, between patients, or within the same patients before/after treatment. RPPAs are generally employed for quantifying large numbers of samples on one array, under identical experimental conditions. However, the goal of personalized cancer medicine is to design therapies based on the molecular portrait of a patient’s tumor, which in turn result in more efficacious treatments with less toxicity. Therefore, RPPAs are also being validated for low throughput assays of individual patient samples. This review explores RPPA technology in the cancer research field, concentrating on its role as a fundamental tool for deciphering protein signaling networks and its emerging role in personalized medicine.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Liotta LA, Kohn EC, Petricoin EF. Clinical proteomics: personalized molecular medicine. JAMA. 2001;286(18):2211–4.

    Article  CAS  PubMed  Google Scholar 

  2. Petricoin EF, Zoon KC, Kohn EC, Barrett JC, Liotta LA. Clinical proteomics: translating benchside promise into bedside reality. Nat Rev Drug Discov. 2002;1(9):683–95.

    Article  CAS  PubMed  Google Scholar 

  3. de Bono JS, Ashworth A. Translating cancer research into targeted therapeutics. Nature. 2010;467(7315):543–9.

    Article  PubMed  Google Scholar 

  4. Spear BB, Heath-Chiozzi M, Huff J. Clinical application of pharmacogenetics. Trends Mol Med. 2001;7(5):201–4.

    Article  CAS  PubMed  Google Scholar 

  5. Jameson GS, Petricoin EF, Sachdev J, Liotta LA, Loesch DM, Anthony SP, et al. A pilot study utilizing multi-omic molecular profiling to find potential targets and select individualized treatments for patients with previously treated metastatic breast cancer. Breast Cancer Res Treat. 2014;147(3):579–88.

    Article  CAS  PubMed  Google Scholar 

  6. Boja ES, Rodriguez H. Proteogenomic convergence for understanding cancer pathways and networks. Clin Proteomics. 2014;11(1):22.

    Article  PubMed Central  PubMed  Google Scholar 

  7. Patel LR, Nykter M, Chen K, Zhang W. Cancer genome sequencing: understanding malignancy as a disease of the genome, its conformation, and its evolution. Cancer Lett. 2013;340(2):152–60.

    Article  CAS  PubMed  Google Scholar 

  8. Espina V, Mehta AI, Winters ME, Calvert V, Wulfkuhle J, Petricoin EF 3rd, et al. Protein microarrays: molecular profiling technologies for clinical specimens. Proteomics. 2003;3(11):2091–100.

    Article  CAS  PubMed  Google Scholar 

  9. Liotta LA, Espina V, Mehta AI, Calvert V, Rosenblatt K, Geho D, et al. Protein microarrays: meeting analytical challenges for clinical applications. Cancer Cell. 2003;3(4):317–25.

    Article  CAS  PubMed  Google Scholar 

  10. Petricoin EF 3rd, Bichsel VE, Calvert VS, Espina V, Winters M, Young L, et al. Mapping molecular networks using proteomics: a vision for patient-tailored combination therapy. J Clin Oncol. 2005;23(15):3614–21.

    Article  CAS  PubMed  Google Scholar 

  11. Wulfkuhle J, Espina V, Liotta L, Petricoin E. Genomic and proteomic technologies for individualisation and improvement of cancer treatment. Eur J Cancer. 2004;40(17):2623–32.

    Article  CAS  PubMed  Google Scholar 

  12. Chen LC, Elliott RA, Ashcroft DM. Systematic review of the analgesic efficacy and tolerability of COX-2 inhibitors in post-operative pain control. J Clin Pharm Ther. 2004;29(3):215–29.

    Article  CAS  PubMed  Google Scholar 

  13. Desjardins PJ, Mehlisch DR, Chang DJ, Krupa D, Polis AB, Petruschke RA, et al. The time to onset and overall analgesic efficacy of rofecoxib 50 mg: a meta-analysis of 13 randomized clinical trials. Clin J Pain. 2005;21(3):241–50.

    Article  PubMed  Google Scholar 

  14. de Gramont A, Figer A, Seymour M, Homerin M, Hmissi A, Cassidy J, et al. Leucovorin and fluorouracil with or without oxaliplatin as first-line treatment in advanced colorectal cancer. J Clin Oncol. 2000;18(16):2938–47.

    PubMed  Google Scholar 

  15. Labianca R, Pancera G, Luporini G. Factors influencing response rates for advanced colorectal cancer chemotherapy. Ann Oncol. 1996;7(9):901–6.

    Article  CAS  PubMed  Google Scholar 

  16. Moreau LC, Rajan R, Thirlwell MP, Alcindor T. Response to chemotherapy in metastatic colorectal cancer after exposure to oxaliplatin in the adjuvant setting. Anticancer Res. 2013;33(4):1765–8.

    CAS  PubMed  Google Scholar 

  17. Advanced colorectal cancer meta-analysis project: modulation of fluorouracil by leucovorin in patients with advanced colorectal cancer: evidence in terms of response rate. J Clin Oncol. 1992;10(6):896–903.

  18. Amado RG, Wolf M, Peeters M, Van Cutsem E, Siena S, Freeman DJ, et al. Wild-type KRAS is required for panitumumab efficacy in patients with metastatic colorectal cancer. J Clin Oncol. 2008;26(10):1626–34.

    Article  CAS  PubMed  Google Scholar 

  19. Douillard JY, Oliner KS, Siena S, Tabernero J, Burkes R, Barugel M, et al. Panitumumab-FOLFOX4 treatment and RAS mutations in colorectal cancer. N Engl J Med. 2013;369(11):1023–34.

    Article  CAS  PubMed  Google Scholar 

  20. Espina V, Mariani BD, Gallagher RI, Tran K, Banks S, Wiedemann J, et al. Malignant precursor cells pre-exist in human breast DCIS and require autophagy for survival. PLoS One. 2010;5(4):e10240.

    Article  PubMed Central  PubMed  Google Scholar 

  21. Petricoin EF 3rd, Espina V, Araujo RP, Midura B, Yeung C, Wan X, et al. Phosphoprotein pathway mapping: Akt/mammalian target of rapamycin activation is negatively associated with childhood rhabdomyosarcoma survival. Cancer Res. 2007;67(7):3431–40.

    Article  CAS  PubMed  Google Scholar 

  22. Pierobon M, Silvestri A, Spira A, Reeder A, Pin E, Banks S, et al. Pilot phase I/II personalized therapy trial for metastatic colorectal cancer: evaluating the feasibility of protein pathway activation mapping for stratifying patients to therapy with imatinib and panitumumab. J Proteome Res. 2014;13(6):2846–55.

    Article  CAS  PubMed  Google Scholar 

  23. Akbani R, Becker KF, Carragher N, Goldstein T, de Koning L, Korf U, et al. Realizing the promise of reverse phase protein arrays for clinical, translational, and basic research: a workshop report: the RPPA (reverse phase protein array) society. Mol Cell Proteomics. 2014;13(7):1625–43.

    Article  CAS  PubMed  Google Scholar 

  24. Espina V, Wulfkuhle JD, Calvert VS, Petricoin EF 3rd, Liotta LA. Reverse phase protein microarrays for monitoring biological responses. Methods Mol Biol. 2007;383:321–36.

    CAS  PubMed  Google Scholar 

  25. Mueller C, Liotta LA, Espina V. Reverse phase protein microarrays advance to use in clinical trials. Mol Oncol. 2010;4(6):461–81.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  26. Nishizuka S, Chen ST, Gwadry FG, Alexander J, Major SM, Scherf U, et al. Diagnostic markers that distinguish colon and ovarian adenocarcinomas: identification by genomic, proteomic, and tissue array profiling. Cancer Res. 2003;63(17):5243–50.

    CAS  PubMed  Google Scholar 

  27. Speer R, Wulfkuhle J, Espina V, Aurajo R, Edmiston KH, Liotta LA, et al. Development of reverse phase protein microarrays for clinical applications and patient-tailored therapy. Cancer Genomics Proteomics. 2007;4(3):157–64.

    CAS  PubMed  Google Scholar 

  28. Davuluri G, Espina V, Petricoin EF 3rd, Ross M, Deng J, Liotta LA, et al. Activated VEGF receptor shed into the vitreous in eyes with wet AMD: a new class of biomarkers in the vitreous with potential for predicting the treatment timing and monitoring response. Arch Ophthalmol. 2009;127(5):613–21.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  29. Popova TG, Turell MJ, Espina V, Kehn-Hall K, Kidd J, Narayanan A, et al. Reverse-phase phosphoproteome analysis of signaling pathways induced by Rift valley fever virus in human small airway epithelial cells. PLoS One. 2010;5(11):e13805.

    Article  PubMed Central  PubMed  Google Scholar 

  30. Paweletz CP, Charboneau L, Bichsel VE, Simone NL, Chen T, Gillespie JW, et al. Reverse phase protein microarrays which capture disease progression show activation of pro-survival pathways at the cancer invasion front. Oncogene. 2001;20(16):1981–9.

    Article  CAS  PubMed  Google Scholar 

  31. Bobrow MN, Harris TD, Shaughnessy KJ, Litt GJ. Catalyzed reporter deposition, a novel method of signal amplification. Application to immunoassays. J Immunol Methods. 1989;125(1–2):279–85.

    Article  CAS  PubMed  Google Scholar 

  32. Bobrow MN, Shaughnessy KJ, Litt GJ. Catalyzed reporter deposition, a novel method of signal amplification. II. Application to membrane immunoassays. J Immunol Methods. 1991;137(1):103–12.

    Article  CAS  PubMed  Google Scholar 

  33. King G, Payne S, Walker F, Murray GI. A highly sensitive detection method for immunohistochemistry using biotinylated tyramine. J Pathol. 1997;183(2):237–41.

    Article  CAS  PubMed  Google Scholar 

  34. Zhu H, Qian J. Applications of functional protein microarrays in basic and clinical research. Adv Genet. 2012;79:123–55.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  35. VanMeter A, Signore M, Pierobon M, Espina V, Liotta LA, Petricoin EF 3rd. Reverse-phase protein microarrays: application to biomarker discovery and translational medicine. Expert Rev Mol Diagn. 2007;7(5):625–33.

    Article  CAS  PubMed  Google Scholar 

  36. Espina V, Petricoin E, Liotta L, Geho D. Application of sector protein microarrays to clinical samples. Clin Proteomics. 2004;1(91):91–9.

    Article  CAS  Google Scholar 

  37. Gorg A, Weiss W, Dunn MJ. Current two-dimensional electrophoresis technology for proteomics. Proteomics. 2004;4(12):3665–85.

    Article  PubMed  Google Scholar 

  38. Belluco C, Mammano E, Petricoin E, Prevedello L, Calvert V, Liotta L, et al. Kinase substrate protein microarray analysis of human colon cancer and hepatic metastasis. Clin Chim Acta. 2005;357(2):180–3.

    Article  CAS  PubMed  Google Scholar 

  39. Gulmann C, Espina V, Petricoin E 3rd, Longo DL, Santi M, Knutsen T, et al. Proteomic analysis of apoptotic pathways reveals prognostic factors in follicular lymphoma. Clin Cancer Res. 2005;11(16):5847–55.

    Article  CAS  PubMed  Google Scholar 

  40. Wulfkuhle JD, Speer R, Pierobon M, Laird J, Espina V, Deng J, et al. Multiplexed cell signaling analysis of human breast cancer applications for personalized therapy. J Proteome Res. 2008;7(4):1508–17.

    Article  CAS  PubMed  Google Scholar 

  41. Espina V, Edmiston KH, Heiby M, Pierobon M, Sciro M, Merritt B, et al. A portrait of tissue phosphoprotein stability in the clinical tissue procurement process. Mol Cell Proteomics. 2008;7(10):1998–2018.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  42. Ornstein DK, Gillespie JW, Paweletz CP, Duray PH, Herring J, Vocke CD, et al. Proteomic analysis of laser capture microdissected human prostate cancer and in vitro prostate cell lines. Electrophoresis. 2000;21(11):2235–42.

    Article  CAS  PubMed  Google Scholar 

  43. van Oostrum J, Calonder C, Rechsteiner D, Ehrat M, Mestan J, Fabbro D, et al. Tracing pathway activities with kinase inhibitors and reverse phase protein arrays. Proteomics Clin Appl. 2009;3(4):412–22.

    Article  PubMed  Google Scholar 

  44. VanMeter AJ, Rodriguez AS, Bowman ED, Jen J, Harris CC, Deng J, et al. Laser capture microdissection and protein microarray analysis of human non-small cell lung cancer: differential epidermal growth factor receptor (EGPR) phosphorylation events associated with mutated EGFR compared with wild type. Mol Cell Proteomics. 2008;7(10):1902–24.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  45. Gallagher RI, Silvestri A, Petricoin EF 3rd, Liotta LA, Espina V. Reverse phase protein microarrays: fluorometric and colorimetric detection. Methods Mol Biol. 2011;723:275–301.

    Article  CAS  PubMed  Google Scholar 

  46. Pin E, Federici G, Petricoin EF 3rd. Preparation and use of reverse protein microarrays. Curr Protoc Protein Sci. 2014;75:27.7.1–27.7.29.

  47. Wulfkuhle JD, Berg D, Wolff C, Langer R, Tran K, Illi J, et al. Molecular analysis of HER2 signaling in human breast cancer by functional protein pathway activation mapping. Clin Cancer Res. 2012;18(23):6426–35.

    Article  CAS  PubMed  Google Scholar 

  48. Chiechi A, Mueller C, Boehm KM, Romano A, Benassi MS, Picci P, et al. Improved data normalization methods for reverse phase protein microarray analysis of complex biological samples. Biotechniques. 2012;53(3):1–7.

  49. Troncale S, Barbet A, Coulibaly L, Henry E, He B, Barillot E, et al. NormaCurve: a SuperCurve-based method that simultaneously quantifies and normalizes reverse phase protein array data. PLoS One. 2012;7(6):e38686.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  50. Eichner J, Heubach Y, Ruff M, Kohlhof H, Strobl S, Mayer B, et al. RPPApipe: a pipeline for the analysis of reverse-phase protein array data. Biosystems. 2014;122:19–24.

    Article  CAS  PubMed  Google Scholar 

  51. Nishizuka S, Charboneau L, Young L, Major S, Reinhold WC, Waltham M, et al. Proteomic profiling of the NCI-60 cancer cell lines using new high-density reverse-phase lysate microarrays. Proc Natl Acad Sci. 2003;100(24):14229–34.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  52. von der Heyde S, Sonntag J, Kaschek D, Bender C, Bues J, Wachter A, et al. RPPanalyzer Toolbox: an improved R package for analysis of reverse phase protein array data. Biotechniques. 2014;57(3):125–35.

    PubMed  Google Scholar 

  53. Mueller C, deCarvalho AC, Mikkelsen T, Lehman NL, Calvert V, Espina V, et al. Glioblastoma cell enrichment is critical for analysis of phosphorylated drug targets and proteomic-genomic correlations. Cancer Res. 2014;74(3):818–28.

    Article  CAS  PubMed  Google Scholar 

  54. Silvestri A, Colombatti A, Calvert VS, Deng J, Mammano E, Belluco C, et al. Protein pathway biomarker analysis of human cancer reveals requirement for upfront cellular-enrichment processing. Lab Invest. 2010;90(5):787–96.

    Article  CAS  PubMed  Google Scholar 

  55. Mukherjee S, Rodriguez-Canales J, Hanson J, Emmert-Buck MR, Tangrea MA, Prieto DA, et al. Proteomic analysis of frozen tissue samples using laser capture microdissection. Methods Mol Biol. 2013;1002:71–83.

    Article  CAS  PubMed  Google Scholar 

  56. Bonner RF, Emmert-Buck M, Cole K, Pohida T, Chuaqui R, Goldstein S, et al. Laser capture microdissection: molecular analysis of tissue. Science. 1997;278(5342):1481–3.

    Article  CAS  PubMed  Google Scholar 

  57. Emmert-Buck MR, Bonner RF, Smith PD, Chuaqui RF, Zhuang Z, Goldstein SR, et al. Laser capture microdissection. Science. 1996;274(5289):998–1001.

    Article  CAS  PubMed  Google Scholar 

  58. Espina V, Wulfkuhle J, Liotta LA. Application of laser microdissection and reverse-phase protein microarrays to the molecular profiling of cancer signal pathway networks in the tissue microenvironment. Clin Lab Med. 2009;29(1):1–13.

    Article  PubMed  Google Scholar 

  59. Espina V, Wulfkuhle JD, Calvert VS, VanMeter A, Zhou W, Coukos G, et al. Laser-capture microdissection. Nat Protoc. 2006;1(2):586–603.

    Article  CAS  PubMed  Google Scholar 

  60. Gallagher RI, Blakely SR, Liotta LA, Espina V. Laser capture microdissection: arcturus(XT) infrared capture and UV cutting methods. Methods Mol Biol. 2012;823:157–78.

    Article  CAS  PubMed  Google Scholar 

  61. Xu BJ. Combining laser capture microdissection and proteomics: methodologies and clinical applications. Proteomics Clin Appl. 2010;4(2):116–23.

    Article  CAS  PubMed  Google Scholar 

  62. Barker AD, Sigman CC, Kelloff GJ, Hylton NM, Berry DA, Esserman LJ. I-SPY 2: an adaptive breast cancer trial design in the setting of neoadjuvant chemotherapy. Clin Pharmacol Ther. 2009;86(1):97–100.

    Article  CAS  PubMed  Google Scholar 

  63. Gujral TS, Karp RL, Finski A, Chan M, Schwartz PE, MacBeath G, et al. Profiling phospho-signaling networks in breast cancer using reverse-phase protein arrays. Oncogene. 2013;32(29):3470–6.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  64. Rapkiewicz A, Espina V, Zujewski JA, Lebowitz PF, Filie A, Wulfkuhle J, et al. The needle in the haystack: application of breast fine-needle aspirate samples to quantitative protein microarray technology. Cancer. 2007;111(3):173–84.

    Article  CAS  PubMed  Google Scholar 

  65. Sheehan KM, Calvert VS, Kay EW, Lu Y, Fishman D, Espina V, et al. Use of reverse phase protein microarrays and reference standard development for molecular network analysis of metastatic ovarian carcinoma. Mol Cell Proteomics. 2005;4(4):346–55.

    Article  CAS  PubMed  Google Scholar 

  66. Sheehan KM, Gulmann C, Eichler GS, Weinstein JN, Barrett HL, Kay EW, et al. Signal pathway profiling of epithelial and stromal compartments of colonic carcinoma reveals epithelial-mesenchymal transition. Oncogene. 2008;27(3):323–31.

    Article  CAS  PubMed  Google Scholar 

  67. Li J, Gould TD, Yuan P, Manji HK, Chen G. Post-mortem interval effects on the phosphorylation of signaling proteins. Neuropsychopharmacology. 2003;28(6):1017–25.

    Article  CAS  PubMed  Google Scholar 

  68. Li X, Friedman AB, Roh MS, Jope RS. Anesthesia and post-mortem interval profoundly influence the regulatory serine phosphorylation of glycogen synthase kinase-3 in mouse brain. J Neurochem. 2005;92(3):701–4.

    Article  PubMed Central  PubMed  Google Scholar 

  69. Espina V, Mueller C, Edmiston K, Sciro M, Petricoin EF, Liotta LA. Tissue is alive: new technologies are needed to address the problems of protein biomarker pre-analytical variability. Proteomics Clin Appl. 2009;3(8):874–82.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  70. Mueller C, Edmiston KH, Carpenter C, Gaffney E, Ryan C, Ward R, et al. One-step preservation of phosphoproteins and tissue morphology at room temperature for diagnostic and research specimens. PLoS One. 2011;6(8):e23780.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  71. Grellner W, Madea B. Demands on scientific studies: vitality of wounds and wound age estimation. Forensic Sci Int. 2007;165(2–3):150–4.

    Article  PubMed  Google Scholar 

  72. Goldstein BJ. Protein-tyrosine phosphatases: emerging targets for therapeutic intervention in type 2 diabetes and related states of insulin resistance. J Clin Endocrinol Metab. 2002;87(6):2474–80.

    Article  CAS  PubMed  Google Scholar 

  73. Neel BG, Tonks NK. Protein tyrosine phosphatases in signal transduction. Curr Opin Cell Biol. 1997;9(2):193–204.

    Article  CAS  PubMed  Google Scholar 

  74. Liotta LA, Petricoin EF 3rd. Omics and cancer biomarkers: link to the biological truth or bear the consequences. Cancer Epidemiol Biomark Prev. 2012;21(8):1229–35.

    Article  CAS  Google Scholar 

  75. Tell RW, Horvath CM. Bioinformatic analysis reveals a pattern of STAT3-associated gene expression specific to basal-like breast cancers in human tumors. Proc Natl Acad Sci. 2014;111(35):12787–92.

    Article  CAS  PubMed  Google Scholar 

  76. Fidler IJ. The pathogenesis of cancer metastasis: the ‘seed and soil’ hypothesis revisited. Nat Rev Cancer. 2003;3(6):453–8.

    Article  CAS  PubMed  Google Scholar 

  77. He Y, Zhou Z, Hofstetter WL, Zhou Y, Hu W, Guo C, et al. Aberrant expression of proteins involved in signal transduction and DNA repair pathways in lung cancer and their association with clinical parameters. PLoS One. 2012;7(2):e31087.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  78. Angenendt P. Progress in protein and antibody microarray technology. Drug Discov Today. 2005;10(7):503–11.

    Article  CAS  PubMed  Google Scholar 

  79. Esserman LJ, Berry DA, DeMichele A, Carey L, Davis SE, Buxton M, et al. Pathologic complete response predicts recurrence-free survival more effectively by cancer subset: results from the I-SPY 1 TRIAL–CALGB 150007/150012, ACRIN 6657. J Clin Oncol. 2012;30(26):3242–9.

    Article  PubMed Central  PubMed  Google Scholar 

  80. Espina V, Liotta LA. What is the malignant nature of human ductal carcinoma in situ? Nat Rev Cancer. 2010;11(1):68–75.

    Article  PubMed Central  PubMed  Google Scholar 

  81. Gulmann C, Sheehan KM, Kay EW, Liotta LA, Petricoin EF 3rd. Array-based proteomics: mapping of protein circuitries for diagnostics, prognostics, and therapy guidance in cancer. J Pathol. 2006;208(5):595–606.

    Article  CAS  PubMed  Google Scholar 

  82. Wulfkuhle JD, Edmiston KH, Liotta LA, Petricoin EF 3rd. Technology insight: pharmacoproteomics for cancer–promises of patient-tailored medicine using protein microarrays. Nat Clin Pract Oncol. 2006;3(5):256–68.

    Article  CAS  PubMed  Google Scholar 

  83. Taylor CF, Paton NW, Lilley KS, Binz PA, Julian RK Jr, Jones AR, et al. The minimum information about a proteomics experiment (MIAPE). Nat Biotechnol. 2007;25(8):887–93.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported in part by George Mason University, the Department of Defense Breast Cancer Research Program through a grant to L. Liotta and V. Espina (W81XVVH-10-1-0781), and the National Institutes of Health Innovative Molecular Analysis Technologies program through a grant to L. Liotta and V. Espina (1R33CA157403-01). Lance Liotta is Principle Investigator for the PINC trial and kindly provided editorial advice for this manuscript. The funding sources did not have any role in the study design; the collection, analysis and interpretation of data; manuscript preparation; or the decision to submit the paper for publication. Conflict of interest statement: VE is an inventor of technologies discussed in this article and, as a university employee, may receive patent royalties per university policies. VE is entitled to stock options from Theranostics Health, Inc. Author contributions: RG and VE wrote the manuscript. RG contributed the figures and tables.

Author information

Authors and Affiliations

  1. Center for Applied Proteomics and Molecular Medicine, George Mason University, 10900 University Blvd, MS1A9, Manassas, VA, 20110, USA

    Rosa I. Gallagher & Virginia Espina

Authors
  1. Rosa I. Gallagher
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Virginia Espina
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Virginia Espina.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gallagher, R.I., Espina, V. Reverse Phase Protein Arrays: Mapping the Path Towards Personalized Medicine. Mol Diagn Ther 18, 619–630 (2014). https://doi.org/10.1007/s40291-014-0122-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40291-014-0122-3

Keywords

Search

Navigation