Early changes in protein expression detected by mass spectrometry predict tumor response to molecular therapeutics

Michelle L. Reyzer, Robert L. Caldwell, Teresa C. Dugger, James T. Forbes, Christoph A. Ritter, Marta Guix, Carlos L. Arteaga, Richard M. Caprioli

Research output: Contribution to journalArticle

125 Scopus citations

Abstract

Biomarkers that predict therapeutic response are essential for the development of anticancer therapies. We have used matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) to directly analyze protein profiles in mouse mammary tumor virus/HER2 transgenic mouse frozen tumor sections after treatment with the erbB receptor inhibitors OSI-774 and Herceptin. Inhibition of tumor cell proliferation and induction of apoptosis and tumor reduction were predicted by a >80% reduction in thymosin β4 and ubiquitin levels that were detectable after 16 hours of a single drug dose before any evidence of in situ cellular activity. These effects were time- and dose-dependent, and their spatial distribution in the tumor correlated with that of the small-molecule inhibitor OSI-774. In addition, they predicted for therapeutic synergy of OSI-774 and Herceptin as well as for drug resistance. These results suggest that drug-induced early proteomic changes as measured by MALDI-MS can be used to predict the therapeutic response to established and novel therapies.

Original languageEnglish (US)
Pages (from-to)9093-9100
Number of pages8
JournalCancer Research
Volume64
Issue number24
DOIs
StatePublished - Dec 15 2004

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Fingerprint Dive into the research topics of 'Early changes in protein expression detected by mass spectrometry predict tumor response to molecular therapeutics'. Together they form a unique fingerprint.

  • Cite this

    Reyzer, M. L., Caldwell, R. L., Dugger, T. C., Forbes, J. T., Ritter, C. A., Guix, M., Arteaga, C. L., & Caprioli, R. M. (2004). Early changes in protein expression detected by mass spectrometry predict tumor response to molecular therapeutics. Cancer Research, 64(24), 9093-9100. https://doi.org/10.1158/0008-5472.CAN-04-2231