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Identification of epidermal growth factor receptor and c-erbB2 pathway inhibitors by correlation with gene expression

K Wosikowski1, D Schuurhuis, K Johnson

  • 1Division of Clinical Sciences, National Cancer Institute, Bethesda, MD 20892, USA.

Abstract

Insights

Researchers identified novel anticancer agents by correlating drug cytotoxicity with gene expression. This method successfully found 14 compounds inhibiting epidermal growth factor (EGF) receptor and c-erbB2 pathways, offering new therapeutic strategies.

Area of Science:

  • Oncology
  • Molecular Biology
  • Pharmacology

Background:

  • Growth factor receptor signaling pathways are crucial targets for anticancer therapies.
  • Correlating molecular target expression with cytotoxicity patterns aids in identifying effective anticancer agents.
  • The epidermal growth factor (EGF) receptor and c-erbB2 (HER2) are significant targets in cancer treatment.

Purpose of the Study:

  • To discover novel anticancer agents targeting the EGF receptor and c-erbB2 pathways.
  • To correlate messenger RNA (mRNA) expression levels of EGF receptor, TGF-alpha, and c-erbB2 with cytotoxicity data from the NCI drug screen.
  • To identify compounds that inhibit the signaling activities of EGF receptor and c-erbB2.

Main Methods:

  • Measured mRNA expression levels for EGF receptor, TGF-alpha, and c-erbB2 across 60 NCI anticancer drug screen cell lines.
  • Utilized the COMPARE program to identify correlations between mRNA expression patterns and cytotoxicity profiles.
  • Validated putative inhibitors by testing their effects on tyrosine phosphorylation, kinase activity, and cell growth.

Main Results:

  • Highest EGF receptor and TGF-alpha mRNA levels were observed in renal cancer cell lines.
  • Highest c-erbB2 mRNA levels were found in breast, ovarian, and colon cancer cell lines.
  • Out of 25 tested compounds, 14 were confirmed as inhibitors of EGF receptor or c-erbB2 signaling, with compound B4 showing potent inhibition of ErbB2 autophosphorylation.

Conclusions:

  • Correlation of cytotoxicity patterns with specific mRNA expression levels is an effective strategy for identifying novel inhibitors of EGF receptor and c-erbB2.
  • The NCI drug screen database, combined with expression profiling, can yield new anticancer drug candidates targeting key growth factor pathways.

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