Biomarkers to predict response to epidermal growth factor receptor inhibitors

Daphne A Haas-Kogan1, Michael D Prados, Kathleen R Lamborn

  • 1Department of Radiation Oncology, University of California-San Francisco, USA. hkogan@radonc.17.ucsf.edu

Insights

Epidermal growth factor receptor (EGFR) inhibitors show promise for certain cancers. Tumors with high EGFR levels and low phospho-PKB/Akt responded best to erlotinib in glioblastoma patients.

Area of Science:

  • Oncology
  • Molecular Biology
  • Cancer Therapeutics

Background:

  • Epidermal growth factor receptors (EGFRs) are frequently amplified and overexpressed in human cancers, correlating with poor prognosis.
  • Tyrosine kinase inhibitors targeting EGFR, such as gefitinib and erlotinib, are approved for non-small cell lung cancer and are under investigation for other tumor types.
  • Response rates to EGFR inhibitors vary, suggesting patient and tumor subgroups may preferentially benefit from these treatments.

Purpose of the Study:

  • To investigate the predictive markers of response to erlotinib in patients with glioblastoma multiforme (GBM).
  • To analyze the relationship between EGFR amplification/overexpression and PKB/Akt phosphorylation status with erlotinib efficacy.
  • To differentiate prognostic indicators from predictive markers for EGFR inhibitor therapy.

Main Methods:

  • Analysis of tumor samples from a Phase I trial of erlotinib in GBM patients.
  • Assessment of EGFR amplification and overexpression levels.
  • Evaluation of the phosphorylation state of PKB/Akt.

Main Results:

  • Patients with EGFR-overexpressing and amplified tumors showed a better response to erlotinib.
  • Low levels of phospho-PKB/Akt predicted a favorable response to erlotinib.
  • Findings align with molecular analyses from placebo-controlled Phase III trials of EGFR inhibitors.

Conclusions:

  • EGFR amplification/overexpression and PKB/Akt phosphorylation status are potential predictive markers for erlotinib response in GBM.
  • Placebo-controlled trials are crucial for distinguishing prognostic factors from predictive therapeutic markers.
  • Identifying patient subgroups who will preferentially respond to EGFR inhibitors is key for optimizing cancer treatment.