Biochemical and structural basis for differential inhibitor sensitivity of EGFR with distinct exon 19 mutations

Iris K van Alderwerelt van Rosenburgh1,2,3, David M Lu1,2,3, Michael J Grant3,4

  • 1Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06520, USA.

Nature Communications
|November 10, 2022
PubMed

Insights

Tyrosine kinase inhibitors (TKIs) effectiveness varies in non-small cell lung cancer (NSCLC) due to EGFR exon 19 mutations. Altered ATP-binding affinity explains differential TKI sensitivity and resistance, aiding variant classification.

Area of Science:

  • Biochemistry
  • Molecular Biology
  • Oncology

Background:

  • Tyrosine kinase inhibitors (TKIs) target EGFR mutations in non-small cell lung cancer (NSCLC).
  • Exon 19 deletions and mutations in EGFR exhibit heterogeneous responses to TKIs.
  • The molecular basis for varying TKI sensitivity in NSCLC remains unclear.

Purpose of the Study:

  • To investigate the kinetic properties of EGFR exon 19 variants.
  • To understand the molecular mechanisms underlying differential TKI sensitivity and resistance.
  • To establish a basis for classifying uncommon EGFR exon 19 variants for clinical prediction.

Main Methods:

  • Purified EGFR tyrosine kinase domains (TKDs) were used for kinetic analysis.
  • Comparison of TKI sensitivity across different exon 19 variants.
  • Crystallography and hydrogen-deuterium exchange mass spectrometry (HDX-MS) were employed.

Main Results:

  • TKI sensitivity varied significantly for first-generation (erlotinib) and third-generation (osimertinib) TKIs, but not for second-generation (afatinib).
  • EGFR variants with reduced ATP-binding affinity showed increased sensitivity to certain TKIs.
  • Variants with wild-type ATP-binding characteristics (low KM, ATP) were associated with primary resistance.

Conclusions:

  • Altered ATP-binding affinity is a key determinant of TKI sensitivity and resistance in EGFR exon 19 mutated NSCLC.
  • Structural and kinetic insights explain differential responses to various TKIs.
  • A classification system for uncommon exon 19 variants may offer predictive clinical value for NSCLC treatment.