Gene mutation analysis in EGFR wild type NSCLC responsive to erlotinib: are there features to guide patient

Paola Ulivi1, Angelo Delmonte2, Elisa Chiadini3

  • 1Biosciences Laboratory, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola 47014, Italy. paola.ulivi@irst.emr.it.

Insights

Certain mutations in NOTCH1, p53, and EGFR are linked to resistance to tyrosine kinase inhibitors (TKIs) in non-small-cell lung cancer. Identifying other EGFR mutations may reveal new TKI sensitivities.

Area of Science:

  • Oncology
  • Genetics
  • Molecular Biology

Background:

  • Tyrosine kinase inhibitors (TKIs) are effective for non-small-cell lung cancer (NSCLC) with specific Epidermal Growth Factor Receptor (EGFR) mutations.
  • A subset of EGFR wild-type (wt) NSCLC patients exhibit TKI sensitivity through unknown mechanisms.
  • Understanding TKI response in EGFR wt NSCLC is crucial for expanding targeted therapy options.

Purpose of the Study:

  • To investigate the molecular mechanisms underlying TKI response in EGFR wild-type NSCLC patients.
  • To identify genetic alterations associated with erlotinib sensitivity or resistance in this patient cohort.
  • To explore the role of specific gene mutations in predicting TKI efficacy.

Main Methods:

  • A case series of 34 EGFR wt NSCLC patients responsive to erlotinib was analyzed.
  • Responsive patients were matched with an equal number of non-responsive EGFR wt patients.
  • A panel of 26 genes (214 somatic mutations) was analyzed using the MassARRAY® System.

Main Results:

  • KRAS mutations (15%) were present in both responsive and non-responsive groups, with G12C more frequent in non-responders.
  • NOTCH1, p53, and EGFR-resistance mutations were more common in non-responders.
  • EGFR-sensitizing mutations and proliferation pathway gene alterations were more frequent in responders.

Conclusions:

  • p53, NOTCH1, and exon 20 EGFR mutations are associated with TKI resistance in EGFR wt NSCLC.
  • KRAS mutations, including G12C, do not appear to significantly influence TKI response.
  • Highly sensitive methods may uncover under-represented EGFR mutations linked to TKI sensitivity.