Citation

Starrett JH, Guernet AA, Cuomo ME, Poels KE, van Alderwerelt van Rosenburgh IK, Nagelberg A, Farnsworth D, Price KS, Khan H, Ashtekar KD, Gaefele M, Ayeni D, Stewart TF, Kuhlmann A, Kaech SM, Unni AM, Homer R, Lockwood WW, Michor F, Goldberg SB, Lemmon MA, Smith PD, Cross DAE, Politi K. 2020. Drug Sensitivity and Allele Specificity of First-Line Osimertinib Resistance Mutations. Cancer research. 80(10):2017-2030. Pubmed: 32193290 DOI:10.1158/0008-5472.CAN-19-3819

Abstract

Osimertinib, a mutant-specific third-generation EGFR tyrosine kinase inhibitor, is emerging as the preferred first-line therapy for -mutant lung cancer, yet resistance inevitably develops in patients. We modeled acquired resistance to osimertinib in transgenic mouse models of -induced lung adenocarcinoma and found that it is mediated largely through secondary mutations in -either C797S or L718V/Q. Analysis of circulating free DNA data from patients revealed that L718Q/V mutations almost always occur in the context of an L858R driver mutation. Therapeutic testing in mice revealed that both erlotinib and afatinib caused regression of osimertinib-resistant C797S-containing tumors, whereas only afatinib was effective on L718Q mutant tumors. Combination first-line osimertinib plus erlotinib treatment prevented the emergence of secondary mutations in . These findings highlight how knowledge of the specific characteristics of resistance mutations is important for determining potential subsequent treatment approaches and suggest strategies to overcome or prevent osimertinib resistance . SIGNIFICANCE: This study provides insight into the biological and molecular properties of osimertinib resistance mutations and evaluates therapeutic strategies to overcome resistance. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/10/2017/F1.large.jpg.
©2020 American Association for Cancer Research.

Related Faculty

Photo of Franziska Michor

Franziska Michor uses the tools of theoretical evolutionary biology, applied mathematics, statistics, and computational biology to address important questions in cancer research.

Search Menu