Although targeted therapy has improved the clinical prognosis of patients with non-small cell lung cancer (NSCLC) EGFR mutations, these patients eventually will develop resistance to TKIs. Immune checkpoint inhibitors (ICIs) could be the potential subsequent treatment option but there is a great heterogeneity in patients’ response to ICIs, which triggers an urgent need for predictive biomarkers to select patients who respond well. Here we displayed the predictive capability of EGFR mutation and tumor mutational burden (TMB) in immunotherapy response prediction using a cohort of 247 patients with advanced NSCLC. The targeted next-generation sequencing panel was used to detect gene expression and mutations from formalin-fixed paraffin-embedded tumor tissue. Progression-free survival was analysed. Patients with EGFR mutations (versus EGFR wild type) demonstrated a worse response to ICIs in patients with advanced NSCLC. Among patients with EGFR mutation, TMB high (versus TMB low) didn’t predict an improved response to ICIs whereas, in the EGFRwt group, TMB high showed a beneficial response to ICIs. Our study therefore suggested that EGFR mutations could be a biomarker to predict a poor response to ICIs in patients with NSCLC and TMB could not have predictive value of ICI response although some EGFR mutation subtypes may suggest improved response in patients with NSCLC EGFR mutations.

Yifei Yu, Xinan Wang. Predictive impact of EGFR mutations and tumor mutational burden on immune checkpoint inhibitor efficacy in non-small cell lung cancer. Frontiers in Medical Science Research (2024), Vol. 6, Issue 8: 61-67. https://doi.org/10.25236/FMSR.2024.060809.

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