IntroductionThe genetic heterogeneity of non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations may affect clinical responses and outcomes to EGFR tyrosine kinase inhibitors (EGFR-TKIs). This study aims to investigate the genomic factors that influence the efficacy and clinical outcomes of first-line, second-line and third-line treatments in NSCLC and explore the heterogeneity of resistance mechanisms. Materials and methodsThis real-world study comprised 65 patients with EGFR mutant NSCLC. Molecular alterations were detected using a customized DNA panel before and after administering targeted therapy. The efficacy and prognosis of each treatment line were evaluated. ResultsIn first-generation EGFR-TKIs treatment, gefitinib showed favorable efficacy compared to icotinib and erlotinib, particularly in patients with EGFR L858R mutations. The resistance mechanisms to first-generation EGFR-TKIs varied among different EGFR mutation cohorts and different first-generation EGFR-TKIs. In second-line EGFR-TKIs treatment, EPH receptor A3 (EPHA3), IKAROS family zinc finger 1 (IKZF1), p21 (RAC1) activated kinase 5 (PAK5), DNA polymerase epsilon, catalytic subunit (POLE), RAD21 cohesin complex component (RAD21) and RNA binding motif protein 10 (RBM10) mutations were markedly associated with poorer progression-free survival (PFS). Notably, EPHA3, IKZF1 and RBM10 were identified as independent predictors of PFS. The mechanisms of osimertinib resistance exhibited heterogeneity, with a higher proportion of non-EGFR-dependent resistant mutations. In third-line treatments, the combination of osimertinib and anlotinib demonstrated superior efficacy compared to other regimens. Glutamate ionotropic receptor NMDA type subunit 2A (GRIN2A) mutation was an independent risk indicator of shorter OS following third-line treatments. ConclusionsComprehending the tumor evolution in NSCLC is advantageous for assessing the efficacy and prognosis at each stage of treatment, providing valuable insights to guide personalized treatment decisions for patients.
Read full abstract