Clonal Architecture of EGFR Mutation Predicts the Efficacy of EGFR-Tyrosine Kinase Inhibitors in Advanced NSCLC: A Prospective Multicenter Study (NCT03059641)

Abstract
Purpose: Clonal architecture is fundamental for the understanding of cancer biology and therapy; however, multiregional sampling in advanced-stage cancers is not always applicable. This prospective clinical trial was to investigate whether paired tissue and circulating tumor DNA (ctDNA) could describe the clonal architecture of advanced non-small cell lung cancer (NSCLC) and its association with clinical outcome (NCT03059641). Patients and Methods: Paired tumor and plasma ctDNA samples were sequenced by target-capture deep sequencing of 1,021 genes. Clonal dominance analysis was performed on the basis of PyClone. Results: Overall, 300 treatment-naive patients with stage IIIB-IV NSCLC were recruited from 14 centers. Of the 94 patients with available ctDNA data for EGFR clonal architecture analysis, 72 76.6%) showed EGFR as the dominant clone. The median progression-free survival was longer for these patients than for the 22 patients whose EGFR was nondominant clone [11 vs. 10 months; HR, 0.46; 95% confidence interval (CI), 0.24-0.88; P = 0.02]. The difference was more significant if both tissue and ctDNA defined EGFR as dominant clone (n = 43) versus those not (n = 8; 11 vs. 6 months; HR, 0.13; 95% CI, 0.04-0.50; P = 0.003). Moreover, multivariate Cox proportional HR analysis demonstrated EGFR clonal architecture as an independent prognostic indicator of the efficacy of EGFR-tyrosine kinase inhibitors (TKIs). Conclusions: Paired tissue and ctDNA could be analyzed for clonal architecture in advanced cancer. EGFR mutations do not always make up a dominant clone in advanced NSCLC, which was associated with the efficacy of EGFR-TKIs in NSCLC.
Funding Information
  • National Key R&D Program of China (2016YFC1303300)
  • Science and Technology Innovation Program of Shanghai Municipal Government (19411950500)
  • National Natural Science Foundation of China (81672272, 82030045)
  • Shanghai Municipal Science & Technology Commission Research Project (17431906103)
  • Shanghai Chest Hospital Project of Collaborative Innovation (YJXT20190105)
  • Science and Technology Program of Guangzhou (201803010024)