2024 World Conference on Lung Cancer (WCLC) - Posters-P3.03I.06 Neoadjuvant Gefitinib in EGFR Mutated NSCLC (a Phase 2 Window-Of-Opportunity Study): Deep Genomic and Transcriptomic Analysis

P3.03I.06 Neoadjuvant Gefitinib in EGFR Mutated NSCLC (a Phase 2 Window-Of-Opportunity Study): Deep Genomic and Transcriptomic Analysis

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This study explores the determinants of therapeutic response to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) like gefitinib in patients with EGFR-mutated non-small cell lung cancer (NSCLC). The research utilizes deep genomic and transcriptomic analyses from a phase 2 window-of-opportunity study involving neoadjuvant gefitinib treatment, prior to surgery, in patients with resectable stage I-IIIA NSCLC. <br /><br />The study involved 14 patients given gefitinib 250 mg daily for a minimum of four weeks, followed by surgical resection. Comprehensive multi-region whole exome sequencing (WES) and RNA sequencing (RNA-seq) on tumor samples provided insights into the genetic and transcriptomic landscape, examining adaptive responses and potential resistance mechanisms.<br /><br />Key findings include an objective response rate (ORR) of 62% and a disease control rate (DCR) of 100%. Six patients (46%) experienced pathological downstaging, and one patient (8%) achieved a major pathological response. Significantly, no known EGFR TKI resistance mechanisms, like the EGFR T790M mutation, emerged during the study.<br /><br />The genomic analysis indicated a lower tumor purity and clonal diversity in the gefitinib-treated group compared to treatment-naive patients. Furthermore, transcriptomic data revealed an upregulation of immune regulatory and inflammatory response genes in treated tumors, suggesting immune activation. Interestingly, a metabolic shift from glycolysis to oxidative phosphorylation was observed in cancer cells following gefitinib treatment, implying adaptive metabolic reprogramming.<br /><br />Overall, these findings provide important insights into the early adaptive response mechanisms of EGFR-mutated NSCLC to TKIs, hinting at the potential for combination therapy strategies to improve outcomes. This research demonstrates the value of integrating multi-dimensional genomic data to understand and potentially overcome treatment resistance in lung cancer therapeutics.

Asset Subtitle

Aaron Tan

Meta Tag

Speaker Aaron Tan

Topic Tumor Biology – Translational Biology

Keywords

EGFR

tyrosine kinase inhibitors

gefitinib

non-small cell lung cancer

genomic analysis

transcriptomic analysis

metabolic reprogramming

immune activation

treatment resistance

combination therapy