Exploring the significance of MET overexpression by gene expression profiling versus immunohistochemistry in an EGFR-mutant lung cancer cohort.

Abstract

e20600 Background: Amivantamab, an innovative EGFR-MET bispecific antibody, approved for use in EGFR exon 20 mutated lung cancers, recently demonstrated substantial clinical benefits in advanced/metastatic lung cancers with EGFR exon 19 deletion and/or L858R mutation according to data from the MARIPOSA clinical trial. Recent findings from the CHRYSALIS 2 trial indicate a potential role for MET overexpression as a predictive biomarker for response to Amivantamab combination therapy, particularly in cases resistant to Osimertinib. Methods: We retrospectively analyzed genomic profiling data in a large lung cancer cohort to characterize EGFR mutations. Additionally, we assessed MET expression via gene expression profiling (GEP) in a smaller EGFR-mutation positive sub-cohort to explore its prevalence. Results: Genomic profiling data from 799 tissue samples was included in our analysis. EGFR mutations were detected in 36%; higher prevalence of EGFR mutations was noted in our cohort (36%) vs the TCGA cohort (26%). Consistent with other studies, exon 19 deletion was the most frequent category of EGFR mutations (46%,), with EGFR p.E746_750del being the most frequent variant among them (60%). Exon 21 L858R mutation was the next most frequently detected variant (28%). Uncommon EGFR mutations were identified in 26% samples, with G719X being the most frequent among these. EGFR Exon 20 insertions contributed 6% of the EGFR variants. EGFR amplification was detected in 4.6% of samples. Of particular significance was the analysis of 21 EGFR-mutated tissue samples for targeted transcriptome analysis as a part Exacta Encyclopedic Tumor Analysis. The MET gene overexpression was detected in 52% of these samples. MET overexpression based on differential GEP identified a higher positivity rate than previously reported using MET immunohistochemistry (IHC) expression (52% vs. 36%), suggesting that GEP may be useful in identifying more patients with MET overexpression. This finding underscores the potential value of MET GEP as a biomarker, especially considering emerging data suggesting MET overexpression as a predictor for enhanced clinical benefit from the combination of Amivantamab and Lazertinib in EGFR-mutated, Osimertinib resistant patients. Furthermore, ongoing clinical trials are exploring MET overexpression as a biomarker for Amivantamab monotherapy. Conclusions: In conclusion, our study not only characterizes the landscape of EGFR mutations in a large lung cancer cohort but also highlights the prevalence of MET overexpression in EGFR-mutated samples, suggesting that MET GEP may serve as a promising predictive biomarker for enhanced clinical outcomes from Amivantamab therapy. In view of small sample size, further exploration and validation of MET overexpression by GEP is warranted in the context of EGFR-mutated advanced lung cancer.