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MA16 - Novel Strategies in Targeted Therapy (ID 407)
- Event: WCLC 2016
- Type: Mini Oral Session
- Track: Chemotherapy/Targeted Therapy/Immunotherapy
- Presentations: 1
MA16.02 - Mutational Landscape of TKI Naïve and Resistant EGFR Mutant Lung Adenocarcinomas (ID 5777)
14:20 - 15:50 | Author(s): Z. Liu
The identification and development of tyrosine kinase inhibitors (TKIs) targeting the epidermal growth factor receptor (EGFR) have revolutionized and greatly improved the treatment of EGFR-mutant non-small cell lung cancer (NSCLC). Unfortunately, acquired resistance (AR) to these agents remains a major clinical problem hindering durable responses. Although significant work has been done to identify particular mechanisms of acquired resistance, little is known regarding the global mutational landscape of EGFR mutant tumors before therapy or at the manifestation of acquired resistance.
Using specimens obtained in the IRB approved, Yale Lung Rebiopsy program, we completed whole exome sequencing of 15 EGFR mutant tumors with paired tissue obtained pre-treatment and at the time of AR to EGFR TKIs. An additional 5 unpaired AR samples were also analyzed. The mutational burden and copy number profile of the specimens were studied.
We found that the mutational burden of pre-treatment EGFR mutant tumors varies widely between tumors. TKI treatment, however, does not significantly alter the overall or non-synonymous mutation load at AR. Interestingly, EGFR[L858R]tumors had a significantly higher mutation burden at acquired resistance to EGFR TKIs than EGFR[Δ19] tumors. The higher mutation burden in EGFR[L858R] tumors compared to those harboring EGFR[Δ19 ]mutations was further confirmed through analysis of TCGA data. Recurrently altered genes shared in the pre- and AR specimens include TP53, EGFR and AKT1. Alterations in EGFR (T790M), MYCBP2, WHSC1L1, AXL, MET, HGF, MYC and NTRK1 were found at exclusively at AR.
Collectively, these data provide valuable insight into the mutational landscape of EGFR mutant NSCLCs as they evolve on TKIs and identify potential resistance candidate genes for further investigation.
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