Journal
NPJ PRECISION ONCOLOGY
Volume 5, Issue 1, Pages -Publisher
NATURE RESEARCH
DOI: 10.1038/s41698-021-00170-7
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Funding
- MEXT/JSPS KAKENHI [JP17H06327, JP18K06594, JPJP18K15936, JP19H03524, 20K21554]
- AMED [JP20cm0106203h0005, JP20ck0106472h0002]
- Uehara Memorial Foundation
- Nippon Foundation
- MEXT
- FOCUS Establishing Supercomputing Center of Excellence
- Information Technology Center, the University of Tokyo (Reedbush-L) through the HPCI System Research Project [hp200129]
- Grants-in-Aid for Scientific Research [20K21554] Funding Source: KAKEN
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This study focused on a lung cancer patient with an EGFR-L747P mutation, which was originally misidentified and resistant to certain EGFR-TKIs. Computational structural analysis was used to investigate the impact of the mutation on the active conformation.
Approximately 15-30% of patients with lung cancer harbor mutations in the EGFR gene. Major EGFR mutations (>90% of EGFR-mutated lung cancer) are highly sensitive to EGFR tyrosine kinase inhibitors (TKIs). Many uncommon EGFR mutations have been identified, but little is known regarding their characteristics, activation, and sensitivity to various EGFR-TKIs, including allosteric inhibitors. We encountered a case harboring an EGFR-L747P mutation, originally misdiagnosed with EGFR-del19 mutation using a routine diagnostic EGFR mutation test, which was resistant to EGFR-TKI gefitinib. Using this minor mutation and common EGFR-activating mutations, we performed the binding free energy calculations and microsecond-timescale molecular dynamic (MD) simulations, revealing that the L747P mutation considerably stabilizes the active conformation through a salt-bridge formation between K745 and E762. We further revealed why several EGFR inhibitors, including the allosteric inhibitor, were ineffective. Our computational structural analysis strategy would be beneficial for future drug development targeting the EGFR minor mutations.
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