Molecular dynamics simulation-guided drug sensitivity prediction for lung cancer with rare EGFR mutations

Next generation sequencing (NGS)-based tumor profiling identified an overwhelming number of uncharacterized somatic mutations, also known as variants of unknown significance (VUS). The therapeutic significance of mutations outside mutational hotspots, consisting of >50 types, in nonsmall cell lun...

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Published in:	Proceedings of the National Academy of Sciences - PNAS Vol. 116; no. 20; p. 10025
Main Authors:	Ikemura, Shinnosuke, Yasuda, Hiroyuki, Matsumoto, Shingo, Kamada, Mayumi, Hamamoto, Junko, Masuzawa, Keita, Kobayashi, Keigo, Manabe, Tadashi, Arai, Daisuke, Nakachi, Ichiro, Kawada, Ichiro, Ishioka, Kota, Nakamura, Morio, Namkoong, Ho, Naoki, Katsuhiko, Ono, Fumie, Araki, Mitsugu, Kanada, Ryo, Ma, Biao, Hayashi, Yuichiro, Mimaki, Sachiyo, Yoh, Kiyotaka, Kobayashi, Susumu S, Kohno, Takashi, Okuno, Yasushi, Goto, Koichi, Tsuchihara, Katsuya, Soejima, Kenzo
Format:	Journal Article
Language:	English
Published:	United States 14.05.2019
Subjects:	Acrylamides - therapeutic use Adenocarcinoma - drug therapy Aniline Compounds - therapeutic use Carcinoma, Non-Small-Cell Lung - genetics Genes, erbB-1 Humans Lung Neoplasms - drug therapy Lung Neoplasms - genetics Middle Aged Molecular Dynamics Simulation Mutation Pharmacogenomic Testing Prospective Studies Protein-Tyrosine Kinases - antagonists & inhibitors rare EGFR mutation mutation diversity in silico prediction model nonsmall cell lung cancer osimertinib
ISSN:	1091-6490, 1091-6490
Online Access:	Get more information
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Summary:	Next generation sequencing (NGS)-based tumor profiling identified an overwhelming number of uncharacterized somatic mutations, also known as variants of unknown significance (VUS). The therapeutic significance of mutations outside mutational hotspots, consisting of >50 types, in nonsmall cell lung carcinoma (NSCLC) is largely unknown. In fact, our pan-nation screening of NSCLC without hotspot mutations ( = 3,779) revealed that the majority (>90%) of cases with rare mutations, accounting for 5.5% of the cohort subjects, did not receive EGFR-tyrosine kinase inhibitors (TKIs) as a first-line treatment. To tackle this problem, we applied a molecular dynamics simulation-based model to predict the sensitivity of rare EGFR mutants to EGFR-TKIs. The model successfully predicted the diverse in vitro and in vivo sensitivities of exon 20 insertion mutants, including a singleton, to osimertinib, a third-generation EGFR-TKI ( = 0.72, = 0.0037). Additionally, our model showed a higher consistency with experimentally obtained sensitivity data than other prediction approaches, indicating its robustness in analyzing complex cancer mutations. Thus, the in silico prediction model will be a powerful tool in precision medicine for NSCLC patients carrying rare mutations in the clinical setting. Here, we propose an insight to overcome mutation diversity in lung cancer.
Bibliography:	ObjectType-Case Study-2 SourceType-Scholarly Journals-1 ObjectType-Feature-4 content type line 23 ObjectType-Report-1 ObjectType-Article-3
ISSN:	1091-6490 1091-6490
DOI:	10.1073/pnas.1819430116