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dc.contributor.authorOkada, Koutaroh
dc.contributor.authorAraki, Mitsugu
dc.contributor.authorSakashita, Takuya
dc.contributor.authorMa, Biao
dc.contributor.authorKanada, Ryo
dc.contributor.authorYanagitani, Noriko
dc.contributor.authorHoriike, Atsushi
dc.contributor.authorKoike, Sumie
dc.contributor.authorOh-hara, Tomoko
dc.contributor.authorWatanabe, Kana
dc.contributor.authorTamai, Keiichi
dc.contributor.authorMaemondo, Makoto
dc.contributor.authorNishio, Makoto
dc.contributor.authorIshikawa, Takeshi
dc.contributor.authorOkuno, Yasushi
dc.contributor.authorFujita, Naoya
dc.contributor.authorKatayama, Ryohei
dc.contributor.alternative奥野, 恭史
dc.date.accessioned2020-10-16T02:26:25Z-
dc.date.available2020-10-16T02:26:25Z-
dc.date.issued2019-03
dc.identifier.issn2352-3964
dc.identifier.urihttp://hdl.handle.net/2433/255588-
dc.description.abstractBackground: Alectinib has shown a greater efficacy to ALK-rearranged non-small-cell lung cancers in first-line setting; however, most patients relapse due to acquired resistance, such as secondary mutations in ALK including I1171N and G1202R. Although ceritinib or lorlatinib was shown to be effective to these resistant mutants, further resistance often emerges due to ALK-compound mutations in relapse patients following the use of ceritinib or lorlatinib. However, the drug for overcoming resistance has not been established yet. Methods: We established lorlatinib-resistant cells harboring ALK-I1171N or -G1202R compound mutations by performing ENU mutagenesis screening or using an in vivo mouse model. We performed drug screening to overcome the lorlatinib-resistant ALK-compound mutations. To evaluate these resistances in silico, we developed a modified computational molecular dynamic simulation (MP-CAFEE). Findings: We identified 14 lorlatinib-resistant ALK-compound mutants, including several mutants that were recently discovered in lorlatinib-resistant patients. Some of these compound mutants were found to be sensitive to early generation ALK-TKIs and several BCR-ABL inhibitors. Using our original computational simulation, we succeeded in demonstrating a clear linear correlation between binding free energy and in vitro experimental IC50 value of several ALK-TKIs to single- or compound-mutated EML4-ALK expressing Ba/F3 cells and in recapitulating the tendency of the binding affinity reduction by double mutations found in this study. Computational simulation revealed that ALK-L1256F single mutant conferred resistance to lorlatinib but increased the sensitivity to alectinib. Interpretation: We discovered lorlatinib-resistant multiple ALK-compound mutations and an L1256F single mutation as well as the potential therapeutic strategies for these ALK mutations. Our original computational simulation to calculate the binding affinity may be applicable for predicting resistant mutations and for overcoming drug resistance in silico. Fund: This work was mainly supported by MEXT/JSPS KAKENHI Grants and AMED Grants.
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier BV
dc.rights© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
dc.subjectALK-rearranged lung cancer
dc.subjectResistant mutation
dc.subjectComputational simulation
dc.subjectMP-CAFEE
dc.subjectCompound mutation
dc.subjectQuantum chemistry
dc.titlePrediction of ALK mutations mediating ALK-TKIs resistance and drug re-purposing to overcome the resistance
dc.type.niitypeJournal Article
dc.identifier.jtitleEBioMedicine
dc.identifier.volume41
dc.identifier.spage105
dc.identifier.epage119
dc.relation.doi10.1016/j.ebiom.2019.01.019
dc.textversionpublisher
dc.identifier.pmid30662002
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