Prediction of ALK mutations mediating ALK-TKIs resistance and drug re-purposing to overcome the resistance.
Aminopyridines
Anaplastic Lymphoma Kinase
/ antagonists & inhibitors
Animals
Antineoplastic Agents
/ pharmacology
Carcinoma, Non-Small-Cell Lung
/ drug therapy
Cell Line, Tumor
Drug Resistance, Neoplasm
HEK293 Cells
Humans
Lactams
Lactams, Macrocyclic
/ pharmacology
Lung Neoplasms
/ drug therapy
Mice
Mice, Inbred BALB C
Mice, Nude
Molecular Dynamics Simulation
Mutation, Missense
Protein Binding
Protein Kinase Inhibitors
/ pharmacology
Pyrazoles
Pyrimidines
/ pharmacology
Software
Sulfones
/ pharmacology
ALK-rearranged lung cancer
Compound mutation
Computational simulation
MP-CAFEE
Quantum chemistry
Resistant mutation
Journal
EBioMedicine
ISSN: 2352-3964
Titre abrégé: EBioMedicine
Pays: Netherlands
ID NLM: 101647039
Informations de publication
Date de publication:
Mar 2019
Mar 2019
Historique:
received:
08
08
2018
revised:
08
01
2019
accepted:
08
01
2019
pubmed:
22
1
2019
medline:
23
7
2019
entrez:
22
1
2019
Statut:
ppublish
Résumé
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. 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). 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 IC 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.
Sections du résumé
BACKGROUND
BACKGROUND
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
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
RESULTS
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 IC
INTERPRETATION
CONCLUSIONS
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.
Identifiants
pubmed: 30662002
pii: S2352-3964(19)30024-6
doi: 10.1016/j.ebiom.2019.01.019
pmc: PMC6441848
pii:
doi:
Substances chimiques
Aminopyridines
0
Antineoplastic Agents
0
Lactams
0
Lactams, Macrocyclic
0
Protein Kinase Inhibitors
0
Pyrazoles
0
Pyrimidines
0
Sulfones
0
ALK protein, human
EC 2.7.10.1
Anaplastic Lymphoma Kinase
EC 2.7.10.1
ceritinib
K418KG2GET
lorlatinib
OSP71S83EU
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
105-119Informations de copyright
Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.
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