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Prediction of Resistance Mutations Against Upcoming Anaplastic Lymphoma Kinase Inhibitors

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Abstract

Background

Chromosomal aberrations involving the anaplastic lymphoma kinase (ALK) gene have been observed in approximately 4% of patients with non-small cell lung cancer (NSCLC). Although these patients clinically benefit from treatment with various ALK tyrosine kinase inhibitors (ALK-TKIs), none of these can inhibit the development of resistance mutations. Considering inevitable drug resistance and the variety of available ALK-TKIs, it is necessary to predict the pattern of drug-resistance mutations to determine the optimal treatment strategy.

Objective

We aimed to establish a polymerase chain reaction (PCR)-based system to predict the development of resistance mutations against ALK-TKIs and identify therapeutic strategies using the upcoming ALK-TKIs repotrectinib (TPX-0005) and ensartinib (X-396) following recurrence on first-line alectinib treatment for ALK-positive NSCLC.

Methods

An error-prone PCR-based method for predicting drug resistance mutations was established and the half-maximal inhibitory concentration (IC50) values of the predicted ALK mutations were evaluated in a Ba/F3 cell-based assay.

Results

We predicted several resistance mutations against repotrectinib and ensartinib, and demonstrated that the next-generation ALK-TKI TPX-0131, was active against repotrectinib-resistant mutations and that the FLT3 inhibitor gilteritinib was active against ensartinib-resistant mutations.

Conclusions

We developed a PCR-based system for predicting drug resistance mutations. When this system was applied to repotrectinib and ensartinib, the results suggested that these drugs can be used for the second-line treatment of ALK-positive NSCLC. Predicting resistance mutations against TKIs will provide useful information to aid in the development of effective therapeutic strategies.

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Acknowledgements

The authors would like to thank Enago (http://www.enago.jp) for the English language review, and Prof. T. Kitamura (Institute of Medical Science, The University of Tokyo, Tokyo, Japan) for kindly providing the Plat-E cell line. The authors appreciate Dr. Fujimoto (Japan Biological Informatics Consortium [JBIC], Tokyo, Japan) and laboratory members for valuable discussion.

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Authors and Affiliations

  1. Department of Life Science and Medical Bioscience, Graduate School of Advanced Science and Engineering, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo, 162-8480, Japan

    Yuta Doi, Hiroaki Tagaya, Ayaka Noge & Kentaro Semba

  2. Translational Research Center, Fukushima Medical University, Hikarigaoka, Fukushima, 960-1295, Japan

    Kentaro Semba

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  1. Yuta Doi
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Correspondence to Kentaro Semba.

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Funding

This study was partly supported by the Fukushima Translational Research Project program.

Conflict of interest

Yuta Doi, Hiroaki Tagaya, Ayaka Noge, and Kentaro Semba declare that they have no conflicts of interest that might be relevant to the contents of this manuscript.

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Availability of data and material

The datasets generated during the current study are available from the corresponding author upon reasonable request.

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Author contributions

KS conceived and designed this study. YD, HT, and AN performed the experiments and analyzed the data. YD and KS interpreted the data and wrote the manuscript. All authors reviewed and edited the manuscript.

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Doi, Y., Tagaya, H., Noge, A. et al. Prediction of Resistance Mutations Against Upcoming Anaplastic Lymphoma Kinase Inhibitors. Targ Oncol 17, 695–707 (2022). https://doi.org/10.1007/s11523-022-00919-5

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