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Review
. 2025 Sep;20(5):767-789.
doi: 10.1007/s11523-025-01166-0. Epub 2025 Jul 18.

MET Alterations in Cancer and MET-Targeted Therapy: Detection Strategies, Treatment Efficacy, and Emerging Technologies

Affiliations
Review

MET Alterations in Cancer and MET-Targeted Therapy: Detection Strategies, Treatment Efficacy, and Emerging Technologies

Jieun Park et al. Target Oncol. 2025 Sep.

Abstract

The MET signaling pathway is dysregulated in several cancers through various mechanisms, including gene mutations, amplifications, rearrangements, and protein overexpression. MET inhibitors have demonstrated clinical benefits in solid tumors including non-small-cell lung cancer (NSCLC), highlighting the importance of optimizing MET alteration detection methods and cut-off values to enhance the efficacy of MET-targeted therapies and improve patient outcomes. Research on MET alterations has primarily focused on MET exon 14 skipping mutations, MET amplification, and MET overexpression. This review summarizes the frequency of MET alterations across different cancer types and the clinical validation of MET alterations in MET-targeted therapies, offering a detailed comparison of objective response rates (ORR) for therapies including crizotinib, capmatinib, tepotinib, savolitinib, telisotuzumab vedotin, telisotuzumab adizutecan, and amivantamab. The review also addresses the challenges in detecting MET exon 14 skipping mutations, such as issues with false positives and negatives, and underscores the need for standardization in MET amplification detection. Trials vary in their cut-offs for MET gene copy number (GCN) and MET/CEP7 ratio and MET expression detection methods, leading to inconsistencies in detection. Additionally, emerging technologies such as circulating tumor DNA (ctDNA) and circulating tumor cell (CTC) analyses have been investigated for their potential to improve MET alterations detection. This review also highlights studies that demonstrate the potential of MET ctDNA and CTC analyses to predict treatment responses and identify resistance mechanisms in MET-targeted therapies.

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Conflict of interest statement

Declarations. Funding: This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT (RS-2023-00217189) and Basic Science Research Program (NRF-2022R1A6A1A03046247, RS-2024-00451303) of the NRF funded by the Ministry of Education, Republic of Korea. Competing Interests: Jieun Park, Hun Seok Lee, and Young Kee Shin received consulting fees from Abion, Inc. Young Kee Shin currently holds stocks at ABION, Inc. Chaithanya Chelakkot, Ji-Hye Nam, Chae Rin Kim, Yeonwoo Lee, Mi-Sook Lee, and Yoon-La Choi declare that they have no conflicts of interest that might be relevant to the contents of this article. Ethics Approval: Not applicable. Consent to Participate: Not applicable. Consent for Publication: Not applicable. Data Availability: No new datasets were analyzed in the present study. Code Availability: Not applicable. Author Contributions: Conceptualization: Jieun Park, Young Kee Shin; Methodology, Jieun Park, Yeonwoo Lee, Mi-Sook Lee; writing–original draft preparation: Jieun Park, Chaithany Chelakkot, Ji-Hye Nam, Hun Seok Lee; writing–review and editing: Jieun Park, Chaithany Chelakkot, Ji-Hye Nam, Hun Seok Lee, Chae Rin Kim, Yoon-La Choi; supervision: Yoon-La Choi, Young Kee Shin. All authors have read and agreed to the published version of the article.

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