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Background <p><i>MET</i> fusions represent emerging therapeutic targets in solid tumors; however, functional interpretation of non-canonical variants remains poorly understood, posing a major challenge for precision oncology.</p> Methods <p>We conducted a multicenter, pan-cancer study analyzing 23,299 clinical samples using DNA-based next-generation sequencing (NGS) to profile <i>MET</i> fusions. Transcriptional validation was performed using RNA-based NGS on available samples. Preliminary clinical outcomes were assessed in four patients with advanced malignancies harboring uncommon <i>MET</i> fusions who received <i>MET</i> tyrosine kinase inhibitor therapy.</p> Results <p>We identified 116 <i>MET</i> fusions (incidence: 0.5%), with 55.2% (64/116) classified as uncommon fusions. These uncommon fusions were stratified into: Group A (5’-retained, <i>n</i> = 12), Group B (intergenic/exonic breakpoints, <i>n</i> = 19), Group C (rare partners, <i>n</i> = 23), and Group D (dual fusions, <i>n</i> = 10). RNA validation revealed an overall low transcriptional consistency of 43.8% (14/32) for uncommon fusions, versus 100% for canonical fusions (<i>PTPRZ1::MET</i>, <i>CAPZA2::MET</i>). Notably, most 5’-retained fusions were transcriptionally silent, while some intergenic fusions resolved into expressed canonical partners (e.g. <i>PTPRZ1::MET</i>). Therapeutically, all four <i>MET</i> inhibitor-treated patients achieved partial responses, including pediatric diffuse midline gliomas (DMG) (median OS: 11.2 months) and lung adenocarcinoma (median OS: 34 months), demonstrating preliminary clinical activity.</p> Conclusions <p>uncommon <i>MET</i> fusions are heterogeneous at genomic and transcriptional levels. DNA-level findings often do not predict functional transcripts, underscoring the necessity of RNA-based confirmation for clinical interpretation. Despite low overall consistency, a subset retains therapeutic potential. We propose a refined diagnostic framework integrating DNA-based stratification and RNA validation to guide the management of <i>MET</i>-altered cancers in precision oncology workflows.</p>

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Clinically actionable stratification of uncommon MET fusions: a precision oncology framework

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月29日

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  • Wenhui Yang,
  • Yanxiang Zhang,
  • Tonghui Ma,
  • Haiyang Liang,
  • Qingsheng Xu,
  • Mingyao Lai,
  • Lusheng Li,
  • Haozhe Piao

摘要

Background

MET fusions represent emerging therapeutic targets in solid tumors; however, functional interpretation of non-canonical variants remains poorly understood, posing a major challenge for precision oncology.

Methods

We conducted a multicenter, pan-cancer study analyzing 23,299 clinical samples using DNA-based next-generation sequencing (NGS) to profile MET fusions. Transcriptional validation was performed using RNA-based NGS on available samples. Preliminary clinical outcomes were assessed in four patients with advanced malignancies harboring uncommon MET fusions who received MET tyrosine kinase inhibitor therapy.

Results

We identified 116 MET fusions (incidence: 0.5%), with 55.2% (64/116) classified as uncommon fusions. These uncommon fusions were stratified into: Group A (5’-retained, n = 12), Group B (intergenic/exonic breakpoints, n = 19), Group C (rare partners, n = 23), and Group D (dual fusions, n = 10). RNA validation revealed an overall low transcriptional consistency of 43.8% (14/32) for uncommon fusions, versus 100% for canonical fusions (PTPRZ1::MET, CAPZA2::MET). Notably, most 5’-retained fusions were transcriptionally silent, while some intergenic fusions resolved into expressed canonical partners (e.g. PTPRZ1::MET). Therapeutically, all four MET inhibitor-treated patients achieved partial responses, including pediatric diffuse midline gliomas (DMG) (median OS: 11.2 months) and lung adenocarcinoma (median OS: 34 months), demonstrating preliminary clinical activity.

Conclusions

uncommon MET fusions are heterogeneous at genomic and transcriptional levels. DNA-level findings often do not predict functional transcripts, underscoring the necessity of RNA-based confirmation for clinical interpretation. Despite low overall consistency, a subset retains therapeutic potential. We propose a refined diagnostic framework integrating DNA-based stratification and RNA validation to guide the management of MET-altered cancers in precision oncology workflows.