Fusion Gene Detection in Driver Mutation-Negative Melanomas Using RNA-Based Anchored Multiplex Polymerase Chain

Tokimasa Hida1, Masashi Idogawa2, Sayuri Sato1

  • 1Department of Dermatology, Sapporo Medical University School of Medicine, Sapporo, Japan.

PubMed

Insights

Fusion genes were identified in Japanese melanomas lacking common mutations, offering new therapeutic targets. This RNA-based approach detects actionable gene fusions in driver-negative melanoma.

Area of Science:

  • Oncology
  • Genetics
  • Molecular Biology

Background:

  • Advanced melanoma treatment relies on immune checkpoint inhibitors (ICIs) and targeted therapies.
  • Efficacy of current treatments is limited in acral and mucosal melanomas, common in non-White populations.
  • These melanoma subtypes often lack major driver mutations like BRAF, necessitating alternative therapeutic strategies.

Purpose of the Study:

  • To detect fusion genes in Japanese melanomas that lack common driver mutations (BRAF, RAS, NF1, KIT).
  • To evaluate the utility of RNA-based anchored multiplex polymerase chain reaction (AMP) for identifying fusion genes in clinical samples.

Main Methods:

  • Analysis of RNA from 14 Japanese melanoma tumors, mostly formalin-fixed paraffin-embedded.
  • Utilized a custom Archer FUSIONPlex panel for RNA-based fusion detection.
  • Developed and validated an anchored multiplex PCR (AMP) workflow, including quality control.

Main Results:

  • Successfully generated libraries from 80% of analyzed samples.
  • Identified two in-frame fusion genes: MAD1L1::BRAF and CIC::MEGF8 (17% of cases).
  • MAD1L1::BRAF retains the BRAF kinase domain, suggesting potential MEK inhibitor targeting. CIC::MEGF8 is a novel fusion potentially causing transcriptional dysregulation.

Conclusions:

  • RNA-based fusion detection is a valuable method for driver-negative melanomas.
  • Fusion genes represent promising actionable therapeutic targets for specific melanoma subtypes.
  • The described AMP workflow is applicable to clinical samples for fusion gene identification.