DNA-Based versus RNA-Based Detection of MET Exon 14 Skipping Events in Lung Cancer

Kurtis D Davies1, Aprille Lomboy1, Carolyn A Lawrence1

  • 1Department of Pathology, Division of Pathology, University of Colorado-Anschutz Medical Campus, Aurora, Colorado.

Abstract

Insights

RNA-based sequencing is more effective than DNA-based methods for detecting MET exon 14 skipping variants in non-small cell lung cancer (NSCLC). This approach identifies more targetable mutations, improving patient care, though RNA quality is a consideration.

Area of Science:

  • Oncology
  • Molecular Diagnostics
  • Genetics

Background:

  • MET exon 14 skipping variants are targetable molecular abnormalities in non-small cell lung cancer (NSCLC).
  • Reliable molecular diagnostic approaches are crucial for identifying these variants to guide patient treatment.

Purpose of the Study:

  • To compare the efficacy of DNA-based and RNA-based next-generation sequencing (NGS) assays for detecting MET exon 14 skipping variants in NSCLC.
  • To evaluate the diagnostic yield and potential limitations of each sequencing approach.

Main Methods:

  • Screening of NSCLC tumor samples using two distinct NGS approaches: DNA-based (amplicon-mediated enrichment) and RNA-based (anchored multiplex PCR enrichment).
  • Direct comparison of results from both assays on a subset of samples to identify discrepancies and potential causes.

Main Results:

  • The RNA-based assay detected MET exon 14 skipping in 4.2% of samples, significantly higher than the 1.3% detected by the DNA-based assay.
  • Of 286 samples tested by both methods, RNA-based testing identified 10 positive cases, including 6 missed by the DNA-based assay.
  • Genomic deletions at primer binding sites were identified as a likely cause for false negatives in the DNA-based assay.

Conclusions:

  • RNA-based analysis offers a higher detection rate for MET exon 14 skipping variants by overcoming limitations of DNA-based amplicon-mediated testing.
  • The sensitivity of RNA-based testing is dependent on RNA quality, which can be a challenge with clinical samples.

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