Clinical validation of KRAS, BRAF, and EGFR mutation detection using next-generation sequencing

Area of Science:

• Genomics
• Molecular Diagnostics
• Bioinformatics

Background:

• Clinical molecular diagnostics increasingly rely on next-generation sequencing (NGS).
• Standardization of clinical testing for NGS is crucial for reliable diagnostic applications.
• Understanding potential artifacts in NGS data is essential for accurate interpretation.

Purpose of the Study:

• To validate next-generation sequencing (NGS) technology for clinical diagnosis.
• To determine the optimal read depth for accurate mutation detection using NGS.
• To assess the reliability of NGS for identifying clinically relevant gene mutations.

Main Methods:

• Validation of KRAS, BRAF, and EGFR genes using the Ion AmpliSeq Cancer Hotspot Panel on the Ion Torrent Personal Genome Machine.
• Development of a statistical model to define necessary read depth based on tumor cellularity and genome number.
• Analysis of 16 cancer-free and 118 cancer specimens with known mutation status.

Main Results:

• A statistical model was developed to guide read depth selection for accurate mutation detection.
• Baseline noise analysis revealed C:G→T:A deamination mutations consistent with FFPE artifacts.
• Validation confirmed the performance characteristics of NGS for clinical use.

Conclusions:

• Next-generation sequencing (NGS) is a robust technology for clinical gene mutation detection.
• Redundant bioinformatic pipelines are critical to mitigate false-negative and false-positive results.
• Careful consideration of potential artifacts is necessary for reliable NGS-based clinical diagnostics.