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

• Published in: American journal of clinical pathology Vol. 141; no. 6; pp. 856 - 866
• Main Authors: Lin, Ming-Tseh, Mosier, Stacy L, Thiess, Michele, Beierl, Katie F, Debeljak, Marija, Tseng, Li-Hui, Chen, Guoli, Yegnasubramanian, Srinivasan, Ho, Hao, Cope, Leslie, Wheelan, Sarah J, Gocke, Christopher D, Eshleman, James R
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.06.2014
• Subjects: Biomarkers, Tumor - genetics; Deamination; High-Throughput Nucleotide Sequencing - methods; Limit of Detection; Molecular Diagnostic Techniques; Mutation; Neoplasms - diagnosis; Neoplasms - genetics; Paraffin Embedding; Proto-Oncogene Proteins - genetics; Proto-Oncogene Proteins B-raf - genetics; Proto-Oncogene Proteins p21(ras); ras Proteins - genetics; Receptor, Epidermal Growth Factor - genetics; Reproducibility of Results; Sensitivity and Specificity; Validation; Next-generation sequencing; Deamination; BRAF; KRAS; Read depth; EGFR
• ISSN: 0002-9173; 1943-7722
• DOI: 10.1309/ajcpmwgwgo34egod

To validate next-generation sequencing (NGS) technology for clinical diagnosis and to determine appropriate read depth. We validated the KRAS, BRAF, and EGFR genes within the Ion AmpliSeq Cancer Hotspot Panel using the Ion Torrent Personal Genome Machine (Life Technologies, Carlsbad, CA). We developed a statistical model to determine the read depth needed for a given percent tumor cellularity and number of functional genomes. Bottlenecking can result from too few input genomes. By using 16 formalin-fixed, paraffin-embedded (FFPE) cancer-free specimens and 118 cancer specimens with known mutation status, we validated the six traditional analytic performance characteristics recommended by the Next-Generation Sequencing: Standardization of Clinical Testing Working Group. Baseline noise is consistent with spontaneous and FFPE-induced C:G→T:A deamination mutations. Redundant bioinformatic pipelines are essential, since a single analysis pipeline gave false-negative and false-positive results. NGS is sufficiently robust for the clinical detection of gene mutations, with attention to potential artifacts.