| Literature DB >> 24211365 |
Catherine E Cottrell1, Hussam Al-Kateb2, Andrew J Bredemeyer1, Eric J Duncavage1, David H Spencer1, Haley J Abel3, Christina M Lockwood1, Ian S Hagemann1, Stephanie M O'Guin3, Lauren C Burcea3, Christopher S Sawyer3, Dayna M Oschwald3, Jennifer L Stratman1, Dorie A Sher1, Mark R Johnson3, Justin T Brown3, Paul F Cliften3, Bijoy George1, Leslie D McIntosh1, Savita Shrivastava1, Tudung T Nguyen1, Jacqueline E Payton1, Mark A Watson1, Seth D Crosby3, Richard D Head3, Robi D Mitra3, Rakesh Nagarajan1, Shashikant Kulkarni4, Karen Seibert1, Herbert W Virgin1, Jeffrey Milbrandt3, John D Pfeifer1.
Abstract
Currently, oncology testing includes molecular studies and cytogenetic analysis to detect genetic aberrations of clinical significance. Next-generation sequencing (NGS) allows rapid analysis of multiple genes for clinically actionable somatic variants. The WUCaMP assay uses targeted capture for NGS analysis of 25 cancer-associated genes to detect mutations at actionable loci. We present clinical validation of the assay and a detailed framework for design and validation of similar clinical assays. Deep sequencing of 78 tumor specimens (≥ 1000× average unique coverage across the capture region) achieved high sensitivity for detecting somatic variants at low allele fraction (AF). Validation revealed sensitivities and specificities of 100% for detection of single-nucleotide variants (SNVs) within coding regions, compared with SNP array sequence data (95% CI = 83.4-100.0 for sensitivity and 94.2-100.0 for specificity) or whole-genome sequencing (95% CI = 89.1-100.0 for sensitivity and 99.9-100.0 for specificity) of HapMap samples. Sensitivity for detecting variants at an observed 10% AF was 100% (95% CI = 93.2-100.0) in HapMap mixes. Analysis of 15 masked specimens harboring clinically reported variants yielded concordant calls for 13/13 variants at AF of ≥ 15%. The WUCaMP assay is a robust and sensitive method to detect somatic variants of clinical significance in molecular oncology laboratories, with reduced time and cost of genetic analysis allowing for strategic patient management.Entities:
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Year: 2013 PMID: 24211365 PMCID: PMC5762937 DOI: 10.1016/j.jmoldx.2013.10.002
Source DB: PubMed Journal: J Mol Diagn ISSN: 1525-1578 Impact factor: 5.568