Automated next-generation profiling of genomic alterations in human cancers Journal Article


Authors: Keefer, L. A.; White, J. R.; Wood, D. E.; Gerding, K. M. R.; Valkenburg, K. C.; Riley, D.; Gault, C.; Papp, E.; Vollmer, C. M.; Greer, A.; Hernandez, J.; McGregor, P. M. 3rd; Zingone, A.; Ryan, B. M.; Deak, K.; McCall, S. J.; Datto, M. B.; Prescott, J. L.; Thompson, J. F.; Cerqueira, G. C.; Jones, S.; Simmons, J. K.; McElhinny, A.; Dickey, J.; Angiuoli, S. V.; Diaz, L. A. Jr; Velculescu, V. E.; Sausen, M.
Article Title: Automated next-generation profiling of genomic alterations in human cancers
Abstract: The lack of validated, distributed comprehensive genomic profiling assays for patients with cancer inhibits access to precision oncology treatment. To address this, we describe elio tissue complete, which has been FDA-cleared for examination of 505 cancer-related genes. Independent analyses of clinically and biologically relevant sequence changes across 170 clinical tumor samples using MSK-IMPACT, FoundationOne, and PCR-based methods reveals a positive percent agreement of >97%. We observe high concordance with whole-exome sequencing for evaluation of tumor mutational burden for 307 solid tumors (Pearson r = 0.95) and comparison of the elio tissue complete microsatellite instability detection approach with an independent PCR assay for 223 samples displays a positive percent agreement of 99%. Finally, evaluation of amplifications and translocations against DNA- and RNA-based approaches exhibits >98% negative percent agreement and positive percent agreement of 86% and 82%, respectively. These methods provide an approach for pan-solid tumor comprehensive genomic profiling with high analytical performance.
Keywords: microsatellite instability; lung-cancer; blockade; alignment; samples; tumor mutational burden
Journal Title: Nature Communications
Volume: 13
ISSN: 2041-1723
Publisher: Nature Publishing Group  
Date Published: 2022-05-20
Start Page: 2830
Language: English
ACCESSION: WOS:000799632400010
DOI: 10.1038/s41467-022-30380-x
PROVIDER: wos
PMCID: PMC9123004
PUBMED: 35595835
Notes: Article -- 2830 -- Source: Wos
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  1. Luis Alberto Diaz
    153 Diaz