Literature DB >> 25209392

Performance of amplicon-based next generation DNA sequencing for diagnostic gene mutation profiling in oncopathology.

Daoud Sie1, Peter J F Snijders, Gerrit A Meijer, Marije W Doeleman, Marinda I H van Moorsel, Hendrik F van Essen, Paul P Eijk, Katrien Grünberg, Nicole C T van Grieken, Erik Thunnissen, Henk M Verheul, Egbert F Smit, Bauke Ylstra, Daniëlle A M Heideman.   

Abstract

PURPOSE: Next generation DNA sequencing (NGS) holds promise for diagnostic applications, yet implementation in routine molecular pathology practice requires performance evaluation on DNA derived from routine formalin-fixed paraffin-embedded (FFPE) tissue specimens. The current study presents a comprehensive analysis of TruSeq Amplicon Cancer Panel-based NGS using a MiSeq Personal sequencer (TSACP-MiSeq-NGS) for somatic mutation profiling.
METHODS: TSACP-MiSeq-NGS (testing 212 hotspot mutation amplicons of 48 genes) and a data analysis pipeline were evaluated in a retrospective learning/test set approach (n = 58/n = 45 FFPE-tumor DNA samples) against 'gold standard' high-resolution-melting (HRM)-sequencing for the genes KRAS, EGFR, BRAF and PIK3CA. Next, the performance of the validated test algorithm was assessed in an independent, prospective cohort of FFPE-tumor DNA samples (n = 75).
RESULTS: In the learning set, a number of minimum parameter settings was defined to decide whether a FFPE-DNA sample is qualified for TSACP-MiSeq-NGS and for calling mutations. The resulting test algorithm revealed 82% (37/45) compliance to the quality criteria and 95% (35/37) concordant assay findings for KRAS, EGFR, BRAF and PIK3CA with HRM-sequencing (kappa = 0.92; 95% CI = 0.81-1.03) in the test set. Subsequent application of the validated test algorithm to the prospective cohort yielded a success rate of 84% (63/75), and a high concordance with HRM-sequencing (95% (60/63); kappa = 0.92; 95% CI = 0.84-1.01). TSACP-MiSeq-NGS detected 77 mutations in 29 additional genes.
CONCLUSION: TSACP-MiSeq-NGS is suitable for diagnostic gene mutation profiling in oncopathology.

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Year:  2014        PMID: 25209392     DOI: 10.1007/s13402-014-0196-2

Source DB:  PubMed          Journal:  Cell Oncol (Dordr)        ISSN: 2211-3428            Impact factor:   6.730


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