Comprehensive routine diagnostic screening to identify predictive mutations, gene amplifications, and microsatellite instability in FFPE tumor material

Elisabeth M P Steeghs, Leonie I Kroeze, Bastiaan B J Tops, Leon C van Kempen, Arja Ter Elst, Annemiek W M Kastner-van Raaij, Sandra J B Hendriks-Cornelissen, Mandy J W Hermsen, Erik A M Jansen, Petra M Nederlof, Ed Schuuring, Marjolijn J L Ligtenberg, Astrid Eijkelenboom*

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

6 Citaten (Scopus)
42 Downloads (Pure)

Samenvatting

Background: Sensitive and reliable molecular diagnostics is needed to guide therapeutic decisions for cancer patients. Although less material becomes available for testing, genetic markers are rapidly expanding. Simultaneous detection of predictive markers, including mutations, gene amplifications and MSI, will save valuable material, time and costs. Methods: Using a single-molecule molecular inversion probe (smMIP)-based targeted next-generation sequencing (NGS) approach, we developed an NGS panel allowing detection of predictive mutations in 33 genes, gene amplifications of 13 genes and microsatellite instability (MSI) by the evaluation of 55 microsatellite markers. The panel was designed to target all clinically relevant single and multiple nucleotide mutations in routinely available lung cancer, colorectal cancer, melanoma, and gastro-intestinal stromal tumor samples, but is useful for a broader set of tumor types. Results: The smMIP-based NGS panel was successfully validated and cut-off values were established for reliable gene amplification analysis (i.e. relative coverage ≥3) and MSI detection (≥30% unstable loci). After validation, 728 routine diagnostic tumor samples including a broad range of tumor types were sequenced with sufficient sensitivity (2.4% drop-out), including samples with low DNA input (< 10 ng; 88% successful), low tumor purity (5-10%; 77% successful), and cytological material (90% successful). 75% of these tumor samples showed ≥1 (likely) pathogenic mutation, including targetable mutations (e.g. EGFR, BRAF, MET, ERBB2, KIT, PDGFRA). Amplifications were observed in 5.5% of the samples, comprising clinically relevant amplifications (e.g. MET, ERBB2, FGFR1). 1.5% of the tumor samples were classified as MSI-high, including both MSI-prone and non-MSI-prone tumors. Conclusions: We developed a comprehensive workflow for predictive analysis of diagnostic tumor samples. The smMIP-based NGS analysis was shown suitable for limited amounts of histological and cytological material. As smMIP technology allows easy adaptation of panels, this approach can comply with the rapidly expanding molecular markers.

Originele taal-2English
Artikelnummer291
Aantal pagina's15
TijdschriftBMC Cancer
Volume20
Nummer van het tijdschrift1
DOI's
StatusPublished - 7-apr-2020

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