91P - Implications of key differences across 12 KRAS mutation detection technologies and their relevance in clinical practice

Date 10 October 2016
Event ESMO 2016 Congress
Session Poster display
Topics Biomarkers
Presenter James Sherwood
Citation Annals of Oncology (2016) 27 (6): 15-42. 10.1093/annonc/mdw363
Authors J.L. Sherwood1, A. Rettino2, H. Brown1, A. Schreieck3, B. Claes4, B. Agrawal5, G. Clark6, R. Chaston7, P. Choppa8, A.O.H. Nygren9, A. Kohlman1
  • 1Imed Biotech Unit: Personalised Healthcare & Biomarkers, AstraZeneca, CB40WG - Cambridge/GB
  • 2West Midlands Regional Genetics Laboratory, Birmingham Women's NHS Foundation Trust, Birmingham/GB
  • 3R&d, IMGM Laboratories GmbH, Martinsried/DE
  • 4R&d, Biocartis NV, Mechelen/BE
  • 5Chief Medical Officer, Vela Diagnostics Pte Ltd, Singapore/SG
  • 6Medical Genetics, University of Cambridge, Cambridge/GB
  • 7R&d, Leica Biosystems, Newcastle upon Tyne/GB
  • 8Clinical Sequencing Division, Thermo Fisher Scientific, West Sacramento/US
  • 9R&d, Agena Bioscience, San Diego/US

Abstract

Background

This study assessed, for the first time, KRAS mutation detection and functional characteristics across 12 distinct platforms and chemistries available in clinical practice.

Methods

5 distinct KRAS-mutant cell lines (MIA PACA-2, PANC-1, MDA-MB231, SW620 and NCI-H460) were obtained from AstraZeneca, Alderley Park Cell Bank, and 5 clinically relevant KRAS mutations were studied: p.G12C, p.G12D and p.G12V, p.G13D and p.Q61H. 50 cell line admixtures with low (50 and 100) mutant KRAS allele copies at 20, 10, 5, 1 and 0.5% frequency were analysed using qPCR (n = 3), digital PCR (n = 1), capillary sequencing (n = 1), NGS (n = 5) and MALDI-TOF (n = 2) assays.

Results

Important performance differences were revealed which could impact patient treatment decisions, particularly sensitivity, regulatory status (e.g. CE-IVD) and turnaround time. Only 384/672 data points across all 12 methods were identified correctly. Successful genotyping of admixtures ranged from 0% (Sanger sequencing) to 100% (NGS). 4/5 NGS platforms reported similar allelic frequency for each sample. Of these, one was able to detect mutations down to a frequency of 0.1% and correctly identify all 56 samples (Oncomine™ Focus Assay, Thermo Fisher Scientific). A qPCR near impact device (Idylla™, Biocartis) and MALDI-TOF (UltraSEEK™, Agena Bioscience) accurately identified 96% (all 100 copies & 23/25 50 copies input) and 93% (23/25 100 copies & 23/25 50 copies input) of samples, respectively. Conversely, the digital PCR assay (KRAS PrimePCR™ ddPCR™, Bio-Rad Laboratories, Inc.) was non-specific, identifying the wrong mutation in 8 different mutation/allele frequency combinations. Turnaround time from clinical sample to result ranged from ∼2 hours (Idylla™ CE-IVD) to 1 day (cobas® CE-IVD) to >1 week for most NGS assays, while the level of required laboratory expertise ranged from minimal (Idylla™ CE-IVD) to high (NGS platforms).

Conclusions

This comprehensive parallel assessment used high molecular weight cell-line DNA as a model to address key questions for a clinical laboratory when implementing routine KRAS testing. As most of the technologies are available for other molecular biomarkers, results may be informative for other diagnostic functions.

Clinical trial identification

N/A

Legal entity responsible for the study

AstraZeneca

Funding

AstraZeneca

Disclosure

J.L. Sherwood, H. Brown, A. Kohlman: Employee of and shareholder in AstraZeneca London. A. Schreieck: institution received financial support for molecular analysis from AstraZeneca. B. Claes: Reports a patent pending for isolation of nucleic acids. B. Agrawal: Employee of Vela Diagnostics.A.O.H. Nygren: Employee of and shareholder in Agena Bioscience. All other authors have declared no conflicts of interest.