Validation of the Oncomine\u2122 focus panel for next-generation sequencing of clinical tumour samples

Hannah L Williams,Anca Oniscu,Kathy Walsh,Zandra C Deans,Austin Diamond

doi:10.1007/s00428-018-2411-4

Abstract

The clinical utility of next-generation sequencing (NGS) for a diverse range of targets is expanding, increasing the need for multiplexed analysis of both DNA and RNA. However, translation into daily use requires a rigorous and comprehensive validation strategy. The aim of this clinical validation was to assess the performance of the Ion Torrent Personal Genome Machine (IonPGM™) and validate the Oncomine™ Focus DNA and RNA Fusion panels for clinical application in solid tumour testing of formalin-fixed, paraffin-embedded (FFPE) tissue. Using a mixture of routine FFPE and reference material across a variety of tissue and specimen types, we sequenced 86 and 31 samples on the Oncomine™ Focus DNA and RNA Fusion assays, respectively. This validation considered a number of parameters including the clinical robustness of the bioinformatics pipeline for variant detection and interpretation. The Oncomine™ Focus DNA assay had a sample and variant-based sensitivity of 99.1 and 97.1%, respectively, and an assay specificity of 100%. The Oncomine™ Focus Fusion panel had a good sensitivity and specificity based upon the samples assessed, however requires further validation to confirm findings due to limited sample numbers. We observed a good sequencing performance based upon amplicon, gene (hotspot variants within gene) and sample specific analysis with 92% of clinical samples obtaining an average amplicon coverage above 500X. Detection of some indels was challenging for the routine IonReporter™ workflow; however, the addition of NextGENe® software improved indel identification demonstrating the importance of both bench and bioinformatic validation. With an increasing number of clinically actionable targets requiring a variety of methodologies, NGS provides a cost-effective and time-saving methodology to assess multiple targets across different modalities. We suggest the use of multiple analysis software to ensure identification of clinically applicable variants.

Highlights

Personalised medicine for the treatment of cancer provides directed therapy for patients based upon the genetic and epigenetic alterations of their disease
This study presents the validation of the OncomineTM Focus DNA and RNA panel on the Ion Torrent Personal Genome Machine (IonPGMTM, Thermo Fisher Scientific) for joint implementation within the Department of Molecular Pathology and United Kingdom National External Quality Assessment Service (UK NEQAS) for Molecular Genetics, Royal Infirmary of Edinburgh, UK
Seventy-eight anonymised FFPE tissues comprising of melanoma (n = 18), colorectal cancer (CRC) (n = 28), non-smallcell lung cancer (NSCLC) (n = 22) and gastrointestinal stromal tumours (GIST) (n = 10) were processed from a range of specimen types: resections (n = 57), biopsies (n = 13), cell blocks (n = 6), fine needle aspirate (FNA) (n = 1) and polyps (n = 1)

Summary

Introduction

Personalised medicine for the treatment of cancer provides directed therapy for patients based upon the genetic and epigenetic alterations of their disease. This requires laboratories to provide rapid assessment of the molecular landscape of the tumour to enable informed treatment decisions. Nextgeneration sequencing (NGS) enables the testing of multiple genes, from multiple patient samples across dual modalities in one assay. With increasing affordability enabling the implementation of NGS into clinical laboratories, validation of both assay and bioinformatic analytical pipelines are the primary challenges clinical laboratories face. To comply with ISO15189 accreditation [2], validation of the detection of somatic variants must, as a minimum, assess limit of detection, analytical sensitivity and specificity, repeatability and reproducibility and set appropriate thresholds and quality control parameters for reliable analysis of clinical specimens. Validation must include the handling of large amounts of data produced by multi-gene panels [3]

Methods

Results

Conclusion