Inter-Laboratory Evaluation of a Next-Generation Sequencing Panel for Acute Myeloid Leukemia

INTRODUCTION: Acute myeloid leukemia (AML) is a heterogeneous clonal disorder often associated with dismal overall survival. The clinical diversity of AML is reflected in the range of recurrent somatic mutations in several genes, many of which have a prognostic and therapeutic value. Targeted next-generation sequencing (NGS) of these genes has the potential for translation into clinical practice. In order to assess this potential, an inter-laboratory evaluation of a commercially available AML gene panel across three diagnostic centres in the UK and Ireland was performed.

METHODS: DNA from six AML patient samples was distributed to each centre and processed using a standardised workflow, including a common sequencing platform, sequencing chips and bioinformatics pipeline. A duplicate sample in each centre was run to assess inter- and intra-laboratory performance.

RESULTS: An average sample read depth of 2725X (range 629-5600) was achieved using six samples per chip, with some variability observed in the depth of coverage generated for individual samples and between centres. A total of 16 somatic mutations were detected in the six AML samples, with a mean of 2.7 mutations per sample (range 1-4) representing nine genes on the panel. 15/16 mutations were identified by all three centres. Allelic frequencies of the mutations ranged from 5.6 to 53.3 % (median 44.4 %), with a high level of concordance of these frequencies between centres, for mutations detected.

CONCLUSION: In this inter-laboratory comparison, a high concordance, reproducibility and robustness was demonstrated using a commercially available NGS AML gene panel and platform.

Understanding next generation sequencing in oncology: A guide for oncologists

DNA sequencing is now faster and cheaper than ever before, due to the development of next generation sequencing (NGS) technologies. NGS is now widely used in the research setting and is becoming increasingly utilised in clinical practice. However, due to evolving clinical commitments, increased workload and lack of training opportunities, many oncologists may be unfamiliar with the terminology and technology involved. This can lead to oncologists feeling daunted by issues such as how to interpret the vast amounts of data generated by NGS and the differences between sequencing platforms. This review article explains common concepts and terminology, summarises the process of DNA sequencing (including data analysis) and discusses the main factors to consider when deciding on a sequencing method. This article aims to improve oncologists' understanding of the most commonly used sequencing platforms and the ongoing challenges faced in expanding the use of NGS into routine clinical practice.

Towards automated Android app collusion detection

Android OS supports multiple communication methods between apps. This opens the possibility to carry out threats in a collaborative fashion, c.f. the Soundcomber example from 2011. In this paper we provide a concise definition of collusion and report on a number of automated detection approaches, developed in co-operation with Intel Security.