Technical and implementation issues in using next-generation sequencing of cancers in clinical practice

Abstract

Next-generation sequencing (NGS) of cancer genomes promises to revolutionise oncology, with the ability to design and use targeted drugs, to predict outcome and response, and to classify tumours. It is continually becoming cheaper, faster and more reliable, with the capability to identify rare yet clinically important somatic mutations. Technical challenges include sequencing samples of low quality and/or quantity, reliable identification of structural and copy number variation, and assessment of intratumour heterogeneity. Once these problems are overcome, the use of the data to guide clinical decision making is not straightforward, and there is a risk of premature use of molecular changes to guide patient management in the absence of supporting evidence. Paradoxically, NGS may simply move the bottleneck of personalised medicine from data acquisition to the identification of reliable biomarkers. Standardised cancer NGS data collection on an international scale would be a significant step towards optimising patient care.

Figure 1

Framework for cancer genome analysis using NGS.