Next-Generation Liquid Biopsies: Embracing Data Science in Oncology.

Deeper and broader sequencing of circulating tumor DNA (ctDNA) has identified a wealth of cancer markers in the circulation, resulting in a paradigm shift towards data science-driven liquid biopsies in oncology. Although panel sequencing for actionable mutations in plasma is moving towards the clinic, the next generation of liquid biopsies is increasingly shifting from analyzing digital mutation signals towards analog signals, requiring a greater role for machine learning. Concomitantly, there is an increasing acceptance that these cancer signals do not have to arise from the tumor itself. In this Opinion, we discuss the opportunities and challenges arising from increasingly complex cancer liquid biopsy data.

The translational potential of circulating tumour DNA in oncology.

The recent understanding of tumour heterogeneity and cancer evolution in response to therapy has raised questions about the value of historical or single site biopsies for guiding treatment decisions. The ability of ctDNA analysis to reveal de novo mutations (i.e., without prior knowledge), allows monitoring of clonal heterogeneity without the need for multiple tumour biopsies. Additionally, ctDNA monitoring of such heterogeneity and novel mutation detection will allow clinicians to detect resistant mechanisms early and tailor treatment therapies accordingly. If ctDNA can be used to detect low volume cancerous states, it will have important applications in treatment stratification post-surgery/radical radiotherapy and may have a role in patient screening. Mutant cfDNA can also be detected in other bodily fluids that are easily accessible and may aid detection of rare mutant alleles in certain cancer types. This article outlines recent advances in these areas.