Dynamic molecular monitoring in haematological malignancies using ctDNA

Recent technological advances in the detection and characterization of circulating tumor DNA (ctDNA) are providing new opportunities for tailoring treatment based on real-time monitoring of clonal evolution. The emerging clinical benefits of ctDNA analysis in the management of solid tumours has led to an expansion of opportunities in the use of ctDNA for disease monitoring in haematological malignancies. Research in this area has rapidly expanded exploring the role of ctDNA for risk stratification, monitoring tumour burden and identifying the early emergence of treatment resistance. In the management of lymphoma, comprehensive analysis of somatic genomic alterations in plasma DNA has emerged as an important clinical tool. The use of ctDNA to follow tumour specific genomic alterations identified on an individual basis can be used to help identify minimal residual disease post treatment, guide therapeutic decisions and identify mechanisms of treatment resistance. Moreover, ctDNA can been utilized to identify distinct biological subtypes of lymphoma and provide insights into patterns of genomic evolution following treatment. The role of ctDNA as a minimally invasive strategy for disease monitoring has also recently been demonstrated in chronic lymphocytic leukaemia (CLL) showing additional potential of this technique in haematological malignancies with a circulating disease component. In CLL, ctDNA can reveal changes in the disease across tissue compartments, including the bone marrow and lymph nodes, providing additional information to that which can be assessed by monitoring the circulating disease alone. Serial ctDNA analysis in CLL can allow clonal dynamics to be monitored over time and can identify the emergence of genomic changes associated with Richter’s syndrome. Here, I will focus on the use of ctDNA to follow disease burden and track genomic changes in patients receiving novel therapies for haematological malignancies. I will highlight emerging data illustrating the promise and challenges in developing these tools for clinical application.