A pocket companion to cell-free DNA (cfDNA) preanalytics

Abstract

The cumulative pool of cell-free DNA (cfDNA) molecules within bodily fluids represents a highly dense and multidimensional information repository. This “biological mirror” provides real-time insights into the composition, function, and dynamics of the diverse genomes within the body, enabling significant advancements in personalized molecular medicine. However, effective use of this information necessitates meticulous classification of distinct cfDNA subtypes with exceptional precision. While cfDNA molecules originating from different sources exhibit numerous genetic, epigenetic, and physico-chemical variations, they also share common features that complicate analyses. Considerable progress has been achieved in mapping the landscape of cfDNA features, their clinical correlations, and optimizing extraction procedures, analytical approaches, bioinformatics pipelines, and machine learning algorithms. Nevertheless, preanalytical workflows, despite their profound impact on cfDNA measurements, have not progressed at a corresponding pace. In this perspective article, we emphasize the pivotal role of robust preanalytical procedures in the development and clinical integration of cfDNA assays, highlighting persistent obstacles and emerging challenges.