Modeling cancer rearrangement landscapes.

Cancer genome sequences contain footprints of somatic mutational processes, whose analysis in large tumor sequencing datasets has revealed novel mutational signatures, correlative features of variant topography, and complex events. Many of these analytic results have yet to reconciled with decades of mechanistic genome integrity research performed in controlled model systems. However, a new generation of genome-integrity experiments combining computational modeling, data analytics, and high-throughput sequencing are emerging to link mechanisms to patterns. Conversely, analytic studies evaluating quantitative footprints of specific genome integrity hypotheses will be critical in fitting naturally occurring mutational patterns to the predictions of a particular mechanistic model. Such quantitative and mechanistic studies will form the foundation of an emerging systems biology of genome integrity.