Tumour evolution is a complex and multifaceted process that arises from the driving forces of carcinogenesis. As cancer progresses, distinct cellular populations with inheritable genetic characteristics can be observed within a single tumour. The ability to trace the progression of a cancer, by identifying sub-populations and inferring the relationships between them from shared genetic features, has only recently become feasible. Next-generation sequencing technologies are able to provide fine-grained genomic data which can quantify the relationships between intra-tumour populations as well as distant metastases. Understanding these relationships using methods of phylogenetic reconstruction can inform the evolution of invasive or metastatic genetic changes in the evolutionary history of a cancer. This information can assist in prognostication and prediction of cancer evolution in a clinical setting.
Particularly in prostate cancer, structural variations (SVs) are commonly observed events that consist of large-scale mutational changes in the genome. By comparing multiple cancer samples from the same patient, distinct cellular populations and their ancestral relationships can be de-convolved and the occurrence of a particular SV within a cancer's evolution can be estimated. We present a method that seeks to reconstruct the phylogenetic relationships of a tumour's sub-clonal cellular populations using structural variation data, detected using the Socrates[1] algorithm. We demonstrate that tumour phylogenies are able to be reconstructed with SV data alone, and that SVs can provide useful insights into evolutionary pathways that lead to metastasis.