Computational Methods for Monitoring The Evolution of Tumours
Cancer is a disease of the genome that disrupt the cells’ key functions and make them grow uncontrollably. DNA sequencing projects have led us to discover that cancer cells involve many genetic changes and that even in a single tumour, there are often multiple cancer cell populations that each carry their own mutations.
Understanding this collection of mutations is important because we need to select therapies that kill all of the cancer cells, not just some of them. Unfortunately, existing computer programs for analyzing “normal” human genome data generated by genome sequencing technologies are limited in scope because they cannot fully characterize all the mutations present in the individual cells of a tumour tissue.
Ideally, researchers would like to monitor how the genomes of cancer cells mutate over time, and how cancer cells travel through the blood stream or the urinary tract and colonize other tissues, forming metastatic tumours. The new liquid biopsy technology has made it possible to capture tumour DNA circulating in the blood stream and to sequence it, however analyzing such data and identifying the spectrum of mutations in an individual patient will require new mathematical and computational approaches.