Finding Mechanisms of Resistance In Cancer

Cancer evolves by sequentially acquiring driver events that increase the fitness of the cells, going from normal, to pre-cancer clonal expansion, to cancer and finally to becoming resistant to therapy. The cancer cells can leverage different mechanisms to evade the therapeutic pressure and develop drug resistance. In order to delay or prevent resistance, one needs to map and understand these mechanisms which can then lead to targets for developing new drugs as well as guide the selection of combinations of therapies that have non-overlapping mechanisms of

resistance. In this presentation, I will discuss different approaches for finding mechanisms of resistance, including studying pre-treatment and post-resistance samples; estimating clonal fitness; and identifying convergent evolution across subclones. Rich phylogenetic trees can be used to identify convergent evolution, a strong statistical signal of positive selection. Such trees can be built based on analyzing multiple tumor samples from the same patient, obtained from liquid biopsies and rapid autopsies. I will give examples from studying resistance in breast cancer and describe novel analytical approaches for detecting convergent evolution. Finally, I will demonstrate the benefit of using whole-genome sequencing data to further enrich the detection of resistance mechanisms.