CC-BY 4.0
Cancers evolve from normal cells, and continue to evolve to evade treatment. Understanding evolution from tumourigenesis will allow for earlier detection of cancer, while predicting evolution of resistance mechanisms is essential for finding treatments that are effective in the long term.
We have developed a computational method for efficient search of potential evolutionary pathways from normal cells to cancer and applied this to breast cancer code, paper.
Based on this work, we have also developed a model of myeloproliferative neoplasms (MPNs) that unravels why these neoplasms have different behaviours dependent on the order in which they gain mutations, even if their mutational profiles are otherwise identical paper.
Image credit: Adapted from Talarmain et al., Nature Communications 2022 CC-BY 4.0
Matthew A. Clarke
Research Fellow
Research Fellow at PIBBSS (Principles of Intelligent Behavior in Biological and Social Systems) working on mechanistic interpratibility of large language models with sparse autoencoders.
Publications
Events
