Mathematical model of colorectal cancer initiation
Abstract: Cancer evolution cannot be observed directly in patients, and new methodologies are needed for obtaining a quantitative understanding of this obscure process. We developed and analyzed a stochastic model of malignant transformation in the colon that precisely quantifies the process of colorectal carcinogenesis in patients through loss of tumor suppressors APC and TP53 and gain of the KRAS oncogene. Our study employs experimentally measured mutation rates in the colon and growth advantages provided by driver mutations. We calculate the probability of a colorectal malignancy, the sizes of premalignant lesions, and the order of acquisition of driver mutations during colorectal tumor evolution. We demonstrate that the order of driver events in colorectal cancer is determined primarily by the fitness effects that they provide, rather than their mutation rates.
Bio: Dr. Bozic is an assistant professor in the Department of Applied Mathematics at the University of Washington. She received BSc and MA degrees in Mathematics from the University of Belgrade, Serbia, and a PhD in Mathematics from Harvard University. Dr. Bozic research interests include mathematical and computational modeling of biological systems, in particular cancer evolution, and analysis of genomic and clinical data. She is the recipient of a 2021 NSF CAREER award.
Meeting ID: 954 0887 3063