Clonal Diversity at Cancer Recurrence
Kevin Leder, Zicheng Wang

TL;DR
This paper develops a mathematical model to analyze clonal diversity at cancer recurrence, revealing that early recurrence is more likely driven by multiple mutations rather than a single dominant clone, with implications for treatment strategies.
Contribution
It introduces a two-type branching process model to quantify clonal diversity at recurrence and develops statistical methods to estimate model parameters from diversity indices.
Findings
Clonal diversity at recurrence is generally high, indicating multiple resistant clones.
Time to recurrence correlates with clonal diversity, serving as a potential prognostic indicator.
Early recurrence is more associated with high diversity, suggesting multiple mutation origins.
Abstract
Despite initial success, cancer therapies often fail due to the emergence of drug-resistant cells. In this study, we use a mathematical model to investigate how cancer evolves over time, specifically focusing on the state of the tumor when it recurs after treatment. We use a two-type branching process to capture the dynamics of both drug-sensitive and drug-resistant cells. We analyze the clonal diversity of drug-resistant cells at the time of cancer recurrence, which is defined as the first time the population size of drug-resistant cells exceeds a specified proportion of the initial population size of drug-sensitive cells. We examine two clonal diversity indices: the number of clones and the Simpson's Index. We calculate the expected values of these indices and utilize them to develop statistical methods for estimating model parameters. Additionally, we examine these two indices…
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Taxonomy
TopicsMathematical Biology Tumor Growth · Gene Regulatory Network Analysis · Evolution and Genetic Dynamics
