Large Deviations of Cancer Recurrence Timing

TL;DR

This paper models the timing of cancer recurrence and resistance development using a two-type branching process, analyzing large deviations in recurrence and crossover times to understand early failure events.

Contribution

It introduces a novel two-type branching process model for cancer recurrence, deriving large deviation rates for early recurrence and resistance crossover times.

Findings

Large deviation rates depend on initial mutant population size.

Recurrence before expected law of large numbers often involves more mutant clones.

The model characterizes how resistance timing varies with initial conditions.

Abstract

We study large deviation events in the timing of disease recurrence. In particular, we are interested in modeling cancer treatment failure due to mutation-induced drug resistance. We first present a two-type branching process model of this phenomenon, where an initial population of cells that are sensitive to therapy can produce mutants that are resistant to the therapy. In this model, we investigate two random times, the recurrence time and the crossover time. Recurrence time is defined as the first time that the population size of mutant cells exceeds a given proportion of the initial population size of drug-sensitive cells. Crossover time is defined as the first time that the resistant cell population dominates the total population. We establish convergence in probability results for both recurrence and crossover time. We then develop expressions for the large deviations rate of early recurrence and early crossover events. We characterize how the large deviation rates and rate functions depend on the initial size of the mutant cell population. We finally look at the large deviations rate of early recurrence conditioned on the number of mutant clones present at recurrence in the special case of a deterministically decaying sensitive population. We find that if recurrence occurs before the predicted law of large numbers limit then there will likely be an increase in the number of clones present at recurrence time.