A superstatistical model of metastasis and cancer survival
L. Leon Chen, Christian Beck
TL;DR
This paper presents a superstatistical model that captures the complex, nonequilibrium dynamics of cancer metastasis, accurately predicting survival time distributions in breast cancer patients.
Contribution
It introduces a novel superstatistical framework modeling metastasis as a nonequilibrium system with multiple pathways and stochastic parameters, aligning well with observed data.
Findings
Model predictions match observed survival distributions
Metastasis pathways are effectively represented as complex nonequilibrium processes
Inverse-chi-square distributed parameters capture variability in metastasis dynamics
Abstract
We introduce a superstatistical model for the progression statistics of malignant cancer cells. The metastatic cascade is modeled as a complex nonequilibrium system with several macroscopic pathways and inverse-chi-square distributed parameters of the underlying Poisson processes. The predictions of the model are in excellent agreement with observed survival time probability distributions of breast cancer patients.
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Taxonomy
TopicsMathematical Biology Tumor Growth · Computational Drug Discovery Methods · Bioinformatics and Genomic Networks