Thick distribution tails in models of cancer secondary tumors

TL;DR

This paper introduces a mathematically rigorous model of multifocal tumor development showing heavy-tailed size distributions and finite-time infinite moments, supported by numerical simulations and recent empirical observations.

Contribution

It refines previous models into an infinite-type branching process, revealing heavy-tailed tumor size distributions with finite-time infinite moments, advancing understanding of tumor growth dynamics.

Findings

Tumor size distributions have heavy tails.

Moments of the distribution become infinite in finite time.

Model aligns with observed super-exponential growth in metastases.

Abstract

Recent progress in microdissection and in DNA sequencing has enabled subsampling of multi-focal cancers in organs such as the liver in several hundred spots, helping to determine the pattern of mutations in each of these spots. This has led to the construction of genealogies of the primary, secondary, tertiary and so forth, foci of the tumor. These studies have led to diverse conclusions concerning the Darwinian (selective) or neutral evolution in cancer. Mathematical models of development of multifocal tumors have been developed to support these claims. We report a model of development of a multifocal tumor, which is a mathematically rigorous refinement of a model of Ling et al. (2015). Guided by numerical studies and simulations, we show that the rigorous model, in the form of an infinite-type branching process, displays distributions of tumors size which have heavy tails and moments that become infinite in finite time. To demonstrate these points, we obtain bounds on the tails of the distributions of the process and infinite-series expression for the first moments. In addition to its inherent mathematical interest, the model is corroborated by recent reports of apparent super-exponential growth in cancer metastases.