Levy model of cancer

TL;DR

This paper models cancer risk as a stochastic process in gene expression space, combining small variations and large Levy jumps, and links it to tissue protection and infection resistance.

Contribution

It introduces a Levy jump-based model to describe microstate displacements in gene expression space related to cancer risk.

Findings

Levy jumps qualitatively match observed cancer lifetime risk

Model links tissue infection protection to cancer risk

Provides a new perspective on gene expression microstate dynamics

Abstract

A small portion of a tissue defines a microstate in gene expression space. Mutations, epigenetic events or external factors cause microstate displacements which are modeled by combining small independent gene expression variations and large Levy jumps, resulting from the collective variations of a set of genes. The risk of cancer in a tissue is estimated as the microstate probability to transit from the normal to the tumor region in gene expression space. The formula coming from the contribution of large Levy jumps seems to provide a qualitatively correct description of the lifetime risk of cancer, and reveals an interesting connection between the risk and the way the tissue is protected against infections.