# Spatial model predicts dispersal and cell turnover cause reduced intra-tumor heterogeneity

## TL;DR

This paper explains how cancer tumors remain genetically similar despite their size by showing how cell movement and turnover lead to rapid mixing and dominance of certain clones.

## Contribution

The paper introduces a spatial model showing how short-range migration and cell turnover explain tumor homogeneity and rapid resistance development.

## Key findings

- Short-range migration and cell turnover enable rapid mixing of tumor cells.
- A small selective advantage allows a single cell's descendants to dominate a large tumor quickly.
- The model explains how resistance to chemotherapy can emerge rapidly.

## Abstract

Most cancers in humans are large, measuring centimeters in diameter, composed of many billions of cells. An equivalent mass of normal cells would be highly heterogeneous as a result of the mutations that occur during each cell division. What is remarkable about cancers is their homogeneity - virtually every neoplastic cell within a large cancer contains the same core set of genetic alterations, with heterogeneity confined to mutations that have emerged after the last clonal expansions. How such clones expand within the spatially-constrained three dimensional architecture of a tumor, and come to dominate a large, pre-existing lesion, has never been explained. We here describe a model for tumor evolution that shows how short-range migration and cell turnover can account for rapid cell mixing inside the tumor. With it, we show that even a small selective advantage of a single cell within a large tumor allows the descendants of that cell to replace the precursor mass in a clinically relevant time frame. We also demonstrate that the same mechanisms can be responsible for the rapid onset of resistance to chemotherapy. Our model not only provides novel insights into spatial and temporal aspects of tumor growth but also suggests that targeting short range cellular migratory activity could have dramatic effects on tumor growth rates.