Cell Competition Driven by Secreted Ligands: Modeling Liver Metastasis of Colorectal Cancer

TL;DR

This paper presents a mean-field model explaining cell competition in liver metastasis of colorectal cancer, focusing on secreted ligands and cell cycle dynamics, aligning with recent experimental observations.

Contribution

It introduces a mechanistic model of ligand-based cell competition coupled with cell cycle dynamics, providing insights into experimental findings and minimal complexity requirements.

Findings

Secretion of beneficial factors and enhanced uptake by cancer cells reproduce experimental competition outcomes.

The model links cell cycle variations to competitive dynamics.

Provides a general framework for growth-stage-dependent competition in biological populations.

Abstract

Cell competition in multicellular organisms has been shown to play a critical role during the development of organisms, cancer progression, and in the establishment and maintenance of tissue homeostasis. Various mechanisms of cell competition have been identified, including active elimination via mechanical forces or induced apoptosis, as well as competition for nutrients and other beneficial factors. A recent experiment demonstrated hallmarks of cell competition, associated with cell cycle dynamics, between liver progenitor cells and colorectal cancer cells [Krotenberg Garcia et al., iScience 27, 109718 (2024)]. However, a mechanistic explanation for this form of competition remains lacking. Here, we present a mean-field model of competition for signaling ligands, coupled with cell cycle dynamics, to provide such an understanding. Our model captures the salient features of the experiment, including population dynamics and cell cycle variations. We demonstrate that secretion of a beneficial factor by cells, coupled with the enhanced uptake efficiency of cancer cells, suffices to reproduce the experimental outcome. Our model, reminiscent of competition for secreted growth factors, provides insight into the minimal level of complexity required to achieve the observed competitive outcome as well as its link to cell cycle dynamics. It can also serve as a general framework for studying biological populations with growth-stage-dependent competition over consumer-produced products.