Spatial heterogeneity in tumor adhesion qualifies collective cell invasion

Area of Science:

• Computational biology
• Cancer research
• Biophysics

Background:

• Collective cell invasion (CCI) is crucial in solid tumors, driven by cancer cell and extracellular matrix (ECM) interactions.
• Tumor cell populations exhibit variable adhesion protein expression, complicating the understanding of how spatial heterogeneity influences multicellular invasion.

Purpose of the Study:

• To investigate how spatial heterogeneity of cell-cell and cell-ECM adhesion affects collective cell invasion.
• To model tumor invasiveness using a multiscale computational framework based on glandular cancer histopathology.

Main Methods:

• Utilized a Cellular Potts model-based multiscale computational framework.
• Simulated tumor cores composed of two distinct cell subsets with varied adhesion strengths.
• Introduced a heterogeneity index (HI) to quantify spatial intermingling of cell subsets.

Main Results:

• Low and high inter-subset cell adhesion differentially favored invasion in high-HI and low-HI populations, respectively.
• High heterogeneity index (HI) populations generally showed better collective invasion, especially with varied cell-ECM adhesion.
• Inter-subset adhesion critically contextualized the HI-invasion relationship, with exceptions noted for heterogeneous cell-ECM adhesion.

Conclusions:

• Spatial heterogeneity and adhesion properties of cancer cells are key regulators of collective invasion.
• The degree of cell-cell and cell-ECM adhesion heterogeneity significantly modulates tumor invasiveness.
• Computational modeling provides insights into complex multicellular behaviors like tumor invasion.