Mathematical modeling and quantitative analysis of phenotypic plasticity during tumor evolution based on single-cell...

Area of Science:

• Mathematical Biology
• Cancer Research
• Computational Biology

Background:

• Tumor progression is driven by complex cellular mechanisms, including plasticity and heterogeneity.
• Understanding these dynamics is key to developing effective cancer treatments.

Purpose of the Study:

• To develop a novel mathematical framework to investigate the role of cellular plasticity and heterogeneity in tumor progression.
• To quantify cell phenotype transitions and their impact on tumor malignancy.

Main Methods:

• Developed a reaction-convection-diffusion model using temporal single-cell data.
• Applied theoretical analysis, including bifurcation analysis and AddModuleScore, to study tumor cell and macrophage dynamics.
• Introduced pulse wave speed and high-plasticity/low-plasticity cell ratio as quantitative measures.

Main Results:

• Established pulse wave speed as a measure of cell phenotype transition rate.
• Identified a high-plasticity/low-plasticity cell ratio as an indicator of tumor malignancy.
• Demonstrated that increased phenotype transition rates correlate with heightened malignancy and tumor progression to adenocarcinoma.

Conclusions:

• Cellular plasticity significantly influences tumor progression and malignancy.
• The developed mathematical framework and quantitative measures provide insights into tumor dynamics.
• Findings can guide the development of targeted therapies to control tumor progression by regulating cellular plasticity.