Determinability of model parameters in a two-stage deterministic cancer model

Area of Science:

• Oncology
• Mathematical Biology
• Carcinogenesis Research

Background:

• Chemically induced skin cancer in mice serves as a model system.
• Understanding cancer progression requires accurate parameterization of mathematical models.
• The two-stage model is a common framework for analyzing carcinogenesis.

Purpose of the Study:

• To investigate the identifiability of parameters within a deterministic two-stage cancer model.
• To determine which biological parameters can be uniquely estimated from experimental data.
• To assess the limitations of current data in fully characterizing cancer kinetics.

Main Methods:

• Utilized a deterministic two-stage cancer model.
• Analyzed time-course data of papilloma number and cancer rates.
• Assessed parameter identifiability using mathematical modeling techniques.

Main Results:

• The rate of initiated cell creation and their net-growth rate were uniquely determinable.
• These two parameters were sufficient to simulate experimental papilloma data.
• Mitotic and death rates of initiated and transformed cells were not uniquely determinable.
• The rate of transformed cell creation and their net-growth rate could not be independently determined.

Conclusions:

• The deterministic two-stage cancer model can effectively simulate papilloma formation and skin cancer data.
• However, fundamental biological parameters (e.g., mitotic and death rates) often lack unique determination from typical experimental datasets.
• This highlights limitations in inferring detailed cellular dynamics from macroscopic cancer progression data.