Tumor heterogeneity and progression: conceptual foundations for modeling

Area of Science:

• Oncology
• Computational Biology
• Mathematical Modeling

Background:

• Tumor progression, growth, and heterogeneity are complex phenomena.
• Understanding these dynamics is crucial for effective cancer treatment.
• Existing models may not fully capture the interplay of key driving factors.

Purpose of the Study:

• To present a conceptual foundation for modeling tumor progression, growth, and heterogeneity.
• To provide a framework for building both conceptual and mathematical cancer models.
• To aid in understanding, testing hypotheses, and guiding experiments in cancer research.

Main Methods:

• Developing a schema integrating three phenomenological driving elements: growth, progression, and genetic instability.
• Defining growth as changes in tumor bulk, distinct from progression.
• Defining progression as processes underlying phenotypic changes.
• Defining genetic elements as heritable changes affecting tumor behavior.

Main Results:

• The proposed framework allows for consistent qualitative reasoning about tumor behavior.
• Models can be built by combining the interactions of growth, progression, and genetic instability.
• These models can explore hypotheses regarding dynamic changes in cellular populations.
• Intratumor heterogeneity generation can be investigated using these models.

Conclusions:

• The conceptual foundation provides a versatile tool for studying dynamic aspects of complex tumor behavior.
• Models derived from this framework can guide experimentation and deepen insights into cancer progression.
• This approach facilitates 'in machina' modeling of cancer to address dynamic features.