Submission Type
Poster
Start Date
4-26-2023
Abstract
Cervical cancer is a complex disease characterized by unpredictable genetic alterations of cells. Computational modeling may be applied to simulate the growth and behavior of cervical cancer within a tissue and the progression of the disease throughout the body. In our computational model, individual cells have the ability to transform behavior between the following states: healthy, precursor lesion (CN1, CN2, CN3), and cancer. Each cell state has a different mutation rate, reproductive rate, and cell life span. Our model simulates the transformation of cells into these different states. The data from our computational model shows the day-to-day growth of cancer within a tissue, and the progression of a cell evolving from healthy to cancerous. Our model suggests how cancer cells become dominant over time within a system and outgrow healthy tissue. Alterations to this model may help determine effectiveness of treatments on individual cells.
Recommended Citation
Mascitti, Mike, "187 - Modeling the Dynamics of Chromosomal Alteration Progression in Cervical Cancer: A Computational Model" (2023). GREAT Day Posters. 30.
https://knightscholar.geneseo.edu/great-day-symposium/great-day-2023/posters-2023/30
Included in
187 - Modeling the Dynamics of Chromosomal Alteration Progression in Cervical Cancer: A Computational Model
Cervical cancer is a complex disease characterized by unpredictable genetic alterations of cells. Computational modeling may be applied to simulate the growth and behavior of cervical cancer within a tissue and the progression of the disease throughout the body. In our computational model, individual cells have the ability to transform behavior between the following states: healthy, precursor lesion (CN1, CN2, CN3), and cancer. Each cell state has a different mutation rate, reproductive rate, and cell life span. Our model simulates the transformation of cells into these different states. The data from our computational model shows the day-to-day growth of cancer within a tissue, and the progression of a cell evolving from healthy to cancerous. Our model suggests how cancer cells become dominant over time within a system and outgrow healthy tissue. Alterations to this model may help determine effectiveness of treatments on individual cells.
Comments
Sponsored by Christopher Leary