Faculty, Staff and Student Publications
Publication Date
10-2-2024
Journal
npj Systems Biology and Applications
Abstract
The reaction-diffusion equation is widely used in mathematical models of cancer. The calibration of model parameters based on limited clinical data is critical to using reaction-diffusion equation simulations for reliable predictions on a per-patient basis. Here, we focus on cell-level data as routinely available from tissue biopsies used for clinical cancer diagnosis. We analyze the spatial architecture in biopsy tissues stained with multiplex immunofluorescence. We derive a two-point correlation function and the corresponding spatial power spectral distribution. We show that this data-deduced power spectral distribution can fit the power spectrum of the solution of reaction-diffusion equations that can then identify patient-specific tumor growth and invasion rates. This approach allows the measurement of patient-specific critical tumor dynamical properties from routinely available biopsy material at a single snapshot in time.
Keywords
Humans, Biopsy, Neoplasm Invasiveness, Neoplasms, Calibration, Spatial Analysis, Models, Biological, Computer Simulation
DOI
10.1038/s41540-024-00439-0
PMID
39358360
PMCID
PMC11447233
PubMedCentral® Posted Date
10-2-2024
PubMedCentral® Full Text Version
Post-print
Published Open-Access
yes
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Oncology Commons