The temporal response of a glioma cell population to irradiation: modeling the effect of dose and cell density
Data files
Feb 26, 2025 version files 75.98 KB
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averaged_curves_article.zip
74.74 KB
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README.md
1.24 KB
Abstract
Time-lapse fluorescence microscopy experiments were performed to track the cell density of F98 glioma cells under varying radiation doses and initial cell densities. Based on these results, a compartmental model characterizing the temporal response of a cancerous cell population to single-dose radiation therapy was developed. This model reproduces very well all the experimental data, with only three free parameters (and four others that are fixed). It allows to have access and follow the evolution of different cell populations after irradiation, in particular the senescent and repaired cell populations. From these different cell populations, surviving fractions could also be estimated. Most importantly, our model allows to analyze and quantify an inhibition effect (or cohort effect) of the dead and senescent cell populations on the regrowth of the repaired one.
https://doi.org/10.5061/dryad.qv9s4mwp5
Description of the data and file structure
These data are the normalized cell density and the standard deviation at each time point (every 90 minutes), with an increasing initial cell density from well 1 to well 6 (as described in the manuscript).
The dose is indicated at the begin of the name of the file: 0GY, 5 Gy, 10 Gy and 15 Gy.
Files and variables
File: averaged_curves_article.zip
Description: list of files corresponding to different doses of irradiatipn (0,5,10 and 15 Gy) and different initial cell density (increasing from well 1 to well 6).
Code/software
The files are text file that can be open with any text editor.
Two codes are included, one (Modele_Control.py) for the fitting of the data with our model in the control case (0Gy) and the second one (Model_in_Response_to_Radiation.py) for the model of the irradiation case. Theses codes are Python codes.
Access information
Other publicly accessible locations of the data:
Data was derived from the following sources:
- Billoir, Marianne; Crepin, Delphine; Plaszczynski, Stéphane et al. (2025). The temporal response of a glioma cell population to irradiation: modelling the effect of dose and cell density. Royal Society Open Science. https://doi.org/10.1098/rsos.241917