Estimating treatment sensitivity in synthetic and in vitro tumors using a random differential equation model
Abstract Resistance to treatment, which comes from the heterogeneity of cell types within tumors, is a leading cause of poor treatment outcomes in cancer patients. Previous mathematical work modeling cancer over time has neither emphasized the relationship between cell heterogeneity and treatment re...
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| Format: | Article |
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Nature Portfolio
2025-05-01
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| Series: | npj Systems Biology and Applications |
| Online Access: | https://doi.org/10.1038/s41540-025-00530-0 |
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| author | Natalie Meacham Erica M. Rutter |
| author_facet | Natalie Meacham Erica M. Rutter |
| author_sort | Natalie Meacham |
| collection | DOAJ |
| description | Abstract Resistance to treatment, which comes from the heterogeneity of cell types within tumors, is a leading cause of poor treatment outcomes in cancer patients. Previous mathematical work modeling cancer over time has neither emphasized the relationship between cell heterogeneity and treatment resistance nor depicted heterogeneity with sufficient nuance. To respond to the need to depict a wide range of resistance levels, we develop a random differential equation model of tumor growth. Random differential equations are differential equations in which the parameters are random variables. In the inverse problem, we aim to recover the sensitivity to treatment as a probability mass function. This allows us to observe what proportions of cells exist at different sensitivity levels. After validating the method with synthetic data, we apply it to monoclonal and mixture cell population data of isogenic Ba/F3 murine cell lines to uncover each tumor’s levels of sensitivity to treatment as a probability mass function. |
| format | Article |
| id | doaj-art-9b539448287e4fe09bc3e30d6a75591a |
| institution | OA Journals |
| issn | 2056-7189 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Systems Biology and Applications |
| spelling | doaj-art-9b539448287e4fe09bc3e30d6a75591a2025-08-20T01:53:14ZengNature Portfolionpj Systems Biology and Applications2056-71892025-05-0111111510.1038/s41540-025-00530-0Estimating treatment sensitivity in synthetic and in vitro tumors using a random differential equation modelNatalie Meacham0Erica M. Rutter1Department of Applied Mathematics, University of California, MercedDepartment of Applied Mathematics, University of California, MercedAbstract Resistance to treatment, which comes from the heterogeneity of cell types within tumors, is a leading cause of poor treatment outcomes in cancer patients. Previous mathematical work modeling cancer over time has neither emphasized the relationship between cell heterogeneity and treatment resistance nor depicted heterogeneity with sufficient nuance. To respond to the need to depict a wide range of resistance levels, we develop a random differential equation model of tumor growth. Random differential equations are differential equations in which the parameters are random variables. In the inverse problem, we aim to recover the sensitivity to treatment as a probability mass function. This allows us to observe what proportions of cells exist at different sensitivity levels. After validating the method with synthetic data, we apply it to monoclonal and mixture cell population data of isogenic Ba/F3 murine cell lines to uncover each tumor’s levels of sensitivity to treatment as a probability mass function.https://doi.org/10.1038/s41540-025-00530-0 |
| spellingShingle | Natalie Meacham Erica M. Rutter Estimating treatment sensitivity in synthetic and in vitro tumors using a random differential equation model npj Systems Biology and Applications |
| title | Estimating treatment sensitivity in synthetic and in vitro tumors using a random differential equation model |
| title_full | Estimating treatment sensitivity in synthetic and in vitro tumors using a random differential equation model |
| title_fullStr | Estimating treatment sensitivity in synthetic and in vitro tumors using a random differential equation model |
| title_full_unstemmed | Estimating treatment sensitivity in synthetic and in vitro tumors using a random differential equation model |
| title_short | Estimating treatment sensitivity in synthetic and in vitro tumors using a random differential equation model |
| title_sort | estimating treatment sensitivity in synthetic and in vitro tumors using a random differential equation model |
| url | https://doi.org/10.1038/s41540-025-00530-0 |
| work_keys_str_mv | AT nataliemeacham estimatingtreatmentsensitivityinsyntheticandinvitrotumorsusingarandomdifferentialequationmodel AT ericamrutter estimatingtreatmentsensitivityinsyntheticandinvitrotumorsusingarandomdifferentialequationmodel |