Gene expression and agent-based modeling improve precision prognosis in breast cancer
Abstract Breast cancer survival is hard to predict because of the complex ways genes and cells interact. This study offers a new method to improve these predictions by combining gene expression profiling (GEP) with agent-based modeling (ABM). First, GEP will pinpoint genes that are important in brea...
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Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-01275-w |
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| author | Padmasri Sridharan Mini Ghosh |
| author_facet | Padmasri Sridharan Mini Ghosh |
| author_sort | Padmasri Sridharan |
| collection | DOAJ |
| description | Abstract Breast cancer survival is hard to predict because of the complex ways genes and cells interact. This study offers a new method to improve these predictions by combining gene expression profiling (GEP) with agent-based modeling (ABM). First, GEP will pinpoint genes that are important in breast cancer development. Then, a mathematical model will be built to show how these genes influence cell behavior. This data will be used in ABM to simulate tumor growth and treatment response. The ABM allows us to virtually test different treatments and see how they might affect patient survival. Finally, the model’s accuracy will be checked against real patient data and compared to other models. By combining the strengths of GEP and ABM, this research could significantly improve breast cancer survival prediction. ABM’s ability to analyze interactions mathematically could pave the way for more personalized and effective treatments. |
| format | Article |
| id | doaj-art-8d60a1a584544d29a96ccdc2b962bd37 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-8d60a1a584544d29a96ccdc2b962bd372025-08-20T01:51:39ZengNature PortfolioScientific Reports2045-23222025-05-0115112610.1038/s41598-025-01275-wGene expression and agent-based modeling improve precision prognosis in breast cancerPadmasri Sridharan0Mini Ghosh1Department of Mathematics, School of Advanced Sciences, Vellore Institute of TechnologyDepartment of Mathematics, School of Advanced Sciences, Vellore Institute of TechnologyAbstract Breast cancer survival is hard to predict because of the complex ways genes and cells interact. This study offers a new method to improve these predictions by combining gene expression profiling (GEP) with agent-based modeling (ABM). First, GEP will pinpoint genes that are important in breast cancer development. Then, a mathematical model will be built to show how these genes influence cell behavior. This data will be used in ABM to simulate tumor growth and treatment response. The ABM allows us to virtually test different treatments and see how they might affect patient survival. Finally, the model’s accuracy will be checked against real patient data and compared to other models. By combining the strengths of GEP and ABM, this research could significantly improve breast cancer survival prediction. ABM’s ability to analyze interactions mathematically could pave the way for more personalized and effective treatments.https://doi.org/10.1038/s41598-025-01275-wBreast cancerGene expression profilingAgent-based modelSurvival predictionsMathematical modelingMachine learning |
| spellingShingle | Padmasri Sridharan Mini Ghosh Gene expression and agent-based modeling improve precision prognosis in breast cancer Scientific Reports Breast cancer Gene expression profiling Agent-based model Survival predictions Mathematical modeling Machine learning |
| title | Gene expression and agent-based modeling improve precision prognosis in breast cancer |
| title_full | Gene expression and agent-based modeling improve precision prognosis in breast cancer |
| title_fullStr | Gene expression and agent-based modeling improve precision prognosis in breast cancer |
| title_full_unstemmed | Gene expression and agent-based modeling improve precision prognosis in breast cancer |
| title_short | Gene expression and agent-based modeling improve precision prognosis in breast cancer |
| title_sort | gene expression and agent based modeling improve precision prognosis in breast cancer |
| topic | Breast cancer Gene expression profiling Agent-based model Survival predictions Mathematical modeling Machine learning |
| url | https://doi.org/10.1038/s41598-025-01275-w |
| work_keys_str_mv | AT padmasrisridharan geneexpressionandagentbasedmodelingimproveprecisionprognosisinbreastcancer AT minighosh geneexpressionandagentbasedmodelingimproveprecisionprognosisinbreastcancer |