Validation of polymorphic Gompertzian model of cancer through in vitro and in vivo data.
Mathematical modeling plays an important role in our understanding and targeting therapy resistance mechanisms in cancer. The polymorphic Gompertzian model, analyzed theoretically and numerically by Viossat and Noble to demonstrate the benefits of adaptive therapy in metastatic cancer, describes a h...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0310844 |
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| _version_ | 1841533182628855808 |
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| author | Arina Soboleva Artem Kaznatcheev Rachel Cavill Katharina Schneider Kateřina Staňková |
| author_facet | Arina Soboleva Artem Kaznatcheev Rachel Cavill Katharina Schneider Kateřina Staňková |
| author_sort | Arina Soboleva |
| collection | DOAJ |
| description | Mathematical modeling plays an important role in our understanding and targeting therapy resistance mechanisms in cancer. The polymorphic Gompertzian model, analyzed theoretically and numerically by Viossat and Noble to demonstrate the benefits of adaptive therapy in metastatic cancer, describes a heterogeneous cancer population consisting of therapy-sensitive and therapy-resistant cells. In this study, we demonstrate that the polymorphic Gompertzian model successfully captures trends in both in vitro and in vivo data on non-small cell lung cancer (NSCLC) dynamics under treatment. Additionally, for the in vivo data of tumor dynamics in patients undergoing treatment, we compare the goodness of fit of the polymorphic Gompertzian model to that of the classical oncologic models, which were previously identified as the models that fit this data best. We show that the polymorphic Gompertzian model can successfully capture the U-shape trend in tumor size during cancer relapse, which can not be fitted with the classical oncologic models. In general, the polymorphic Gompertzian model corresponds well to both in vitro and in vivo real-world data, suggesting it as a candidate for improving the efficacy of cancer therapy, for example, through evolutionary/adaptive therapies. |
| format | Article |
| id | doaj-art-9e3f94f0b7394bd6a328c9ba8e29b832 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-9e3f94f0b7394bd6a328c9ba8e29b8322025-01-17T05:31:28ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01201e031084410.1371/journal.pone.0310844Validation of polymorphic Gompertzian model of cancer through in vitro and in vivo data.Arina SobolevaArtem KaznatcheevRachel CavillKatharina SchneiderKateřina StaňkováMathematical modeling plays an important role in our understanding and targeting therapy resistance mechanisms in cancer. The polymorphic Gompertzian model, analyzed theoretically and numerically by Viossat and Noble to demonstrate the benefits of adaptive therapy in metastatic cancer, describes a heterogeneous cancer population consisting of therapy-sensitive and therapy-resistant cells. In this study, we demonstrate that the polymorphic Gompertzian model successfully captures trends in both in vitro and in vivo data on non-small cell lung cancer (NSCLC) dynamics under treatment. Additionally, for the in vivo data of tumor dynamics in patients undergoing treatment, we compare the goodness of fit of the polymorphic Gompertzian model to that of the classical oncologic models, which were previously identified as the models that fit this data best. We show that the polymorphic Gompertzian model can successfully capture the U-shape trend in tumor size during cancer relapse, which can not be fitted with the classical oncologic models. In general, the polymorphic Gompertzian model corresponds well to both in vitro and in vivo real-world data, suggesting it as a candidate for improving the efficacy of cancer therapy, for example, through evolutionary/adaptive therapies.https://doi.org/10.1371/journal.pone.0310844 |
| spellingShingle | Arina Soboleva Artem Kaznatcheev Rachel Cavill Katharina Schneider Kateřina Staňková Validation of polymorphic Gompertzian model of cancer through in vitro and in vivo data. PLoS ONE |
| title | Validation of polymorphic Gompertzian model of cancer through in vitro and in vivo data. |
| title_full | Validation of polymorphic Gompertzian model of cancer through in vitro and in vivo data. |
| title_fullStr | Validation of polymorphic Gompertzian model of cancer through in vitro and in vivo data. |
| title_full_unstemmed | Validation of polymorphic Gompertzian model of cancer through in vitro and in vivo data. |
| title_short | Validation of polymorphic Gompertzian model of cancer through in vitro and in vivo data. |
| title_sort | validation of polymorphic gompertzian model of cancer through in vitro and in vivo data |
| url | https://doi.org/10.1371/journal.pone.0310844 |
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