A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspective
Abstract Pancreatic neuroendocrine tumors (PanNETs) are a rare tumor entity with largely unpredictable progression and increasing incidence in developed countries. Molecular pathways involved in PanNETs development are still not elucidated, and specific biomarkers are missing. Moreover, the heteroge...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-06-01
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| Series: | npj Systems Biology and Applications |
| Online Access: | https://doi.org/10.1038/s41540-023-00283-8 |
| _version_ | 1797811402496278528 |
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| author | Silke D. Werle Nensi Ikonomi Ludwig Lausser Annika M. T. U. Kestler Felix M. Weidner Julian D. Schwab Julia Maier Malte Buchholz Thomas M. Gress Angelika M. R. Kestler Hans A. Kestler |
| author_facet | Silke D. Werle Nensi Ikonomi Ludwig Lausser Annika M. T. U. Kestler Felix M. Weidner Julian D. Schwab Julia Maier Malte Buchholz Thomas M. Gress Angelika M. R. Kestler Hans A. Kestler |
| author_sort | Silke D. Werle |
| collection | DOAJ |
| description | Abstract Pancreatic neuroendocrine tumors (PanNETs) are a rare tumor entity with largely unpredictable progression and increasing incidence in developed countries. Molecular pathways involved in PanNETs development are still not elucidated, and specific biomarkers are missing. Moreover, the heterogeneity of PanNETs makes their treatment challenging and most approved targeted therapeutic options for PanNETs lack objective responses. Here, we applied a systems biology approach integrating dynamic modeling strategies, foreign classifier tailored approaches, and patient expression profiles to predict PanNETs progression as well as resistance mechanisms to clinically approved treatments such as the mammalian target of rapamycin complex 1 (mTORC1) inhibitors. We set up a model able to represent frequently reported PanNETs drivers in patient cohorts, such as Menin-1 (MEN1), Death domain associated protein (DAXX), Tuberous Sclerosis (TSC), as well as wild-type tumors. Model-based simulations suggested drivers of cancer progression as both first and second hits after MEN1 loss. In addition, we could predict the benefit of mTORC1 inhibitors on differentially mutated cohorts and hypothesize resistance mechanisms. Our approach sheds light on a more personalized prediction and treatment of PanNET mutant phenotypes. |
| first_indexed | 2024-03-13T07:23:08Z |
| format | Article |
| id | doaj.art-4ccc6dba9fcc4072b055b2958bdc1426 |
| institution | Directory Open Access Journal |
| issn | 2056-7189 |
| language | English |
| last_indexed | 2024-03-13T07:23:08Z |
| publishDate | 2023-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Systems Biology and Applications |
| spelling | doaj.art-4ccc6dba9fcc4072b055b2958bdc14262023-06-04T11:32:01ZengNature Portfolionpj Systems Biology and Applications2056-71892023-06-019111710.1038/s41540-023-00283-8A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspectiveSilke D. Werle0Nensi Ikonomi1Ludwig Lausser2Annika M. T. U. Kestler3Felix M. Weidner4Julian D. Schwab5Julia Maier6Malte Buchholz7Thomas M. Gress8Angelika M. R. Kestler9Hans A. Kestler10Institute of Medical Systems Biology, Ulm UniversityInstitute of Medical Systems Biology, Ulm UniversityInstitute of Medical Systems Biology, Ulm UniversityInstitute of Medical Systems Biology, Ulm UniversityInstitute of Medical Systems Biology, Ulm UniversityInstitute of Medical Systems Biology, Ulm UniversityInstitute of Medical Systems Biology, Ulm UniversityDepartment of Gastroenterology, Endocrinology and Metabolism, Philipps-University MarburgDepartment of Gastroenterology, Endocrinology and Metabolism, Philipps-University MarburgDepartment of Internal Medicine I, University Hospital UlmInstitute of Medical Systems Biology, Ulm UniversityAbstract Pancreatic neuroendocrine tumors (PanNETs) are a rare tumor entity with largely unpredictable progression and increasing incidence in developed countries. Molecular pathways involved in PanNETs development are still not elucidated, and specific biomarkers are missing. Moreover, the heterogeneity of PanNETs makes their treatment challenging and most approved targeted therapeutic options for PanNETs lack objective responses. Here, we applied a systems biology approach integrating dynamic modeling strategies, foreign classifier tailored approaches, and patient expression profiles to predict PanNETs progression as well as resistance mechanisms to clinically approved treatments such as the mammalian target of rapamycin complex 1 (mTORC1) inhibitors. We set up a model able to represent frequently reported PanNETs drivers in patient cohorts, such as Menin-1 (MEN1), Death domain associated protein (DAXX), Tuberous Sclerosis (TSC), as well as wild-type tumors. Model-based simulations suggested drivers of cancer progression as both first and second hits after MEN1 loss. In addition, we could predict the benefit of mTORC1 inhibitors on differentially mutated cohorts and hypothesize resistance mechanisms. Our approach sheds light on a more personalized prediction and treatment of PanNET mutant phenotypes.https://doi.org/10.1038/s41540-023-00283-8 |
| spellingShingle | Silke D. Werle Nensi Ikonomi Ludwig Lausser Annika M. T. U. Kestler Felix M. Weidner Julian D. Schwab Julia Maier Malte Buchholz Thomas M. Gress Angelika M. R. Kestler Hans A. Kestler A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspective npj Systems Biology and Applications |
| title | A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspective |
| title_full | A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspective |
| title_fullStr | A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspective |
| title_full_unstemmed | A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspective |
| title_short | A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspective |
| title_sort | systems biology approach to define mechanisms phenotypes and drivers in pannets with a personalized perspective |
| url | https://doi.org/10.1038/s41540-023-00283-8 |
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