Modeling Tumor Clonal Evolution for Drug Combinations Design
Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure toward drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed...
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| Format: | Article |
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Elsevier BV
2018
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| Online Access: | http://hdl.handle.net/1721.1/116546 https://orcid.org/0000-0003-4610-1707 https://orcid.org/0000-0002-0050-989X |
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| author | Zhao, Boyang Hemann, Michael Lauffenburger, Douglas A |
| author2 | Massachusetts Institute of Technology. Computational and Systems Biology Program |
| author_facet | Massachusetts Institute of Technology. Computational and Systems Biology Program Zhao, Boyang Hemann, Michael Lauffenburger, Douglas A |
| author_sort | Zhao, Boyang |
| collection | MIT |
| description | Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure toward drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling and combinations design. In this review we discuss the promising opportunities that these interdisciplinary approaches hold for advances in cancer biology and treatment. We propose that quantitative modeling perspectives can complement emerging experimental technologies to facilitate enhanced understanding of disease progression and improved capabilities for therapeutic drug regimen designs. |
| first_indexed | 2024-09-23T12:40:05Z |
| format | Article |
| id | mit-1721.1/116546 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T12:40:05Z |
| publishDate | 2018 |
| publisher | Elsevier BV |
| record_format | dspace |
| spelling | mit-1721.1/1165462022-09-28T09:20:25Z Modeling Tumor Clonal Evolution for Drug Combinations Design Zhao, Boyang Hemann, Michael Lauffenburger, Douglas A Massachusetts Institute of Technology. Computational and Systems Biology Program Massachusetts Institute of Technology. Department of Biological Engineering Massachusetts Institute of Technology. Department of Biology Massachusetts Institute of Technology. Department of Chemical Engineering Zhao, Boyang Hemann, Michael Lauffenburger, Douglas A intratumoral heterogeneity tumor clonal evolution mathematical/computational modeling drug combinations drug resistance Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure toward drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling and combinations design. In this review we discuss the promising opportunities that these interdisciplinary approaches hold for advances in cancer biology and treatment. We propose that quantitative modeling perspectives can complement emerging experimental technologies to facilitate enhanced understanding of disease progression and improved capabilities for therapeutic drug regimen designs. David H. Koch Cancer Research Fund (Grant P30-CA14051) National Cancer Institute (U.S.). Integrative Cancer Biology Program (Grant U54-CA112967) National Institute of General Medical Sciences (U.S.). Interdepartmental Biotechnology Training Program (5T32GM008334) 2018-06-25T13:02:27Z 2018-06-25T13:02:27Z 2016-03 2018-06-21T17:28:32Z Article http://purl.org/eprint/type/JournalArticle 24058033 http://hdl.handle.net/1721.1/116546 Zhao, Boyang, Michael T. Hemann, and Douglas A. Lauffenburger. “Modeling Tumor Clonal Evolution for Drug Combinations Design.” Trends in Cancer 2, no. 3 (March 2016): 144–158. https://orcid.org/0000-0003-4610-1707 https://orcid.org/0000-0002-0050-989X http://dx.doi.org/10.1016/J.TRECAN.2016.02.001 Trends in Cancer Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier BV PMC |
| spellingShingle | intratumoral heterogeneity tumor clonal evolution mathematical/computational modeling drug combinations drug resistance Zhao, Boyang Hemann, Michael Lauffenburger, Douglas A Modeling Tumor Clonal Evolution for Drug Combinations Design |
| title | Modeling Tumor Clonal Evolution for Drug Combinations Design |
| title_full | Modeling Tumor Clonal Evolution for Drug Combinations Design |
| title_fullStr | Modeling Tumor Clonal Evolution for Drug Combinations Design |
| title_full_unstemmed | Modeling Tumor Clonal Evolution for Drug Combinations Design |
| title_short | Modeling Tumor Clonal Evolution for Drug Combinations Design |
| title_sort | modeling tumor clonal evolution for drug combinations design |
| topic | intratumoral heterogeneity tumor clonal evolution mathematical/computational modeling drug combinations drug resistance |
| url | http://hdl.handle.net/1721.1/116546 https://orcid.org/0000-0003-4610-1707 https://orcid.org/0000-0002-0050-989X |
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