Modelling longitudinal preclinical tumour size data to identify transient dynamics in tumour response to anti-angiogenic drugs
Experimental evidence suggests that antiangiogenic therapy gives rise to a transient window of vessel normalization, within which the efficacy of radiotherapy and chemotherapy may be enhanced. Preclinical experiments that measure components of vessel normalization are invasive and expensive. We have...
| Main Authors: | , , , , , , , , |
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| Formato: | Journal article |
| Publicado: |
Wiley
2016
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| _version_ | 1826287093812297728 |
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| author | Hutchinson, L Mueller, H Gaffney, E Maini, P Wagg, J Phipps, A Boetsch, C Byrne, H Ribba, B |
| author_facet | Hutchinson, L Mueller, H Gaffney, E Maini, P Wagg, J Phipps, A Boetsch, C Byrne, H Ribba, B |
| author_sort | Hutchinson, L |
| collection | OXFORD |
| description | Experimental evidence suggests that antiangiogenic therapy gives rise to a transient window of vessel normalization, within which the efficacy of radiotherapy and chemotherapy may be enhanced. Preclinical experiments that measure components of vessel normalization are invasive and expensive. We have developed a mathematical model of vascular tumor growth from preclinical time‐course data in a breast cancer xenograft model. We used a mixed‐effects approach for model parameterization, leveraging tumor size data to identify a period of enhanced tumor growth that could potentially correspond to the transient window of vessel normalization. We estimated the characteristics of the window for mice treated with an anti‐VEGF antibody (bevacizumab) or with a bispecific anti‐VEGF/anti‐angiopoietin‐2 antibody (vanucizumab). We show how the mathematical model could theoretically be used to predict how to coordinate antiangiogenic therapy with radiotherapy or chemotherapy to maximize therapeutic effect, reducing the need for preclinical experiments that directly measure vessel normalization parameters. |
| first_indexed | 2024-03-07T01:53:28Z |
| format | Journal article |
| id | oxford-uuid:9aebeac0-f118-45a1-94f6-3fc626e316dd |
| institution | University of Oxford |
| last_indexed | 2024-03-07T01:53:28Z |
| publishDate | 2016 |
| publisher | Wiley |
| record_format | dspace |
| spelling | oxford-uuid:9aebeac0-f118-45a1-94f6-3fc626e316dd2022-03-27T00:24:48ZModelling longitudinal preclinical tumour size data to identify transient dynamics in tumour response to anti-angiogenic drugsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:9aebeac0-f118-45a1-94f6-3fc626e316ddSymplectic Elements at OxfordWiley2016Hutchinson, LMueller, HGaffney, EMaini, PWagg, JPhipps, ABoetsch, CByrne, HRibba, BExperimental evidence suggests that antiangiogenic therapy gives rise to a transient window of vessel normalization, within which the efficacy of radiotherapy and chemotherapy may be enhanced. Preclinical experiments that measure components of vessel normalization are invasive and expensive. We have developed a mathematical model of vascular tumor growth from preclinical time‐course data in a breast cancer xenograft model. We used a mixed‐effects approach for model parameterization, leveraging tumor size data to identify a period of enhanced tumor growth that could potentially correspond to the transient window of vessel normalization. We estimated the characteristics of the window for mice treated with an anti‐VEGF antibody (bevacizumab) or with a bispecific anti‐VEGF/anti‐angiopoietin‐2 antibody (vanucizumab). We show how the mathematical model could theoretically be used to predict how to coordinate antiangiogenic therapy with radiotherapy or chemotherapy to maximize therapeutic effect, reducing the need for preclinical experiments that directly measure vessel normalization parameters. |
| spellingShingle | Hutchinson, L Mueller, H Gaffney, E Maini, P Wagg, J Phipps, A Boetsch, C Byrne, H Ribba, B Modelling longitudinal preclinical tumour size data to identify transient dynamics in tumour response to anti-angiogenic drugs |
| title | Modelling longitudinal preclinical tumour size data to identify transient dynamics in tumour response to anti-angiogenic drugs |
| title_full | Modelling longitudinal preclinical tumour size data to identify transient dynamics in tumour response to anti-angiogenic drugs |
| title_fullStr | Modelling longitudinal preclinical tumour size data to identify transient dynamics in tumour response to anti-angiogenic drugs |
| title_full_unstemmed | Modelling longitudinal preclinical tumour size data to identify transient dynamics in tumour response to anti-angiogenic drugs |
| title_short | Modelling longitudinal preclinical tumour size data to identify transient dynamics in tumour response to anti-angiogenic drugs |
| title_sort | modelling longitudinal preclinical tumour size data to identify transient dynamics in tumour response to anti angiogenic drugs |
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