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dc.contributor.authorJain, Harsh Vardhan
dc.contributor.authorMüller, A
dc.date.accessioned2015-04-09T09:37:38Zen
dc.date.available2015-04-09T09:37:38Zen
dc.date.issued2011-02-01en
dc.identifier.citationThe molecular basis of synergism between carboplatin and ABT-737 therapy targeting ovarian carcinomas. 2011, 71 (3):705-15 Cancer Res.en
dc.identifier.issn1538-7445en
dc.identifier.pmid21169413en
dc.identifier.doi10.1158/0008-5472.CAN-10-3174en
dc.identifier.urihttp://hdl.handle.net/10033/362483en
dc.description.abstractResistance to standard chemotherapy (carboplatin + paclitaxel) is one of the leading causes of therapeutic failure in ovarian carcinomas. Emergence of chemoresistance has been shown to be mediated in part by members of the Bcl family of proteins including the antiapoptotic protein Bcl-x(L), whose expression is correlated with shorter disease-free intervals in recurrent disease. ABT-737 is an example of one of the first small-molecule inhibitors of Bcl-2/Bcl-x(L) that has been shown to increase the sensitivity of ovarian cancer cells to carboplatin. To exploit the therapeutic potential of these two drugs and predict optimal doses and dose scheduling, it is essential to understand the molecular basis of their synergistic action. Here, we build and calibrate a mathematical model of ABT-737 and carboplatin action on an ovarian cancer cell line (IGROV-1). The model suggests that carboplatin treatment primes cells for ABT-737 therapy because of an increased dependence of cells with DNA damage on Bcl-x(L) for survival. Numerical simulations predict the existence of a threshold of Bcl-x(L) below which these cells are unable to recover. Furthermore, co- plus posttreatment of ABT-737 with carboplatin is predicted to be the best strategy to maximize synergism between these two drugs. A critical challenge in chemotherapy is to strike a balance between maximizing cell-kill while minimizing patient drug load. We show that the model can be used to compute minimal doses required for any desired fraction of cell kill. These results underscore the potential of the modeling work presented here as a valuable quantitative tool to aid in the translation of novel drugs such as ABT-737 from the experimental to clinical setting and highlight the need for close collaboration between modelers and experimental scientists.
dc.language.isoenen
dc.subject.meshAnimalsen
dc.subject.meshAntineoplastic Combined Chemotherapy Protocolsen
dc.subject.meshApoptosisen
dc.subject.meshBiphenyl Compoundsen
dc.subject.meshCarboplatinen
dc.subject.meshDNA Damageen
dc.subject.meshDrug Administration Scheduleen
dc.subject.meshDrug Synergismen
dc.subject.meshFemaleen
dc.subject.meshHumansen
dc.subject.meshMiceen
dc.subject.meshModels, Biologicalen
dc.subject.meshMolecular Targeted Therapyen
dc.subject.meshNitrophenolsen
dc.subject.meshOvarian Neoplasmsen
dc.subject.meshPiperazinesen
dc.subject.meshSulfonamidesen
dc.subject.meshbcl-X Proteinen
dc.titleThe molecular basis of synergism between carboplatin and ABT-737 therapy targeting ovarian carcinomas.en
dc.typeArticleen
dc.identifier.journalCancer researchen
refterms.dateFOA2018-06-13T19:46:36Z
html.description.abstractResistance to standard chemotherapy (carboplatin + paclitaxel) is one of the leading causes of therapeutic failure in ovarian carcinomas. Emergence of chemoresistance has been shown to be mediated in part by members of the Bcl family of proteins including the antiapoptotic protein Bcl-x(L), whose expression is correlated with shorter disease-free intervals in recurrent disease. ABT-737 is an example of one of the first small-molecule inhibitors of Bcl-2/Bcl-x(L) that has been shown to increase the sensitivity of ovarian cancer cells to carboplatin. To exploit the therapeutic potential of these two drugs and predict optimal doses and dose scheduling, it is essential to understand the molecular basis of their synergistic action. Here, we build and calibrate a mathematical model of ABT-737 and carboplatin action on an ovarian cancer cell line (IGROV-1). The model suggests that carboplatin treatment primes cells for ABT-737 therapy because of an increased dependence of cells with DNA damage on Bcl-x(L) for survival. Numerical simulations predict the existence of a threshold of Bcl-x(L) below which these cells are unable to recover. Furthermore, co- plus posttreatment of ABT-737 with carboplatin is predicted to be the best strategy to maximize synergism between these two drugs. A critical challenge in chemotherapy is to strike a balance between maximizing cell-kill while minimizing patient drug load. We show that the model can be used to compute minimal doses required for any desired fraction of cell kill. These results underscore the potential of the modeling work presented here as a valuable quantitative tool to aid in the translation of novel drugs such as ABT-737 from the experimental to clinical setting and highlight the need for close collaboration between modelers and experimental scientists.


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