Dynamic BH3 profiling identifies pro-apoptotic drug combinations for the treatment of malignant pleural mesothelioma.
Dynamic BH3 profiling identifies pro-apoptotic drug combinations for the treatment of malignant pleural mesothelioma.
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DOI:
10.1038/s41467-023-38552-z
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发表时间:
2023-05-20
影响因子:
16.6
通讯作者:
Letai, Anthony
中科院分区:
文献类型:
--
作者:
Potter, Danielle S. S.;Du, Ruochen;Bohl, Stephan R. R.;Chow, Kin-Hoe;Ligon, Keith L. L.;Bueno, Raphael;Letai, Anthony
Malignant pleural mesothelioma (MPM) has relatively ineffective first/second-line therapy for advanced disease and only 18% five-year survival for early disease. Drug-induced mitochondrial priming measured by dynamic BH3 profiling identifies efficacious drugs in multiple disease settings. We use high throughput dynamic BH3 profiling (HTDBP) to identify drug combinations that prime primary MPM cells derived from patient tumors, which also prime patient derived xenograft (PDX) models. A navitoclax (BCL-xL/BCL-2/BCL-w antagonist) and AZD8055 (mTORC1/2 inhibitor) combination demonstrates efficacy in vivo in an MPM PDX model, validating HTDBP as an approach to identify efficacious drug combinations. Mechanistic investigation reveals AZD8055 treatment decreases MCL-1 protein levels, increases BIM protein levels, and increases MPM mitochondrial dependence on BCL-xL, which is exploited by navitoclax. Navitoclax treatment increases dependency on MCL-1 and increases BIM protein levels. These findings demonstrate that HTDBP can be used as a functional precision medicine tool to rationally construct combination drug regimens in MPM and other cancers. Malignant pleural mesothelioma (MPM) is an aggressive malignancy with few effective treatment options available. Here, the authors use dynamic BH3 profiling to measure drug-induced mitochondrial priming and identify AZD8055 and navitoclax as a pro-apoptotic drug combination in ex vivo and preclinical MPM models.
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影响因子:
64.5
作者:
Brunet, A;Bonni, A;Greenberg, ME
通讯作者:
Greenberg, ME
影响因子:
3.7
作者:
Guzmán C;Bagga M;Kaur A;Westermarck J;Abankwa D
通讯作者:
Abankwa D
影响因子:
7
作者:
Arulananda S;O'Brien M;Evangelista M;Jenkins LJ;Poh AR;Walkiewicz M;Leong T;Mariadason JM;Cebon J;Balachander SB;Cidado JR;Lee EF;John T;Fairlie WD
通讯作者:
Fairlie WD
DOI:
10.1073/pnas.1411848112
发表时间:
2015-03-17
影响因子:
11.1
作者:
Faber, Anthony C.;Farago, Anna F.;Engelman, Jeffrey A.
通讯作者:
Engelman, Jeffrey A.
影响因子:
11.2
作者:
Daniel VC;Marchionni L;Hierman JS;Rhodes JT;Devereux WL;Rudin CM;Yung R;Parmigiani G;Dorsch M;Peacock CD;Watkins DN
通讯作者:
Watkins DN