000885554 001__ 885554
000885554 005__ 20240625095122.0
000885554 0247_ $$2doi$$a10.1101/2020.05.06.080150
000885554 0247_ $$2Handle$$a2128/25859
000885554 0247_ $$2altmetric$$aaltmetric:81635887
000885554 037__ $$aFZJ-2020-03925
000885554 1001_ $$0P:(DE-HGF)0$$aToledo, Marcelo A. S.$$b0
000885554 245__ $$aNintedanib Targets KIT D816V Neoplastic Cells Derived from Induced Pluripotent Stem cells of Systemic Mastocytosis
000885554 260__ $$c2020
000885554 3367_ $$0PUB:(DE-HGF)25$$2PUB:(DE-HGF)$$aPreprint$$bpreprint$$mpreprint$$s1602242905_12680
000885554 3367_ $$2ORCID$$aWORKING_PAPER
000885554 3367_ $$028$$2EndNote$$aElectronic Article
000885554 3367_ $$2DRIVER$$apreprint
000885554 3367_ $$2BibTeX$$aARTICLE
000885554 3367_ $$2DataCite$$aOutput Types/Working Paper
000885554 520__ $$aThe KIT D816V mutation is found in more than 80% of patients with systemic mastocytosis (SM) and is key to neoplastic mast cell (MC) expansion and accumulation in affected organs. KIT D816V therefore represents a prime therapeutic target for SM. Here we generated a panel of patient-specific KIT D816V induced pluripotent stem cells (iPSCs) from patients with aggressive SM (ASM) and mast cell leukemia (MCL) to develop a patient-specific SM disease model for mechanistic and drug discovery studies. KIT D816V iPSCs differentiated into neoplastic hematopoietic progenitor cells and MCs with patient-specific phenotypic features, thereby reflecting the heterogeneity of the disease. CRISPR/Cas9n-engineered KIT D816V human embryonic stem cells (ESCs), when differentiated into hematopoietic cells, recapitulated the phenotype observed for KIT D816V iPSC hematopoiesis. KIT D816V causes constitutive activation of the KIT tyrosine kinase receptor and we exploited our iPSCs and ESCs to investigate new tyrosine kinase inhibitors targeting KIT D816V. Our study identified nintedanib as a novel KIT D816V inhibitor. Nintedanib selectively reduced the viability of iPSC-derived KIT D816V hematopoietic progenitor cells and MCs in the nanomolar range. Nintedanib was also active on primary samples of KIT D816V SM patients. Molecular docking studies show that nintedanib binds to the ATP binding pocket of inactive KIT D816V. Our results suggest nintedanib as a new drug candidate for KIT D816V targeted therapy of advanced SM.
000885554 536__ $$0G:(DE-HGF)POF3-573$$a573 - Neuroimaging (POF3-573)$$cPOF3-573$$fPOF III$$x0
000885554 536__ $$0G:(DE-HGF)POF3-511$$a511 - Computational Science and Mathematical Methods (POF3-511)$$cPOF3-511$$fPOF III$$x1
000885554 588__ $$aDataset connected to CrossRef
000885554 7001_ $$0P:(DE-HGF)0$$aGatz, Malrun$$b1
000885554 7001_ $$0P:(DE-HGF)0$$aSontag, Stephanie$$b2
000885554 7001_ $$0P:(DE-HGF)0$$aGleixner, Karoline V.$$b3
000885554 7001_ $$0P:(DE-HGF)0$$aEisenwort, Gregor$$b4
000885554 7001_ $$0P:(DE-HGF)0$$aFeldberg, Kristina$$b5
000885554 7001_ $$0P:(DE-HGF)0$$aKluge, Frederick$$b6
000885554 7001_ $$0P:(DE-Juel1)172064$$aGuareschi, Riccardo$$b7
000885554 7001_ $$0P:(DE-Juel1)145921$$aRossetti, Giulia$$b8$$ufzj
000885554 7001_ $$0P:(DE-HGF)0$$aSechi, Antonio S.$$b9
000885554 7001_ $$0P:(DE-HGF)0$$aDufva, Olli M. J.$$b10
000885554 7001_ $$0P:(DE-HGF)0$$aMustjoki, Satu M.$$b11
000885554 7001_ $$0P:(DE-HGF)0$$aMaurer, Angela$$b12
000885554 7001_ $$0P:(DE-HGF)0$$aSchüler, Herdit M.$$b13
000885554 7001_ $$0P:(DE-HGF)0$$aGoetzke, Roman$$b14
000885554 7001_ $$0P:(DE-HGF)0$$aBraunschweig, Till$$b15
000885554 7001_ $$0P:(DE-HGF)0$$aSimonowski, Anne$$b16
000885554 7001_ $$0P:(DE-HGF)0$$aPanse, Jens$$b17
000885554 7001_ $$0P:(DE-HGF)0$$aJawhar, Mohamad$$b18
000885554 7001_ $$0P:(DE-HGF)0$$aReiter, Andreas$$b19
000885554 7001_ $$0P:(DE-HGF)0$$aHilberg, Frank$$b20
000885554 7001_ $$0P:(DE-HGF)0$$aEttmayer, Peter$$b21
000885554 7001_ $$00000-0002-1971-3217$$aWagner, Wolfgang$$b22
000885554 7001_ $$0P:(DE-HGF)0$$aKoschmieder, Steffen$$b23
000885554 7001_ $$0P:(DE-HGF)0$$aBrümmendorf, Tim H.$$b24
000885554 7001_ $$0P:(DE-HGF)0$$aValent, Peter$$b25
000885554 7001_ $$0P:(DE-HGF)0$$aChatain, Nicolas$$b26
000885554 7001_ $$00000-0002-1107-3251$$aZenke, Martin$$b27$$eCorresponding author
000885554 773__ $$a10.1101/2020.05.06.080150
000885554 8564_ $$uhttps://www.biorxiv.org/content/10.1101/2020.05.06.080150v1.full.pdf
000885554 8564_ $$uhttps://juser.fz-juelich.de/record/885554/files/2020.05.06.080150v1.full.pdf$$yOpenAccess
000885554 8564_ $$uhttps://juser.fz-juelich.de/record/885554/files/2020.05.06.080150v1.full.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000885554 909CO $$ooai:juser.fz-juelich.de:885554$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000885554 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)172064$$aForschungszentrum Jülich$$b7$$kFZJ
000885554 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)145921$$aForschungszentrum Jülich$$b8$$kFZJ
000885554 9131_ $$0G:(DE-HGF)POF3-573$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vNeuroimaging$$x0
000885554 9131_ $$0G:(DE-HGF)POF3-511$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data$$vComputational Science and Mathematical Methods$$x1
000885554 9141_ $$y2020
000885554 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000885554 915__ $$0LIC:(DE-HGF)CCBYNCND4$$2HGFVOC$$aCreative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0
000885554 9201_ $$0I:(DE-Juel1)IAS-5-20120330$$kIAS-5$$lComputational Biomedicine$$x0
000885554 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x1
000885554 9201_ $$0I:(DE-Juel1)INM-9-20140121$$kINM-9$$lComputational Biomedicine$$x2
000885554 980__ $$apreprint
000885554 980__ $$aVDB
000885554 980__ $$aUNRESTRICTED
000885554 980__ $$aI:(DE-Juel1)IAS-5-20120330
000885554 980__ $$aI:(DE-Juel1)JSC-20090406
000885554 980__ $$aI:(DE-Juel1)INM-9-20140121
000885554 9801_ $$aFullTexts