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000293795 1001_ $$0P:(DE-He78)98da1f9d3c5ced2d8867edfe9f681ddc$$aAlhalabi, Obada$$b0$$eFirst author
000293795 245__ $$aIntegration of Transcriptomics, Proteomics and Loss-of-function Screening Reveals WEE1 as a Target for Combination with Dasatinib against Proneural Glioblastoma.
000293795 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2024
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000293795 520__ $$aGlioblastoma is characterized by a pronounced resistance to therapy with dismal prognosis. Transcriptomics classify glioblastoma into proneural (PN), mesenchymal (MES) and classical (CL) subtypes that show differential resistance to targeted therapies. The aim of this study was to provide a viable approach for identifying combination therapies in glioblastoma subtypes. Proteomics and phosphoproteomics were performed on dasatinib inhibited glioblastoma stem cells (GSCs) and complemented by an shRNA loss-of-function screen to identify genes whose knockdown sensitizes GSCs to dasatinib. Proteomics and screen data were computationally integrated with transcriptomic data using the SamNet 2.0 algorithm for network flow learning to reveal potential combination therapies in PN GSCs. In vitro viability assays and tumor spheroid models were used to verify the synergy of identified therapy. Further in vitro and TCGA RNA-Seq data analyses were utilized to provide a mechanistic explanation of these effects. Integration of data revealed the cell cycle protein WEE1 as a potential combination therapy target for PN GSCs. Validation experiments showed a robust synergistic effect through combination of dasatinib and the WEE1 inhibitor, MK-1775, in PN GSCs. Combined inhibition using dasatinib and MK-1775 propagated DNA damage in PN GCSs, with GCSs showing a differential subtype-driven pattern of expression of cell cycle genes in TCGA RNA-Seq data. The integration of proteomics, loss-of-function screens and transcriptomics confirmed WEE1 as a target for combination with dasatinib against PN GSCs. Utilizing this integrative approach could be of interest for studying resistance mechanisms and revealing combination therapy targets in further tumor entities.
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000293795 650_7 $$2Other$$aLoss-of-function shRNA screen
000293795 650_7 $$2Other$$aPhosphoproteomics
000293795 650_7 $$2Other$$aWEE1
000293795 650_7 $$2Other$$acomputational integration
000293795 650_7 $$2Other$$adasatinib
000293795 7001_ $$0P:(DE-He78)442ee8f54d846d943023a916889feb8e$$aGöttmann, Mona$$b1$$eFirst author
000293795 7001_ $$aGold, Maxwell P$$b2
000293795 7001_ $$0P:(DE-He78)880900065fdfb634b00cd591b801ee42$$aSchlue, Silja$$b3
000293795 7001_ $$0P:(DE-He78)743a4a82daab55306a2c88b9f6bf8c2f$$aHielscher, Thomas$$b4
000293795 7001_ $$0P:(DE-He78)f28fcc92d5c00f3ee511e3319c699b38$$aIskar, Murat$$b5
000293795 7001_ $$0P:(DE-He78)5c2c9cbe6ce72553684d82d94aebdadd$$aKessler, Tobias$$b6
000293795 7001_ $$aHai, Ling$$b7
000293795 7001_ $$0P:(DE-He78)3bdc7fb5a6314e2f3be584df6007b4ae$$aLokumcu, Tolga$$b8
000293795 7001_ $$aCousins, Clara C$$b9
000293795 7001_ $$aHerold-Mende, Christel$$b10
000293795 7001_ $$0P:(DE-He78)a5f5be3a0458fbc0017086b569fe7d75$$aHeßling, Bernd$$b11
000293795 7001_ $$aHorschitz, Sandra$$b12
000293795 7001_ $$aJabali, Ammar$$b13
000293795 7001_ $$aKoch, Philipp$$b14
000293795 7001_ $$aBaumgartner, Ulrich$$b15
000293795 7001_ $$aDay, Bryan W$$b16
000293795 7001_ $$0P:(DE-He78)92e9783ca7025f36ce14e12cd348d2ee$$aWick, Wolfgang$$b17
000293795 7001_ $$0P:(DE-He78)a1f4b408b9155beb2a8f7cba4d04fe88$$aSahm, Felix$$b18$$udkfz
000293795 7001_ $$aKrieg, Sandro M$$b19
000293795 7001_ $$aFraenkel, Ernest$$b20
000293795 7001_ $$0P:(DE-He78)830be4979a39935ac6272eaebad5982a$$aPhillips, Emma$$b21
000293795 7001_ $$0P:(DE-HGF)0$$aGoidts, Violaine$$b22$$eLast author
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