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000304111 245__ $$aHigh content-imaging drug synergy screening identifies specific senescence-related vulnerabilities of mesenchymal neuroblastomas.
000304111 260__ $$aLondon [u.a.]$$bNature Publishing Group$$c2025
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000304111 520__ $$aNeuroblastomas encompass malignant cells with varying degrees of differentiation, ranging from adrenergic (adr) cells resembling the sympathoadrenal lineage to undifferentiated, stem-cell-like mesenchymal (mes) cancer cells. Relapsed neuroblastomas, which often have mesenchymal features, have a poor prognosis and respond less to anticancer therapies, necessitating the development of novel treatment strategies. To identify novel treatment options, we analyzed the sensitivity of 91 pediatric cell models, including patient-derived tumoroid cultures, to a drug library of 76 anti-cancer drugs at clinically relevant concentrations. This included 24 three-dimensionally cultured neuroblastoma cell lines representing the range of mesenchymal to adrenergic subtypes. High-throughput ATP-based luminescence measurements were compared to high-content confocal imaging. With machine learning-supported imaging analysis, we focused on changes in the lysosomal compartment as a marker for therapy-induced senescence and assessed the basal lysosomal levels in a subset of untreated mesenchymal versus adrenergic cells. We correlated these findings with pathway activity signatures based on bulk RNA and scRNAseq. Comprehensive image-based synergy screens with spheroid cultures validated the combined effects of selected drugs on proliferation and cytotoxicity. Mesenchymal models presented high basal lysosomal levels correlating with senescence-associated secretory phenotype (SASP) and sphingolipid metabolism pathways. Chemotherapy treatment further increased lysosome numbers, indicative of therapy-induced senescence. Furthermore, the mesenchymal subtypes correlated with MAPK activity and sensitivity to MAPK pathway inhibitors. Lysosomal and SASP signaling is druggable by inhibitors of lysosomal acid sphingomyelinase (SLMi) or senolytics, including BCL2-family inhibitors. Especially the sequential combination of MEK inhibitors (MEKi) with BCL2-family inhibitors was the most effective on relapsed neuroblastoma cell lines. Gene expression analysis of 223 patient samples, drug sensitivity profiling of five patient-derived fresh tissue cultures, and in vivo zebrafish embryo neuroblastoma xenograft models confirmed these findings. Inhibition of MAPK signaling in combination with BCL2-family inhibitors is a novel treatment option for patients suffering from relapsed neuroblastomas.
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000304111 650_7 $$2NLM Chemicals$$aAntineoplastic Agents
000304111 650_2 $$2MeSH$$aHumans
000304111 650_2 $$2MeSH$$aNeuroblastoma: pathology
000304111 650_2 $$2MeSH$$aNeuroblastoma: drug therapy
000304111 650_2 $$2MeSH$$aNeuroblastoma: metabolism
000304111 650_2 $$2MeSH$$aNeuroblastoma: genetics
000304111 650_2 $$2MeSH$$aCellular Senescence: drug effects
000304111 650_2 $$2MeSH$$aCell Line, Tumor
000304111 650_2 $$2MeSH$$aAnimals
000304111 650_2 $$2MeSH$$aAntineoplastic Agents: pharmacology
000304111 650_2 $$2MeSH$$aDrug Synergism
000304111 650_2 $$2MeSH$$aMesenchymal Stem Cells: drug effects
000304111 650_2 $$2MeSH$$aMesenchymal Stem Cells: metabolism
000304111 650_2 $$2MeSH$$aMesenchymal Stem Cells: pathology
000304111 650_2 $$2MeSH$$aCell Proliferation: drug effects
000304111 650_2 $$2MeSH$$aLysosomes: metabolism
000304111 650_2 $$2MeSH$$aLysosomes: drug effects
000304111 650_2 $$2MeSH$$aZebrafish
000304111 7001_ $$00000-0002-8538-4319$$aEmperador, Marta$$b1
000304111 7001_ $$0P:(DE-He78)972e5722b39c126d3b5ddefb432780b9$$aSmyrilli, Kyriaki$$b2$$udkfz
000304111 7001_ $$0P:(DE-He78)4679059a19b1f3cd341bd27d0ddb7c45$$aKocher, Daniela$$b3
000304111 7001_ $$0P:(DE-He78)32e22d1c8416af3f2a612da9121f2c05$$aCelikyürekli, Simay$$b4$$udkfz
000304111 7001_ $$0P:(DE-He78)7cf43fe3da2429e80c087d85018b09e4$$aZeiser, Constantia$$b5$$udkfz
000304111 7001_ $$0P:(DE-He78)4302629f88822e785a2ba95b985cc952$$aGerloff, Xenia$$b6
000304111 7001_ $$0P:(DE-He78)21d657d65d4ad0fd8b0bbfe10fa65172$$aKreth, Sina$$b7$$udkfz
000304111 7001_ $$0P:(DE-He78)a579ca2567736066534409e732b31c91$$aHenrich, Kai-Oliver$$b8$$udkfz
000304111 7001_ $$0P:(DE-He78)5100059e746b377e2e0a37c0e24f6bf7$$aMaaß, Kendra K$$b9$$udkfz
000304111 7001_ $$0P:(DE-He78)9eebe1af0e32ef6e4655e6ba195ef0ad$$aRettenmeier, Johanna$$b10$$udkfz
000304111 7001_ $$0P:(DE-He78)7a590ab95c6f7ba52880452da78ecd6c$$aGrünewald, Thomas$$b11$$udkfz
000304111 7001_ $$0P:(DE-He78)2727b5cb63b52d0137d4f4e8f110ee7e$$aPeterziel, Heike$$b12$$udkfz
000304111 7001_ $$0P:(DE-He78)91f32735ee876c579d63c05a7f4778dd$$aWestermann, Frank$$b13$$udkfz
000304111 7001_ $$aHamacher-Brady, Anne$$b14
000304111 7001_ $$0P:(DE-He78)143af26de9d57bf624771616318aaf7c$$aWitt, Olaf$$b15$$udkfz
000304111 7001_ $$0P:(DE-He78)908367a659dea9e28dac34592b3c46e5$$aOehme, Ina$$b16$$eLast author$$udkfz
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