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000144469 0247_ $$2doi$$a10.1007/978-1-4939-9151-8_17
000144469 0247_ $$2pmid$$apmid:30779044
000144469 0247_ $$2ISSN$$a1064-3745
000144469 0247_ $$2ISSN$$a1940-6029
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000144469 037__ $$aDKFZ-2019-01920
000144469 041__ $$aeng
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000144469 1001_ $$0P:(DE-He78)b19e65a29d89d299cf5a04670a7ff0ae$$aTomska, Katarzyna$$b0$$eFirst author$$udkfz
000144469 245__ $$aLymphoma and Leukemia Cell Vulnerabilities and Resistance Identified by Compound Library Screens.
000144469 260__ $$a[Heidelberg]$$b[Springer]$$c2019
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000144469 520__ $$aResponse to anticancer agents is often restricted to subsets of patients. The recognition of factors underlying this heterogeneity and the identification of biomarkers associated with response to drugs would greatly improve the efficacy of drug treatment. Platforms that can comprehensively map drug response in high-throughput ex vivo provide a unique tool to identify associated biomarkers and provide hypotheses for mechanisms underlying variable response. Such screens can be performed on cell lines and short-term cultures of primary cells to take advantage of the respective models' strength, which include, e.g., the ability to silence genes in cell lines and the 'indefinite' supply of primary cells where clonal selection can be avoided. Cohorts of such samples represent the natural diversity of cancers, including rarer mutations and combinatorial patterns of mutations.We here summarize a simple and scalable method for the measurement of viability after drug exposure based on ATP measurements as a surrogate for viability, which we use to measure and understand drug response in cell lines and primary cells.
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000144469 650_7 $$2NLM Chemicals$$aAntineoplastic Agents
000144469 650_7 $$2NLM Chemicals$$aBiomarkers, Pharmacological
000144469 7001_ $$0P:(DE-He78)648d23797edea029cdadba96810a9e8c$$aScheinost, Sebastian$$b1$$udkfz
000144469 7001_ $$aZenz, Thorsten$$b2
000144469 773__ $$0PERI:(DE-600)2493551-7$$a10.1007/978-1-4939-9151-8_17$$p351-362$$tMethods in molecular biology$$v1956$$x1064-3745$$y2019
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000144469 9141_ $$y2019
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