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Comparing the value of mono- versus coculture for high-throughput compound screening in hematological malignancies

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TLDR
In this article , the authors measured ex vivo sensitivity of 108 primary blood cancer samples to 50 drugs in monoculture and in coculture with bone marrow stromal cells and found that the effect sizes were lower in the coculture than in the mono-and coculture.
Abstract
Large-scale compound screens are a powerful model system for understanding variability of treatment response and for discovering druggable tumor vulnerabilities of hematological malignancies. However, as mostly performed in a monoculture of tumor cells, these assays disregard modulatory effects of the in vivo microenvironment. It is an open question whether and to what extent coculture with bone marrow stromal cells could improve the biological relevance of drug testing assays over monoculture. Here, we measured ex vivo sensitivity of 108 primary blood cancer samples to 50 drugs in monoculture and in coculture with bone marrow stromal cells. Stromal coculture conferred resistance to 52 % of compounds in chronic lymphocytic leukemia (CLL) and to 36% of compounds in acute myeloid leukemia (AML), including chemotherapeutics, BCR inhibitors, proteasome inhibitors and BET inhibitors. While most of the remaining drugs were similarly effective in mono- and coculture, only the JAK inhibitors ruxolitinib and tofacitinib exhibited increased efficacy in AML and CLL stromal coculture. We further confirmed the importance of JAK-STAT signaling for stroma-mediated resistance by showing that stromal cells induce phosphorylation of STAT3 in CLL cells. We genetically characterized the 108 cancer samples and found that drug-gene associations agreed well between mono- and coculture. Overall, effect sizes were lower in coculture, thus more drug-gene associations were detected in monoculture than in coculture. Our results suggest a two-step strategy for drug perturbation testing, with large-scale screening performed in monoculture, followed by focused evaluation of potential stroma-mediated resistances in coculture.

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Drug‐microenvironment perturbations reveal resistance mechanisms and prognostic subgroups in CLL

TL;DR: The impact of microenvironmental stimuli on drug response and their dependence on genetic alterations are quantified, identifying interleukin 4 and Toll‐like receptor (TLR) stimulation as the strongest actuators of drug resistance.
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Conditional lethality profiling reveals anticancer mechanisms of action and drug-nutrient interactions

TL;DR: In this paper , the authors performed high-throughput screens in conventional versus human plasma-like medium (HPLM) and found that brivudine affects two independent targets in folate metabolism.
References
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Going deeper with convolutions

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The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity

TL;DR: The results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents and the generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of ‘personalized’ therapeutic regimens.
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Systematic identification of genomic markers of drug sensitivity in cancer cells

TL;DR: It was found that mutated cancer genes were associated with cellular response to most currently available cancer drugs, and systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.
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A Landscape of Pharmacogenomic Interactions in Cancer

TL;DR: It is reported how cancer-driven alterations identified in 11,289 tumors from 29 tissues can be mapped onto 1,001 molecularly annotated human cancer cell lines and correlated with sensitivity to 265 drugs.
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