蛋白质组学
生物
计算生物学
表观遗传学
染色质
组蛋白
药物发现
染色质免疫沉淀
定量蛋白质组学
生物信息学
基因
基因表达
遗传学
发起人
作者
Lev Litichevskiy,Ryan Peckner,Jennifer G. Abelin,Jacob K. Asiedu,Amanda L. Creech,John F. Davis,Desiree Davison,Caitlin M. Dunning,Jarrett D. Egertson,Shawn B. Egri,Joshua Gould,Tak Ko,Sarah Johnson,David L. Lahr,Daniel D. Lam,Zihan Liu,Nicholas Lyons,Xiaodong Lü,Brendan MacLean,Alison E. Mungenast
出处
期刊:Cell systems
[Elsevier BV]
日期:2018-04-01
卷期号:6 (4): 424-443.e7
被引量:83
标识
DOI:10.1016/j.cels.2018.03.012
摘要
Although the value of proteomics has been demonstrated, cost and scale are typically prohibitive, and gene expression profiling remains dominant for characterizing cellular responses to perturbations. However, high-throughput sentinel assays provide an opportunity for proteomics to contribute at a meaningful scale. We present a systematic library resource (90 drugs × 6 cell lines) of proteomic signatures that measure changes in the reduced-representation phosphoproteome (P100) and changes in epigenetic marks on histones (GCP). A majority of these drugs elicited reproducible signatures, but notable cell line- and assay-specific differences were observed. Using the "connectivity" framework, we compared signatures across cell types and integrated data across assays, including a transcriptional assay (L1000). Consistent connectivity among cell types revealed cellular responses that transcended lineage, and consistent connectivity among assays revealed unexpected associations between drugs. We further leveraged the resource against public data to formulate hypotheses for treatment of multiple myeloma and acute lymphocytic leukemia. This resource is publicly available at https://clue.io/proteomics.
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