The Broad Institute, 415 Main Street, Cambridge, MA 02142, USA.
University of Washington, Department of Genome Sciences, 3720 15th Avenue NE, Seattle, WA 98195, USA.
Cell Syst. 2018 Apr 25;6(4):424-443.e7. doi: 10.1016/j.cels.2018.03.012. Epub 2018 Apr 11.
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.
尽管蛋白质组学的价值已经得到了证明，但成本和规模通常是阻碍其发展的因素，而基因表达谱分析仍然是描述细胞对干扰的反应的主要方法。然而，高通量的哨兵检测为蛋白质组学提供了在有意义的规模上做出贡献的机会。我们提出了一个系统的文库资源（90 种药物×6 种细胞系），其中包含了测量还原代表性磷酸化组（P100）和组蛋白上的表观遗传标记（GCP）变化的蛋白质组学特征。这些药物中的大多数都能产生可重复的特征，但观察到了明显的细胞系和检测特异性差异。使用“连接性”框架，我们比较了不同细胞类型的特征，并整合了不同检测方法的数据，包括转录检测（L1000）。细胞类型之间的一致连接性揭示了超越谱系的细胞反应，而检测方法之间的一致连接性揭示了药物之间的意外关联。我们进一步利用该资源来对抗公共数据，为多发性骨髓瘤和急性淋巴细胞白血病的治疗提出假设。该资源可在 https://clue.io/proteomics 上公开获取。
