Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK; Instituto Superior Técnico (IST), Universidade de Lisboa, 1049-001 Lisboa, Portugal; INESC-ID, 1000-029 Lisboa, Portugal.
ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
Cancer Cell. 2022 Aug 8;40(8):835-849.e8. doi: 10.1016/j.ccell.2022.06.010. Epub 2022 Jul 14.
The proteome provides unique insights into disease biology beyond the genome and transcriptome. A lack of large proteomic datasets has restricted the identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types are analyzed by mass spectrometry. Deploying a workflow to quantify 8,498 proteins, these data capture evidence of cell-type and post-transcriptional modifications. Integrating multi-omics, drug response, and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline reveals thousands of protein biomarkers of cancer vulnerabilities that are not significant at the transcript level. The power of the proteome to predict drug response is very similar to that of the transcriptome. Further, random downsampling to only 1,500 proteins has limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger) is a comprehensive resource available at https://cellmodelpassports.sanger.ac.uk.
蛋白质组学提供了超越基因组和转录组的疾病生物学的独特见解。缺乏大型蛋白质组数据集限制了新癌症生物标志物的识别。在这里，通过质谱分析了 28 种组织类型的 949 种癌细胞系的蛋白质组。通过部署一种定量 8498 种蛋白质的工作流程，这些数据捕获了细胞类型和转录后修饰的证据。将多组学、药物反应和 CRISPR-Cas9 基因必需性筛选与基于深度学习的管道集成，揭示了数千种癌症脆弱性的蛋白质生物标志物，这些标志物在转录水平上并不显著。蛋白质组预测药物反应的能力与转录组非常相似。此外，随机下采样到仅 1500 个蛋白质对预测能力的影响有限，这与蛋白质网络高度连接和共同调节一致。这个泛癌症蛋白质组图谱（ProCan-DepMapSanger）是一个综合性资源，可在 https://cellmodelpassports.sanger.ac.uk 上获取。
