Wang Jing, Mouradov Dmitri, Wang Xiaojing, Jorissen Robert N, Chambers Matthew C, Zimmerman Lisa J, Vasaikar Suhas, Love Christopher G, Li Shan, Lowes Kym, Leuchowius Karl-Johan, Jousset Helene, Weinstock Janet, Yau Christopher, Mariadason John, Shi Zhiao, Ban Yuguang, Chen Xi, Coffey Robert J C, Slebos Robbert J C, Burgess Antony W, Liebler Daniel C, Zhang Bing, Sieber Oliver M
Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas.
Systems Biology and Personalised Medicine Division, The Walter and Eliza Hall Institute of Medial Research, Parkville, VIC, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia.
Gastroenterology. 2017 Oct;153(4):1082-1095. doi: 10.1053/j.gastro.2017.06.008. Epub 2017 Jun 16.
Proteomics holds promise for individualizing cancer treatment. We analyzed to what extent the proteomic landscape of human colorectal cancer (CRC) is maintained in established CRC cell lines and the utility of proteomics for predicting therapeutic responses.
Proteomic and transcriptomic analyses were performed on 44 CRC cell lines, compared against primary CRCs (n=95) and normal tissues (n=60), and integrated with genomic and drug sensitivity data.
Cell lines mirrored the proteomic aberrations of primary tumors, in particular for intrinsic programs. Tumor relationships of protein expression with DNA copy number aberrations and signatures of post-transcriptional regulation were recapitulated in cell lines. The 5 proteomic subtypes previously identified in tumors were represented among cell lines. Nonetheless, systematic differences between cell line and tumor proteomes were apparent, attributable to stroma, extrinsic signaling, and growth conditions. Contribution of tumor stroma obscured signatures of DNA mismatch repair identified in cell lines with a hypermutation phenotype. Global proteomic data showed improved utility for predicting both known drug-target relationships and overall drug sensitivity as compared with genomic or transcriptomic measurements. Inhibition of targetable proteins associated with drug responses further identified corresponding synergistic or antagonistic drug combinations. Our data provide evidence for CRC proteomic subtype-specific drug responses.
Proteomes of established CRC cell line are representative of primary tumors. Proteomic data tend to exhibit improved prediction of drug sensitivity as compared with genomic and transcriptomic profiles. Our integrative proteogenomic analysis highlights the potential of proteome profiling to inform personalized cancer medicine.
蛋白质组学有望实现癌症治疗的个体化。我们分析了人类结直肠癌(CRC)的蛋白质组格局在已建立的CRC细胞系中得以保留的程度,以及蛋白质组学在预测治疗反应方面的实用性。
对44个CRC细胞系进行了蛋白质组学和转录组学分析,并与原发性CRC(n = 95)和正常组织(n = 60)进行比较,并与基因组和药物敏感性数据进行整合。
细胞系反映了原发性肿瘤的蛋白质组异常,特别是对于内在程序。蛋白质表达与DNA拷贝数异常以及转录后调控特征之间的肿瘤关系在细胞系中得以重现。先前在肿瘤中鉴定出的5种蛋白质组亚型在细胞系中也有体现。尽管如此,细胞系和肿瘤蛋白质组之间的系统差异仍然明显,这归因于基质、外在信号和生长条件。肿瘤基质的作用掩盖了在具有高突变表型的细胞系中鉴定出的DNA错配修复特征。与基因组或转录组测量相比,全局蛋白质组数据在预测已知药物-靶点关系和总体药物敏感性方面显示出更高的实用性。抑制与药物反应相关的可靶向蛋白质进一步确定了相应的协同或拮抗药物组合。我们的数据为CRC蛋白质组亚型特异性药物反应提供了证据。
已建立的CRC细胞系的蛋白质组代表原发性肿瘤。与基因组和转录组图谱相比,蛋白质组数据在预测药物敏感性方面往往表现更佳。我们的综合蛋白质基因组分析突出了蛋白质组分析在指导个性化癌症医学方面的潜力。