Uitdehaag Joost C M, de Roos Jeroen A D M, Prinsen Martine B W, Willemsen-Seegers Nicole, de Vetter Judith R F, Dylus Jelle, van Doornmalen Antoon M, Kooijman Jeffrey, Sawa Masaaki, van Gerwen Suzanne J C, de Man Jos, Buijsman Rogier C, Zaman Guido J R
Netherlands Translational Research Center B.V., Kloosterstraat, the Netherlands.
Carna Biosciences, Inc., Kobe, Japan.
Mol Cancer Ther. 2016 Dec;15(12):3097-3109. doi: 10.1158/1535-7163.MCT-16-0403. Epub 2016 Sep 1.
Cancer cell line panels are important tools to characterize the in vitro activity of new investigational drugs. Here, we present the inhibition profiles of 122 anticancer agents in proliferation assays with 44 or 66 genetically characterized cancer cell lines from diverse tumor tissues (Oncolines). The library includes 29 cytotoxics, 68 kinase inhibitors, and 11 epigenetic modulators. For 38 compounds this is the first comparative profiling in a cell line panel. By strictly maintaining optimized assay protocols, biological variation was kept to a minimum. Replicate profiles of 16 agents over three years show a high average Pearson correlation of 0.8 using IC values and 0.9 using GI values. Good correlations were observed with other panels. Curve fitting appears a large source of variation. Hierarchical clustering revealed 44 basic clusters, of which 26 contain compounds with common mechanisms of action, of which 9 were not reported before, including TTK, BET and two clusters of EZH2 inhibitors. To investigate unexpected clusterings, sets of BTK, Aurora and PI3K inhibitors were profiled in biochemical enzyme activity assays and surface plasmon resonance binding assays. The BTK inhibitor ibrutinib clusters with EGFR inhibitors, because it cross-reacts with EGFR. Aurora kinase inhibitors separate into two clusters, related to Aurora A or pan-Aurora selectivity. Similarly, 12 inhibitors in the PI3K/AKT/mTOR pathway separated into different clusters, reflecting biochemical selectivity (pan-PI3K, PI3Kβγδ-isoform selective or mTOR-selective). Of these, only allosteric mTOR inhibitors preferentially targeted PTEN-mutated cell lines. This shows that cell line profiling is an excellent tool for the unbiased classification of antiproliferative compounds. Mol Cancer Ther; 15(12); 3097-109. ©2016 AACR.
癌细胞系面板是表征新型研究药物体外活性的重要工具。在此,我们展示了122种抗癌药物在增殖试验中的抑制谱,这些试验使用了来自不同肿瘤组织(肿瘤细胞系)的44或66种基因特征明确的癌细胞系。该文库包括29种细胞毒性药物、68种激酶抑制剂和11种表观遗传调节剂。对于38种化合物,这是在细胞系面板中的首次比较分析。通过严格维持优化的试验方案,将生物学变异降至最低。16种药物在三年中的重复分析显示,使用IC值时平均皮尔逊相关性较高,为0.8,使用GI值时为0.9。与其他面板观察到良好的相关性。曲线拟合似乎是变异的一个重要来源。层次聚类揭示了44个基本聚类,其中26个包含具有共同作用机制的化合物,其中9个以前未报道过,包括TTK、BET和两组EZH2抑制剂。为了研究意外的聚类情况,在生化酶活性测定和表面等离子体共振结合测定中对BTK、Aurora和PI3K抑制剂组进行了分析。BTK抑制剂依鲁替尼与EGFR抑制剂聚类,因为它与EGFR发生交叉反应。Aurora激酶抑制剂分为两个聚类,与Aurora A或泛Aurora选择性有关。同样,PI3K/AKT/mTOR途径中的12种抑制剂分为不同的聚类,反映了生化选择性(泛PI3K、PI3Kβγδ异构体选择性或mTOR选择性)。其中,只有变构mTOR抑制剂优先靶向PTEN突变的细胞系。这表明细胞系分析是对抗增殖化合物进行无偏分类的优秀工具。《分子癌症治疗》;15(12);3097 - 109。©2016美国癌症研究协会。