HMS LINCS Center, Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, MA 02115 USA.
MEP LINCS Center, Department of Biomedical Engineering and Oregon Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR 97239 USA.
Sci Data. 2017 Nov 7;4:170166. doi: 10.1038/sdata.2017.166.
Traditional means for scoring the effects of anti-cancer drugs on the growth and survival of cell lines is based on relative cell number in drug-treated and control samples and is seriously confounded by unequal division rates arising from natural biological variation and differences in culture conditions. This problem can be overcome by computing drug sensitivity on a per-division basis. The normalized growth rate inhibition (GR) approach yields per-division metrics for drug potency (GR) and efficacy (GR) that are analogous to the more familiar IC and E values. In this work, we report GR-based, proliferation-corrected, drug sensitivity metrics for ~4,700 pairs of breast cancer cell lines and perturbagens. Such data are broadly useful in understanding the molecular basis of therapeutic response and resistance. Here, we use them to investigate the relationship between different measures of drug sensitivity and conclude that drug potency and efficacy exhibit high variation that is only weakly correlated. To facilitate further use of these data, computed GR curves and metrics can be browsed interactively at http://www.GRbrowser.org/.
传统的基于细胞系生长和存活的抗癌药物效果评分方法基于药物处理和对照样品中的相对细胞数量，并且由于自然生物学变异和培养条件差异引起的不均等分裂率而受到严重干扰。这个问题可以通过基于每个分裂计算药物敏感性来克服。归一化生长率抑制（GR）方法产生了药物效力（GR）和疗效（GR）的每分裂度量，类似于更熟悉的 IC 和 E 值。在这项工作中，我们报告了基于 GR 的、增殖校正的、约 4700 对乳腺癌细胞系和扰动剂的药物敏感性度量。此类数据在理解治疗反应和耐药性的分子基础方面具有广泛的用途。在这里，我们使用它们来研究不同药物敏感性测量之间的关系，并得出结论，药物效力和疗效表现出高度变化，而且相关性很弱。为了便于进一步使用这些数据，可以在 http://www.GRbrowser.org/ 上交互浏览计算的 GR 曲线和度量。
