Data from: Quantification of sensitivity and resistance of breast cancer cell lines to anti-cancer drugs using GR metrics

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 (GR50) and efficacy (GRmax) that are analogous to the more familiar IC50 and Emax 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/.传统用于评估抗癌药物对细胞系生长与存活影响的方法，均以药物处理组与对照组样本中的相对细胞数量为依据，但会因自然生物学变异与培养条件差异引发的细胞分裂速率不均，受到严重的混杂偏倚。通过以每细胞分裂为单位计算药物敏感性，可解决该问题。标准化生长速率抑制（normalized growth rate inhibition, GR）方法能够产出以每细胞分裂为单位的药物效力指标GR50与药物效能指标GRmax，二者与更为人熟知的IC50与Emax值具有相似性。在本研究中，我们报道了针对约4700对乳腺癌细胞系与扰动因子（perturbagens）的、基于GR且经增殖校正的药物敏感性指标。此类数据对于解析治疗应答与耐药性的分子机制具有广泛应用价值。本研究利用这些指标探究了不同药物敏感性评估方式之间的关联，并得出结论：药物效力与效能存在高度变异，且二者仅呈现弱相关性。为便于后续使用这些数据，用户可通过http://www.GRbrowser.org/交互式浏览计算得到的GR曲线与相关指标。