Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, 20742, USA.
Cancer Data Science Lab, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, USA.
Sci Rep. 2019 Jul 29;9(1):10989. doi: 10.1038/s41598-019-47440-w.
The efficacy of prospective cancer treatments is routinely estimated by in vitro cell-line proliferation screens. However, it is unclear whether tumor aggressiveness and patient survival are influenced more by the proliferative or the migratory properties of cancer cells. To address this question, we experimentally measured proliferation and migration phenotypes across more than 40 breast cancer cell-lines. Based on the latter, we built and validated individual predictors of breast cancer proliferation and migration levels from the cells' transcriptomics. We then apply these predictors to estimate the proliferation and migration levels of more than 1000 TCGA breast cancer tumors. Reassuringly, both estimates increase with tumor's aggressiveness, as qualified by its stage, grade, and subtype. However, predicted tumor migration levels are significantly more strongly associated with patient survival than the proliferation levels. We confirmed these findings by conducting siRNA knock-down experiments on the highly migratory MDA-MB-231 cell lines and deriving gene knock-down based proliferation and migration signatures. We show that cytoskeletal drugs might be more beneficial in patients with high predicted migration levels. Taken together, these results testify to the importance of migration levels in determining patient survival.
前瞻性癌症治疗的疗效通常通过体外细胞系增殖筛选来估计。然而,尚不清楚肿瘤侵袭性和患者生存是否更多地受到癌细胞增殖或迁移特性的影响。为了解决这个问题,我们在 40 多种乳腺癌细胞系中实验性地测量了增殖和迁移表型。基于后者,我们从细胞转录组学中构建并验证了预测乳腺癌细胞增殖和迁移水平的个体预测因子。然后,我们将这些预测因子应用于估计超过 1000 个 TCGA 乳腺癌肿瘤的增殖和迁移水平。令人欣慰的是,这两个估计值都随着肿瘤的侵袭性增加而增加,其侵袭性由其分期、分级和亚型来确定。然而,与增殖水平相比,预测的肿瘤迁移水平与患者生存的相关性要强得多。我们通过对高迁移性 MDA-MB-231 细胞系进行 siRNA 敲低实验并得出基于基因敲低的增殖和迁移特征,证实了这些发现。我们表明,细胞骨架药物可能对预测迁移水平高的患者更有益。总之,这些结果证明了迁移水平在确定患者生存中的重要性。