Uhr Katharina, Prager-van der Smissen Wendy J C, Heine Anouk A J, Ozturk Bahar, Smid Marcel, Göhlmann Hinrich W H, Jager Agnes, Foekens John A, Martens John W M
Department of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center, Postbus 2040, 's-Gravendijkwal 230, 3000 CA Rotterdam, The Netherlands.
Division of Janssen Pharmaceutica, Johnson & Johnson Pharmaceutical Research and Development, Turnhoutseweg 30, 2340 Beerse, Belgium.
Springerplus. 2015 Oct 15;4:611. doi: 10.1186/s40064-015-1406-8. eCollection 2015.
With substantial numbers of breast tumors showing or acquiring treatment resistance, it is of utmost importance to develop new agents for the treatment of the disease, to know their effectiveness against breast cancer and to understand their relationships with other drugs to best assign the right drug to the right patient. To achieve this goal drug screenings on breast cancer cell lines are a promising approach. In this study a large-scale drug screening of 37 compounds was performed on a panel of 42 breast cancer cell lines representing the main breast cancer subtypes. Clustering, correlation and pathway analyses were used for data analysis. We found that compounds with a related mechanism of action had correlated IC50 values and thus grouped together when the cell lines were hierarchically clustered based on IC50 values. In total we found six clusters of drugs of which five consisted of drugs with related mode of action and one cluster with two drugs not previously connected. In total, 25 correlated and four anti-correlated drug sensitivities were revealed of which only one drug, Sirolimus, showed significantly lower IC50 values in the luminal/ERBB2 breast cancer subtype. We found expected interactions but also discovered new relationships between drugs which might have implications for cancer treatment regimens.
由于大量乳腺肿瘤表现出或产生了治疗抗性，开发治疗该疾病的新药物、了解它们对乳腺癌的有效性以及理解它们与其他药物的关系，以便为合适的患者选择合适的药物，这至关重要。为实现这一目标，对乳腺癌细胞系进行药物筛选是一种很有前景的方法。在本研究中，对代表主要乳腺癌亚型的42种乳腺癌细胞系组成的细胞组进行了37种化合物的大规模药物筛选。采用聚类、相关性和通路分析进行数据分析。我们发现，具有相关作用机制的化合物具有相关的IC50值，因此当根据IC50值对细胞系进行层次聚类时会聚集在一起。我们总共发现了六类药物，其中五类由作用方式相关的药物组成，一类由两种以前未关联的药物组成。总共揭示了25种相关和4种反相关的药物敏感性，其中只有一种药物西罗莫司在管腔/ERBB2乳腺癌亚型中显示出显著更低的IC50值。我们发现了预期的相互作用，还发现了药物之间的新关系，这可能对癌症治疗方案有影响。
