Abstract
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.Electronic supplementary materialThe online version of this article (doi:10.1186/s40064-015-1406-8) contains supplementary material, which is available to authorized users.
Highlights
Life expectancy and survival of breast cancer patients have increased significantly over the last decades, due to—amongst other factors—an increasing number of effective drug therapies (Berry et al 2005; Lichtenberg 2009, 2011)
Relationships between drugs: clustering and correlation analysis To investigate the relationships between different drugs the inhibitory concentration 50 (IC50) values of all 7 cytotoxic drugs and 30 targeted agents, measured in the 42 breast cancer cell lines, were correlated (Fig. 1)
Serdemetan, a drug which acts on cholesterol transport and targets MDM2 proto-oncogene (MDM2) (Jones et al 2013)—a mechanism shared with Nutlin-3 and MI-219 (Shangary and Wang 2009)—showed no correlation with these two compounds
Summary
Life expectancy and survival of breast cancer patients have increased significantly over the last decades, due to—amongst other factors—an increasing number of effective drug therapies (Berry et al 2005; Lichtenberg 2009, 2011). In the last couple of years large scale generation sequencing efforts have made a big contribution to our understanding of breast cancer by delivering precise information on cancer driver mutations (Kangaspeska et al 2012; Desmedt et al 2012; Previati et al 2013; Radovich et al 2013; The Cancer Genome Atlas Network 2012) All these sources of information combined have helped to elucidate how breast cancer evolves, progresses and metastasizes and some of them have led to the development of diagnostic tests to characterize breast cancer better (Kittaneh et al 2013). As a first step to test new compounds breast cancer cell lines are a good model, because
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