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Understanding drugs in breast cancer through drug sensitivity screening.

Uhr K, Prager-van der Smissen WJ, Heine AA, Ozturk B, Smid M, Göhlmann HW, Jager A, Foekens JA, Martens JW - Springerplus (2015)

Bottom Line: 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.We found expected interactions but also discovered new relationships between drugs which might have implications for cancer treatment regimens.

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center, Postbus 2040, 's-Gravendijkwal 230, 3000 CA Rotterdam, The Netherlands.

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.

No MeSH data available.


Related in: MedlinePlus

Similar drugs cluster together. Depicted is a hierarchical unsupervised clustering of the analyzable drugs and cell lines. Blue color indicates low IC50 values (i.e. cells are drug-sensitive), and red color high IC50 values (i.e. cells are drug-resistant). Color intensity illustrates the degree of drug sensitivity or resistance; outliers exceeding the legend boundaries are set to the maxima colors of the legend to ensure visibility of small differences instead of few outliers. Breast-cancer subtypes are color-coded on the basis of the intrinsic subtypes of breast cancer cell lines as previously described (Riaz et al. 2013). The respective legend can be found on the top right. Tree distance is representative for similarity of drugs or cell lines. Drugs with similar response profiles among the cell lines are highlighted by red boxes
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Fig2: Similar drugs cluster together. Depicted is a hierarchical unsupervised clustering of the analyzable drugs and cell lines. Blue color indicates low IC50 values (i.e. cells are drug-sensitive), and red color high IC50 values (i.e. cells are drug-resistant). Color intensity illustrates the degree of drug sensitivity or resistance; outliers exceeding the legend boundaries are set to the maxima colors of the legend to ensure visibility of small differences instead of few outliers. Breast-cancer subtypes are color-coded on the basis of the intrinsic subtypes of breast cancer cell lines as previously described (Riaz et al. 2013). The respective legend can be found on the top right. Tree distance is representative for similarity of drugs or cell lines. Drugs with similar response profiles among the cell lines are highlighted by red boxes

Mentions: To investigate the relationships between different drugs the IC50 values of all 7 cytotoxic drugs and 30 targeted agents, measured in the 42 breast cancer cell lines, were correlated (Fig. 1). Capecitabine, cMet 605 and Cyclophosphamide exhibited no differential IC50 values and were consequently omitted from the clustering and further analyses. To express the relationships among drugs and cell lines hierarchical clustering was performed (Fig. 2). Clustering and correlation performed fairly similarly and are therefore discussed together.Fig. 1


Understanding drugs in breast cancer through drug sensitivity screening.

Uhr K, Prager-van der Smissen WJ, Heine AA, Ozturk B, Smid M, Göhlmann HW, Jager A, Foekens JA, Martens JW - Springerplus (2015)

Similar drugs cluster together. Depicted is a hierarchical unsupervised clustering of the analyzable drugs and cell lines. Blue color indicates low IC50 values (i.e. cells are drug-sensitive), and red color high IC50 values (i.e. cells are drug-resistant). Color intensity illustrates the degree of drug sensitivity or resistance; outliers exceeding the legend boundaries are set to the maxima colors of the legend to ensure visibility of small differences instead of few outliers. Breast-cancer subtypes are color-coded on the basis of the intrinsic subtypes of breast cancer cell lines as previously described (Riaz et al. 2013). The respective legend can be found on the top right. Tree distance is representative for similarity of drugs or cell lines. Drugs with similar response profiles among the cell lines are highlighted by red boxes
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4628005&req=5

Fig2: Similar drugs cluster together. Depicted is a hierarchical unsupervised clustering of the analyzable drugs and cell lines. Blue color indicates low IC50 values (i.e. cells are drug-sensitive), and red color high IC50 values (i.e. cells are drug-resistant). Color intensity illustrates the degree of drug sensitivity or resistance; outliers exceeding the legend boundaries are set to the maxima colors of the legend to ensure visibility of small differences instead of few outliers. Breast-cancer subtypes are color-coded on the basis of the intrinsic subtypes of breast cancer cell lines as previously described (Riaz et al. 2013). The respective legend can be found on the top right. Tree distance is representative for similarity of drugs or cell lines. Drugs with similar response profiles among the cell lines are highlighted by red boxes
Mentions: To investigate the relationships between different drugs the IC50 values of all 7 cytotoxic drugs and 30 targeted agents, measured in the 42 breast cancer cell lines, were correlated (Fig. 1). Capecitabine, cMet 605 and Cyclophosphamide exhibited no differential IC50 values and were consequently omitted from the clustering and further analyses. To express the relationships among drugs and cell lines hierarchical clustering was performed (Fig. 2). Clustering and correlation performed fairly similarly and are therefore discussed together.Fig. 1

Bottom Line: 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.We found expected interactions but also discovered new relationships between drugs which might have implications for cancer treatment regimens.

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center, Postbus 2040, 's-Gravendijkwal 230, 3000 CA Rotterdam, The Netherlands.

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.

No MeSH data available.


Related in: MedlinePlus