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Drug combination essays. The combinations were selected from 20 "responsive" drugs (Table 1). 16 two-drug combinations matrices were applied to two cell lines (TCCSUP & UMUC3). 5x5 matrices (10x5 wells including duplicates) + single-drug rows and columns + controls were prepared. 4 dual combinations were set in each plate, 8 plates total (4 for each cell line). Example of 7 single features response for the combination of Radicinin (rows) and Brasilin (columns) in concentrations of 4-0.25µM are displayed for the two cell lines (TOP). The data require preparation of larger matrices with more dilutions and repeats. Nevertheless we attempted to fit the Mahalanobis scores (BOTTOM) to Loewe or Bliss models (see Methods) but found no significant synergism.
Source publication
We present here a novel multi-parametric approach for the characterization of multiple cellular features, using images acquired by high-throughput and high-definition light microscopy. We specifically used this approach for deep and unbiased analysis of the effects of a drug library on five cultured cell lines. The presented method enables the acqu...
Context in source publication
Context 1
... addition, since systematic screen of all drug combinations is not practical, selection based on multi-parametric analysis may increase the chance of identifying interactions between different cellular mechanisms favorably affected by drug combinations. In Figure 4 we show matrices of the responses of one combination (Radicinin and Brasilin) out of 16 binary combinations tested at five 2-fold dilutions around the "AC 50 " concentration of the single drug treatments. Differences between the two treated cell (Table 1). ...
Citations
We present here a novel multi-parametric approach for the characterization of multiple cellular features, using images acquired by high-throughput and high-definition light microscopy. We specifically used this approach for deep and unbiased analysis of the effects of a drug library on five cultured cell lines. The presented method enables the acquisition and analysis of millions of images, of treated and control cells, followed by an automated identification of drugs inducing strong responses, evaluating the median effect concentrations and those cellular properties that are most highly affected by the drug. The tools described here provide standardized quantification of multiple attributes for systems level dissection of complex functions in normal and diseased cells, using multiple perturbations. Such analysis of cells, derived from pathological samples, may help in the diagnosis and follow-up of treatment in patients.
