Additional file 1: Table S1. of Comparison, alignment, and synchronization of cell line information between CLO and EFO

EFO cell lines drawn from external sources. In the initial step of the EFO-CLO comparison and alignment process, there are 428 and 20 EFO cell lines which were imported from Cell Line Ontology and 20 in BRENDA Tissue and Enzyme Source Ontology respectively. These 448 EFO cell lines were excluded from the entire mapping process. File is stored in Microsoft Excel spreadsheet (xlsx) format. (XLSX 47 kb

Additional file 2: Table S2. of Comparison, alignment, and synchronization of cell line information between CLO and EFO

Final EFO-CLO alignment result. The 874 EFO-CLO mapped cell lines aligned and merged into CLO (Tab. 1 in the excel file) and 344 EFO unique immortalized permanent cell lines added to CLO (Tab. 2 in the excel file). File is stored in Microsoft Excel spreadsheet (xlsx) format. (XLSX 54 kb

Results of statistical analysis using repeated measures one-way ANOVA with Dunnett's multiple comparisons between patient cells and normal mononuclear blood cells (N1) on viability of the best drug combinations originating from the cell lines search and from pairs of single agents plus imatininb.

<p>Patients B001 and B002 are BCR-ABL+ (ALL). Patients B031 to B037 are BCR-ABL- (ALL).</p

Identification of Drug Combinations Containing Imatinib for Treatment of BCR-ABL+ Leukemias

<div><p>The BCR-ABL translocation is found in chronic myeloid leukemia (CML) and in Ph+ acute lymphoblastic leukemia (ALL) patients. Although imatinib and its analogues have been used as front-line therapy to target this mutation and control the disease for over a decade, resistance to the therapy is still observed and most patients are not cured but need to continue the therapy indefinitely. It is therefore of great importance to find new therapies, possibly as drug combinations, which can overcome drug resistance. In this study, we identified eleven candidate anti-leukemic drugs that might be combined with imatinib, using three approaches: a kinase inhibitor library screen, a gene expression correlation analysis, and literature analysis. We then used an experimental search algorithm to efficiently explore the large space of possible drug and dose combinations and identified drug combinations that selectively kill a BCR-ABL+ leukemic cell line (K562) over a normal fibroblast cell line (IMR-90). Only six iterations of the algorithm were needed to identify very selective drug combinations. The efficacy of the top forty-nine combinations was further confirmed using Ph+ and Ph- ALL patient cells, including imatinib-resistant cells. Collectively, the drug combinations and methods we describe might be a first step towards more effective interventions for leukemia patients, especially those with the BCR-ABL translocation.</p></div

Iterative search for a highly selective drug combinations

<p>(a) Increased selectivity after each iteration step. The lines represent the selectivity of the drug combinations at as triplets and at each of the six iteration steps. (b) A dot plot showing corrected selectivity (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0102221#s2" target="_blank">Results</a>) through the iterative searches. The pie symbols shows the relative contributions of the 12 drugs for the best combination obtained at each iteration. (c) Cluster analysis on the optimized drug combinations. The top ranked 200 combinations clustered into two groups and the frequencies of the doses of the individual drugs are shown for each cluster.</p

The list and targets of the drugs used in the combinatorial studies.

<p>The list and targets of the drugs used in the combinatorial studies.</p

Test of optimum drug combinations in the patient cells.

<p>The best 49 drug combinations or single agents used for the combination were tested in the cells from BCR-ABL+ and BCR-ABL- ALL patients. The selectivity (vs control IMR fibroblasts) obtained in each patient specimen was color-coded from red (lowest) to green (highest). The drug combinations were also tested in Burkitt's lymphoma patient and in normal subject white blood cells as controls.</p

Scheme of our search strategy

<p>(a) anti-leukemic drugs were selected using three approaches: kinase inhibitor library screens, correlation analysis, and literature survey. (b) Dose responses of single agent and pair-wise analysis with a fixed dose of imatinib (pairs and triplets) were performed. (c) The drug combinations were optimized using iterative search algorithm (d) The optimal drug combinations were validated with primary patient cells.</p

Concentrations (µM) and levels of 11 small molecules used with imatinib in the combinatorial drug searches.

<p>Concentrations (µM) and levels of 11 small molecules used with imatinib in the combinatorial drug searches.</p

Top 10 kinases that show a protective response in hypoxia when inhibited.

<p>The data were obtained using KIEN on the entire kinase inhibitor library. The coefficient <i>β</i>_<i>k</i>, a measure of the protective impact of each kinase, was calculated and the kinases were ranked using this parameter in order to estimate the main kinases influencing the protective mechanisms against hypoxia. In bold we show kinases important for the response of both cell lines.</p><p>Top 10 kinases that show a protective response in hypoxia when inhibited.</p