ABSTRACT
Drug combinations are a promising strategy to overcome the compensatory mechanisms and unwanted off-target effects that limit the utility of many potential drugs. However, enthusiasm for this approach is tempered by concerns that the therapeutic synergy of a combination will be accompanied by synergistic side effects. Using large scale simulations of bacterial metabolism and 94,110 multi-dose experiments relevant to diverse diseases, we provide evidence that synergistic drug combinations are generally more specific to particular cellular contexts than are single agent activities. We highlight six combinations whose selective synergy depends on multitarget drug activity. For one anti-inflammatory example, we show how such selectivity is achieved through differential expression of the drugs' targets in cell types associated with therapeutic, but not toxic, effects and validate its therapeutic relevance in a rat model of asthma. The context specificity of synergistic combinations creates many opportunities for therapeutically relevant selectivity and enables improved control of complex biological systems.
Subject(s)
Drug Synergism , Drug Therapy, Combination , Pharmaceutical Preparations/administration & dosage , Pharmacology , Animals , Cell Line, Tumor , Disease Models, Animal , Drug Discovery , Drug-Related Side Effects and Adverse Reactions , Escherichia coli/drug effects , Escherichia coli/growth & development , Humans , Male , Models, Biological , Rats , Rats, Sprague-Dawley , Reproducibility of ResultsABSTRACT
Acute lymphoblastic leukemias carrying a chromosomal translocation involving the mixed-lineage leukemia gene (MLL, ALL1, HRX) have a particularly poor prognosis. Here we show that they have a characteristic, highly distinct gene expression profile that is consistent with an early hematopoietic progenitor expressing select multilineage markers and individual HOX genes. Clustering algorithms reveal that lymphoblastic leukemias with MLL translocations can clearly be separated from conventional acute lymphoblastic and acute myelogenous leukemias. We propose that they constitute a distinct disease, denoted here as MLL, and show that the differences in gene expression are robust enough to classify leukemias correctly as MLL, acute lymphoblastic leukemia or acute myelogenous leukemia. Establishing that MLL is a unique entity is critical, as it mandates the examination of selectively expressed genes for urgently needed molecular targets.
