Understanding resistance to combination chemotherapy

Abstract

The current clinical application of combination chemotherapy is guided by a historically successful set of practices that were developed by basic and clinical researchers 50-60 years ago. Thus, in order to understand how emerging approaches to drug development might aid the creation of new therapeutic combinations, it is critical to understand the defining principles underlying classic combination therapy and the original experimental rationales behind them. One such principle is that the use of combination therapies with independent mechanisms of action can minimize the evolution of drug resistance. Another is that in order to kill sufficient cancer cells to cure a patient, multiple drugs must be delivered at their maximum tolerated dose - a condition that allows for enhanced cancer cell killing with manageable toxicity. In light of these models, we aim to explore recent genomic evidence underlying the mechanisms of resistance to the combination regimens constructed on these principles. Interestingly, we find that emerging genomic evidence contradicts some of the rationales of early practitioners in developing commonly used drug regimens. However, we also find that the addition of recent targeted therapies has yet to change the current principles underlying the construction of anti-cancer combinatorial regimens, nor have they made substantial inroads into the treatment of most cancers. We suggest that emerging systems/network biology approaches have an immense opportunity to impact the rational development of successful drug regimens. Specifically, by examining drug combinations in multivariate ways, next generation combination therapies can be constructed with a clear understanding of how mechanisms of resistance to multi-drug regimens differ from single agent resistance.

Figure 1

A diagram showing the relationship between single and combinatorial therapy and the development of drug resistance. In response to single agent treatment of bacteria or tumor cells, whether targeted or “cytotoxic”, drug target alterations or, perhaps, drug efflux, can mediate therapeutic resistance. Here lower case letters indicate specific mutations in drug target genes. Conversely, in response to combinatorial therapy, bacteria evolve specific resistance mechanisms to each agent, while mammalian cells evolve resistance to targeted therapeutics, reinforcing alterations that restore target activity as well as mechanisms of multi-drug (target non-specific) resistance.

Figure 2

A diagram showing potential computational solutions revealed by the addition of two drug “signatures”. Combination treatments may reveal signatures representative of one of the component signatures. In this case, the drug combination would be expected to act like one of the parental drugs – merely at a lower dose. Alternatively, the combination signature may be an average of component signatures, in which global genetic dependencies are reduced or homogenized. Finally, a combination signature may deviate completely from component signatures – representing a neomorphic affect achieved by the drug combination.