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Combinatorial drug screening identifies compensatory pathway interactions and adaptive resistance mechanisms.

ABSTRACT: Constitutively activated signaling molecules are often the primary drivers of malignancy, and are favored targets for therapeutic intervention. However, the effectiveness of targeted inhibition of cell signaling can be blunted by compensatory signaling which generates adaptive resistance mechanisms and reduces therapeutic responses. Therefore, it is important to identify and target these compensatory pathways with combinations of targeted agents to achieve durable clinical benefit. In this report, we demonstrate the use of high-throughput combinatorial drug screening as a discovery tool to identify compensatory pathways that generate resistance to the cytotoxic effects of targeted therapy. We screened 420 drug combinations in 14 different cell lines representing three cancer lineages, and assessed the ability of each combination to cause synergistic cytotoxicity. Drug substitution studies were used to validate the functionally important drug targets. Of the 84 combinations that caused robust synergy in multiple cell lines, none were synergistic in more than half of the lines tested, and we observed no pattern of lineage specificity in the observed synergies. This reflects the plasticity of cell signaling networks, even among cell lines of the same tissue of origin. Mechanistic analysis of one novel synergistic combination identified in the screen, the multi-kinase inhibitor Ro31-8220 and lapatinib, demonstrated compensatory crosstalk between the p70S6 kinase and EGF receptor pathways. In addition, we identified BAD as a node of convergence between these two pathways that may be playing a role in the enhanced apoptosis observed upon combination treatment.

SUBMITTER: Axelrod M

PROVIDER: S-EPMC3720609 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Combinatorial drug screening identifies compensatory pathway interactions and adaptive resistance mechanisms.

Axelrod Mark M Gordon Vicki L VL Conaway Mark M Tarcsafalvi Adel A Neitzke Daniel J DJ Gioeli Daniel D Weber Michael J MJ

Oncotarget 20130401 4

Constitutively activated signaling molecules are often the primary drivers of malignancy, and are favored targets for therapeutic intervention. However, the effectiveness of targeted inhibition of cell signaling can be blunted by compensatory signaling which generates adaptive resistance mechanisms and reduces therapeutic responses. Therefore, it is important to identify and target these compensatory pathways with combinations of targeted agents to achieve durable clinical benefit. In this repor ...[more]

PMID: 23599172

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Project description:The adaptive landscape analogy has found practical use in recent years, as many have explored how their understanding can inform therapeutic strategies that subvert the evolution of drug resistance. A major barrier to applications of these concepts is a lack of detail concerning how the environment affects adaptive landscape topography, and consequently, the outcome of drug treatment. Here we combine empirical data, evolutionary theory, and computer simulations towards dissecting adaptive landscape by environment interactions for the evolution of drug resistance in two dimensions-drug concentration and drug type. We do so by studying the resistance mediated by Plasmodium falciparum dihydrofolate reductase (DHFR) to two related inhibitors-pyrimethamine and cycloguanil-across a breadth of drug concentrations. We first examine whether the adaptive landscapes for the two drugs are consistent with common definitions of cross-resistance. We then reconstruct all accessible pathways across the landscape, observing how their structure changes with drug environment. We offer a mechanism for non-linearity in the topography of accessible pathways by calculating of the interaction between mutation effects and drug environment, which reveals rampant patterns of epistasis. We then simulate evolution in several different drug environments to observe how these individual mutation effects (and patterns of epistasis) influence paths taken at evolutionary "forks in the road" that dictate adaptive dynamics in silico. In doing so, we reveal how classic metrics like the IC50 and minimal inhibitory concentration (MIC) are dubious proxies for understanding how evolution will occur across drug environments. We also consider how the findings reveal ambiguities in the cross-resistance concept, as subtle differences in adaptive landscape topography between otherwise equivalent drugs can drive drastically different evolutionary outcomes. Summarizing, we discuss the results with regards to their basic contribution to the study of empirical adaptive landscapes, and in terms of how they inform new models for the evolution of drug resistance.

Dataset Information

Combinatorial drug screening identifies compensatory pathway interactions and adaptive resistance mechanisms.

Publications

Combinatorial drug screening identifies compensatory pathway interactions and adaptive resistance mechanisms.

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