Adenosine A2A and beta-2 adrenergic receptor agonists: novel selective and synergistic multiple myeloma targets discovered through systematic combination screening.

The use of combination drug regimens has dramatically improved the clinical outcome for patients with multiple myeloma. However, to date, combination treatments have been limited to approved drugs and a small number of emerging agents. Using a systematic approach to identify synergistic drug combinations, combination high-throughput screening (cHTS) technology, adenosine A2A and ß-2 adrenergic receptor (ß2AR) agonists were shown to be highly synergistic, selective, and novel agents that enhance glucocorticoid activity in B-cell malignancies. Unexpectedly, A2A and ß2AR agonists also synergize with melphalan, lenalidomide, bortezomib, and doxorubicin. An analysis of agonists, in combination with dexamethasone or melphalan in 83 cell lines, reveals substantial activity in multiple myeloma and diffuse large B-cell lymphoma cell lines. Combination effects are also observed with dexamethasone as well as bortezomib, using multiple myeloma patient samples and mouse multiple myeloma xenograft assays. Our results provide compelling evidence in support of development of A2A and ß2AR agonists for use in multi-drug combination therapy for multiple myeloma. Furthermore, use of cHTS for the discovery and evaluation of new targets and combination therapies has the potential to improve cancer treatment paradigms and patient outcomes.

Chemical combinations elucidate pathway interactions and regulation relevant to Hepatitis C replication.

The search for effective Hepatitis C antiviral therapies has recently focused on host sterol metabolism and protein prenylation pathways that indirectly affect viral replication. However, inhibition of the sterol pathway with statin drugs has not yielded consistent results in patients. Here, we present a combination chemical genetic study to explore how the sterol and protein prenylation pathways work together to affect hepatitis C viral replication in a replicon assay. In addition to finding novel targets affecting viral replication, our data suggest that the viral replication is strongly affected by sterol pathway regulation. There is a marked transition from antagonistic to synergistic antiviral effects as the combination targets shift downstream along the sterol pathway. We also show how pathway regulation frustrates potential hepatitis C therapies based on the sterol pathway, and reveal novel synergies that selectively inhibit hepatitis C replication over host toxicity. In particular, combinations targeting the downstream sterol pathway enzymes produced robust and selective synergistic inhibition of hepatitis C replication. Our findings show how combination chemical genetics can reveal critical pathway connections relevant to viral replication, and can identify potential treatments with an increased therapeutic window.

Adenosine A2A receptor agonists and PDE inhibitors: a synergistic multitarget mechanism discovered through systematic combination screening in B-cell malignancies.

Using a combination high-throughput screening technology, multiple classes of drugs and targeted agents were identified that synergize with dexamethasone (Dex) in multiple myeloma (MM) cells. Performing combination screening with these enhancers, we discovered an unexpected synergistic interaction between adenosine receptor agonists and phosphodiesterase (PDE) inhibitors that displays substantial activity in a panel of MM and diffuse large B-cell lymphoma (DLBCL) cell lines and tumor cells from MM patients. We have used selective adenosine receptor agonists, antagonists, and PDE inhibitors as well as small interfering RNAs targeting specific molecular isoforms of these proteins to dissect the molecular mechanism of this synergy. The adenosine A2A receptor and PDE2, 3, 4, and 7 are important for activity. Drug combinations induce cyclic AMP (cAMP) accumulation and up-regulate PDE4B. We also observe rigorous mathematical synergy in 3-way combinations containing A2A agonists, PDE inhibitors, and Dex at multiple concentrations and ratios. Taken together, these data suggest that A2A agonist/PDE inhibitor combinations may be attractive as an adjunctive to clinical glucocorticoid containing regiments for patients with MM or DLBCL and confer benefit in both glucocorticoid-sensitive and -resistant populations.

Therapeutic selectivity and the multi-node drug target.

Drug combinations are an increasingly favored strategy for increasing therapeutic windows for potential drugs, but enthusiasm for this approach is tempered by concerns that therapeutic synergy will too often be mirrored by synergistic toxicity. Here we review our recent experimental results and numerical simulations that establish the context-specificity of synergistic combinations. Thus systematic testing of chemical combinations in cell-based disease models can preferentially discover synergies with beneficial therapeutic selectivity. For an anti-inflammatory combination, we demonstrate how such selective synergy is achieved through differential expression of its targets in cells associated with therapeutic and toxic effects, and validate the combination's therapeutic relevance in animals. The narrower context specificity of synergistic combinations creates many new opportunities for such therapeutically relevant selectivity, and reinforces the realization that the most useful paradigm for a drug target is often a set of biomolecules that cooperate to produce a therapeutic response with reduced side effects.

Synergistic drug combinations tend to improve therapeutically relevant selectivity.

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.

Selective amplification of glucocorticoid anti-inflammatory activity through synergistic multi-target action of a combination drug.

INTRODUCTION: Glucocorticoids are a mainstay of anti-inflammatory therapy, but significant adverse effects ultimately limit their utility. Previous efforts to design glucocorticoid structures with an increased therapeutic window have focused on dissociating anti-inflammatory transcriptional repression from adverse effects primarily driven by transcriptional activation. An alternative to this medicinal chemistry approach is a systems biology based strategy that seeks to amplify selectively the anti-inflammatory activity of very low dose glucocorticoid in immune cells without modulating alternative cellular networks that mediate glucocorticoid toxicity. METHODS: The combination of prednisolone and the antithrombotic drug dipyridamole was profiled using in vitro and in vivo models of anti-inflammatory activity and glucocorticoid-induced adverse effects to demonstrate a dissociated activity profile. RESULTS: The combination synergistically suppresses release of proinflammatory mediators, including tumour necrosis factor-alpha, IL-6, chemokine (C-C motif) ligand 5 (RANTES), matrix metalloproteinase-9, and others, from human peripheral blood mononuclear cells and mouse macrophages. In rat models of acute lipopolysaccharide-induced endotoxemia and delayed-type hypersensitivity, and in chronic models of collagen-induced and adjuvant-induced arthritis, the combination produced anti-inflammatory activity that required only a subtherapeutic dose of prednisolone. The immune-specific amplification of prednisolone anti-inflammatory activity by dipyridamole did not extend to glucocorticoid-mediated adverse effects, including corticosterone suppression or increased expression of tyrosine aminotransferase, in vivo after repeat dosing in rats. After 8 weeks of oral dosing in mice, treatment with the combination did not alter prednisolone-induced reduction in osteocalcin and mid-femur bone density, which are markers of steroid-induced osteoporosis. Additionally, amplification was not observed in the cellular network of corticotroph AtT-20/D16v-F2 cells in vitro, as measured by pro-opiomelanocortin expression and adrenocorticotropic hormone secretion. CONCLUSIONS: These data suggest that the multi-target mechanism of low-dose prednisolone and dipyridamole creates a dissociated activity profile with an increased therapeutic window through cellular network selective amplification of glucocorticoid-mediated anti-inflammatory signaling.

The novel combination of chlorpromazine and pentamidine exerts synergistic antiproliferative effects through dual mitotic action.

Combination therapy has proven successful in treating a wide variety of aggressive human cancers. Historically, combination treatments have been discovered through serendipity or lengthy trials using known anticancer agents with similar indications. We have used combination high-throughput screening to discover the unexpected synergistic combination of an antiparasitic agent, pentamidine, and a phenothiazine antipsychotic, chlorpromazine. This combination, CRx-026, inhibits the growth of tumor cell lines in vivo more effectively than either pentamidine or chlorpromazine alone. Here, we report that CRx-026 exerts its antiproliferative effect through synergistic dual mitotic action. Chlorpromazine is a potent and specific inhibitor of the mitotic kinesin KSP/Eg5 and inhibits tumor cell proliferation through mitotic arrest and accumulation of monopolar spindles. Pentamidine treatment results in chromosomal segregation defects and delayed progression through mitosis, consistent with inhibition of the phosphatase of regenerating liver family of phosphatases. We also show that CRx-026 synergizes in vitro and in vivo with the microtubule-binding agents paclitaxel and vinorelbine. These data support a model where dual action of pentamidine and chlorpromazine in mitosis results in synergistic antitumor effects and show the importance of systematic screening for combinations of targeted agents.

Chemical combination effects predict connectivity in biological systems.

Efforts to construct therapeutically useful models of biological systems require large and diverse sets of data on functional connections between their components. Here we show that cellular responses to combinations of chemicals reveal how their biological targets are connected. Simulations of pathways with pairs of inhibitors at varying doses predict distinct response surface shapes that are reproduced in a yeast experiment, with further support from a larger screen using human tumour cells. The response morphology yields detailed connectivity constraints between nearby targets, and synergy profiles across many combinations show relatedness between targets in the whole network. Constraints from chemical combinations complement genetic studies, because they probe different cellular components and can be applied to disease models that are not amenable to mutagenesis. Chemical probes also offer increased flexibility, as they can be continuously dosed, temporally controlled, and readily combined. After extending this initial study to cover a wider range of combination effects and pathway topologies, chemical combinations may be used to refine network models or to identify novel targets. This response surface methodology may even apply to non-biological systems where responses to targeted perturbations can be measured.

Multicomponent therapeutics for networked systems.

Therapeutic regimens that comprise more than one active ingredient are commonly used in clinical medicine. Despite this, most drug discovery efforts search for drugs that are composed of a single chemical entity. A focus in the early drug discovery process on identifying and optimizing the activity of combinations of molecules can result in the identification of more effective drug regimens. A systems perspective facilitates an understanding of the mechanism of action of such drug combinations.

Systematic discovery of multicomponent therapeutics.

Multicomponent therapies, originating through deliberate mixing of drugs in a clinical setting, through happenstance, and through rational design, have a successful history in a number of areas of medicine, including cancer, infectious diseases, and CNS disorders. We have developed a high-throughput screening method for identifying effective combinations of therapeutic compounds. We report here that systematic screening of combinations of small molecules reveals unexpected interactions between compounds, presumably due to interactions between the pathways on which they act. Through systematic screening of approximately 120,000 different two-component combinations of reference-listed drugs, we identified potential multicomponent therapeutics, including (i) fungistatic and analgesic agents that together generate fungicidal activity in drug-resistant Candida albicans, yet do not significantly affect human cells, (ii) glucocorticoid and antiplatelet agents that together suppress the production of tumor necrosis factor-alpha in human primary peripheral blood mononu-clear cells, and (iii) antipsychotic and antiprotozoal agents that do not exhibit significant antitumor activity alone, yet together prevent the growth of tumors in mice. Systematic combination screening may ultimately be useful for exploring the connectivity of biological pathways and, when performed with reference-listed drugs, may result in the discovery of new combination drug regimens.