Gene Expression Ratios Lead to Accurate and Translatable Predictors of DR5 Agonism across Multiple Tumor Lineages.

Death Receptor 5 (DR5) agonists demonstrate anti-tumor activity in preclinical models but have yet to demonstrate robust clinical responses. A key limitation may be the lack of patient selection strategies to identify those most likely to respond to treatment. To overcome this limitation, we screened a DR5 agonist Nanobody across >600 cell lines representing 21 tumor lineages and assessed molecular features associated with response. High expression of DR5 and Casp8 were significantly associated with sensitivity, but their expression thresholds were difficult to translate due to low dynamic ranges. To address the translational challenge of establishing thresholds of gene expression, we developed a classifier based on ratios of genes that predicted response across lineages. The ratio classifier outperformed the DR5+Casp8 classifier, as well as standard approaches for feature selection and classification using genes, instead of ratios. This classifier was independently validated using 11 primary patient-derived pancreatic xenograft models showing perfect predictions as well as a striking linearity between prediction probability and anti-tumor response. A network analysis of the genes in the ratio classifier captured important biological relationships mediating drug response, specifically identifying key positive and negative regulators of DR5 mediated apoptosis, including DR5, CASP8, BID, cFLIP, XIAP and PEA15. Importantly, the ratio classifier shows translatability across gene expression platforms (from Affymetrix microarrays to RNA-seq) and across model systems (in vitro to in vivo). Our approach of using gene expression ratios presents a robust and novel method for constructing translatable biomarkers of compound response, which can also probe the underlying biology of treatment response.

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.

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.

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.

Second-generation shRNA libraries covering the mouse and human genomes.

Loss-of-function phenotypes often hold the key to understanding the connections and biological functions of biochemical pathways. We and others previously constructed libraries of short hairpin RNAs that allow systematic analysis of RNA interference-induced phenotypes in mammalian cells. Here we report the construction and validation of second-generation short hairpin RNA expression libraries designed using an increased knowledge of RNA interference biochemistry. These constructs include silencing triggers designed to mimic a natural microRNA primary transcript, and each target sequence was selected on the basis of thermodynamic criteria for optimal small RNA performance. Biochemical and phenotypic assays indicate that the new libraries are substantially improved over first-generation reagents. We generated large-scale-arrayed, sequence-verified libraries comprising more than 140,000 second-generation short hairpin RNA expression plasmids, covering a substantial fraction of all predicted genes in the human and mouse genomes. These libraries are available to the scientific community.

A lentiviral microRNA-based system for single-copy polymerase II-regulated RNA interference in mammalian cells.

The advent of RNA interference has led to the ability to interfere with gene expression and greatly expanded our ability to perform genetic screens in mammalian cells. The expression of short hairpin RNA (shRNA) from polymerase III promoters can be encoded in transgenes and used to produce small interfering RNAs that down-regulate specific genes. In this study, we show that polymerase II-transcribed shRNAs display very efficient knockdown of gene expression when the shRNA is embedded in a microRNA context. Importantly, our shRNA expression system [called PRIME (potent RNA interference using microRNA expression) vectors] allows for the multicistronic cotranscription of a reporter gene, thereby facilitating the tracking of shRNA production in individual cells. Based on this system, we developed a series of lentiviral vectors that display tetracycline-responsive knockdown of gene expression at single copy. The high penetrance of these vectors will facilitate genomewide loss-of-function screens and is an important step toward using bar-coding strategies to follow loss of specific sequences in complex populations.