Frederick J. King

Genome-scale functional profiling of the mammalian AP-1 signaling pathway

Large-scale functional genomics approaches are fundamental to the characterization of mammalian transcriptomes annotated by genome sequencing projects. Although current high-throughput strategies systematically survey either transcriptional or biochemical networks, analogous genome-scale investigations that analyze gene function in mammalian cells have yet to be fully realized. Through transient overexpression analysis, we describe the parallel interrogation of ≈20,000 sequence annotated genes in cancer-related signaling pathways. For experimental validation of these genome data, we apply an integrative strategy to characterize previously unreported effectors of activator protein-1 (AP-1) mediated growth and mitogenic response pathways. These studies identify the ADP-ribosylation factor GTPase-activating protein Centaurin α1 and a Tudor domain-containing hypothetical protein as putative AP-1 regulatory oncogenes. These results provide insight into the composition of the AP-1 signaling machinery and validate this approach as a tractable platform for genome-wide functional analysis.

Large-Scale Annotation of Small-Molecule Libraries Using Public Databases

While many large publicly accessible databases provide excellent annotation for biological macromolecules, the same is not true for small chemical compounds. Commercial data sources also fail to encompass an annotation interface for large numbers of compounds and tend to be cost prohibitive to be widely available to biomedical researchers. Therefore, using annotation information for the selection of lead compounds from a modern day high-throughput screening (HTS) campaign presently occurs only under a very limited scale. The recent rapid expansion of the NIH PubChem database provides an opportunity to link existing biological databases with compound catalogs and provides relevant information that potentially could improve the information garnered from large-scale screening efforts. Using the 2.5 million compound collection at the Genomics Institute of the Novartis Research Foundation (GNF) as a model, we determined that approximately 4% of the library contained compounds with potential annotation in such databases as PubChem and the World Drug Index (WDI) as well as related databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and ChemIDplus. Furthermore, the exact structure match analysis showed 32% of GNF compounds can be linked to third party databases via PubChem. We also showed annotations such as MeSH (medical subject headings) terms can be applied to in-house HTS databases in identifying signature biological inhibition profiles of interest as well as expediting the assay validation process. The automated annotation of thousands of screening hits in batch is becoming feasible and has the potential to play an essential role in the hit-to-lead decision making process.

Learning from the Data: Mining of Large High-Throughput Screening Databases

High-throughput screening (HTS) campaigns in pharmaceutical companies have accumulated a large amount of data for several million compounds over a couple of hundred assays. Despite the general awareness that rich information is hidden inside the vast amount of data, little has been reported for a systematic data mining method that can reliably extract relevant knowledge of interest for chemists and biologists. We developed a data mining approach based on an algorithm called ontology-based pattern identification (OPI) and applied it to our in-house HTS database. We identified nearly 1500 scaffold families with statistically significant structure-HTS activity profile relationships. Among them, dozens of scaffolds were characterized as leading to artifactual results stemming from the screening technology employed, such as assay format and/or readout. Four types of compound scaffolds can be characterized based on this data mining effort: tumor cytotoxic, general toxic, potential reporter gene assay artifact, and target family specific. The OPI-based data mining approach can reliably identify compounds that are not only structurally similar but also share statistically significant biological activity profiles. Statistical tests such as Kruskal-Wallis test and analysis of variance (ANOVA) can then be applied to the discovered scaffolds for effective assignment of relevant biological information. The scaffolds identified by our HTS data mining efforts are an invaluable resource for designing SAR-robust diversity libraries, generating in silico biological annotations of compounds on a scaffold basis, and providing novel target family specific scaffolds for focused compound library design.

Seeing the light: luminescent reporter gene assays.

The luminescent reporter gene assay (LRGA) is arguably the most prominent type of reporter gene assay used in biomolecular and pharmaceutical development laboratories. Part of this popularity is due to the high signal associated with luciferases, the foundation of this technology. This feature makes them ideally suited for high throughput screening applications where potentially millions of chemical compounds can be analyzed in a given assay. Recent technical advancements that enhance signal stability of the luciferases along with development and commercialization of multiple forms of luciferases, their respective substrates, and improvements in expression vectors for reporter gene assay (RGA) applications have broadened their use. While the practical challenges related to the application of luminescent technology in a laboratory setting have been overcome, there remains much to do in laying a systematic approach towards the construction of RGAs, which are essential to the elucidation of the basic biology for genes of interest. This mini-review aims at giving a birds-eye view of the available luciferases, substrates and other luminescent technologies available and provides a general blueprint as well as practical considerations for constructing and interfacing RGAs with chemical biology and functional genomics for the elucidation of fundamental biological questions and for biomedical research.

Chemical and biological properties of frequent screening hits.

High-throughput screening (HTS) has become an important technology for the drug discovery process. It has been noted that certain compounds frequently appear as hits in many screening campaigns. By mining an HTS database covering large chemical space and diverse biological functions, we identified many novel chemical features, as well as several biological processes that were associated with a significant portion of frequent hits. However, we also noted that several marketed drugs also contained characteristics that commonly were associated with frequent hits. This observation suggested that current generally employed strategies for triaging compounds may result in the removal of compounds with desirable properties. Therefore, we developed a novel strategy that overlaid chemical scaffolds and biological processes, along with empirical hit frequency data, in order to provide a more functional frequent hit triage strategy; the risk of removing biologically relevant frequent hits was reduced compared to the typical empirical hit frequency-based filtering strategy.

Pathway Reporter Assays Reveal Small Molecule Mechanisms of Action

Cell-based, phenotypic screening of small molecules often identifies compounds with provocative biological properties. However, determining the cellular target(s) and/or mechanism of action (MoA) of lead compounds remains an extremely challenging and time-consuming exercise. To provide insights into a compounds cellular action and greatly reduce the time required for MoA determination, we have developed a screening platform consisting of an extensive series of reporter gene assays (RGAs). A collection of > 11,000 compounds of known MoA (e.g., World Drug Index entries) were screened against the entire panel. The output provided evidence that an RGA signature could be ascribed to numerous, biologically diverse MoAs. The reference database generated suggested novel biological activity for particular compounds. For example, the profiling data led to the prediction that the cellular target of the natural product terprenin was dihydroorotate dehydrogenase (DHODH), which was confirmed experimentally. The screening methodology developed for this endeavor renders it amenable to the future examination of compounds with unknown MoA, in an automated, inexpensive, and time-efficient manner.

Multiplexed Reporter Gene Assays: Monitoring the Cell Viability and the Compound Kinetics on Luciferase Activity

High-throughput screening assays with multiple readouts enable one to monitor multiple assay parameters. By capturing as much information about the underlying biology as possible, the detection of true actives can be improved. This report describes an extension to standard luciferase reporter gene assays that enables multiple parameters to be monitored from each sample. The report describes multiplexing luciferase assays with an orthogonal readout monitoring cell viability using reduction of resazurin. In addition, this technical note shows that by using the luciferin substrate in live cells, an assay time course can be recorded. This enables the identification of nonactive or unspecific compounds that act by inhibiting luciferase, as well as compounds altering gene expression or cell growth.

Profiling the kinome for drug discovery

The human kinome is made up of 518 distinctive serine/threonine and tyrosine kinases, which are key components of virtually every mammalian signal transduction pathway. Consequently, kinases provide a compelling target family for the development of small molecule inhibitors, which could be used as tools to delineate the mechanism of action for biological processes and potentially be used as therapeutics to treat human diseases such as cancer. A myriad of recent technological advances have accelerated our understanding of kinome function, its relationship to tumorigenic development, and have contributed to the progression of small molecule kinase inhibitors into the clinic. Essential to the continued growth of the field are informatics tools that can assist in interpreting disparate and voluminous data sets and correctly guide decision making processes. These advances are expected to have a dramatic impact on kinase drug development and clinical diagnoses and treatment in the near future.:

Abstract B42: Combinatorial CDK4/6 and ALK inhibition demonstrates on-target synergy against neuroblastoma

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA BACKGROUND: Activated ALK by mutation or amplification is a validated therapeutic target in neuroblastoma, and identifying therapeutic strategies to overcome primary resistance to direct ALK kinase inhibition will be critical to improve clinical responses. We hypothesized that simultaneous targeting of ALK and additional oncogenic networks would improve efficacy. METHODS: We performed a synergy screen combining molecularly targeted compounds (n=14) and standard-of-care chemotherapy agents (n=8) in extensively characterized human neuroblastoma cell lines (n=14). We investigated the combination of LDK378 and LEE011 on in vitro proliferation, cell cycle, viability, caspase activation, and the Cyclin D/CDK4/CDK6/RB and pALK signaling networks in neuroblastoma-derived cell lines with representative ALK status. Transport inhibitor studies were performed in Caco2 cells. We performed in vivo trials in neuroblastoma CB17 xenograft models comparing LDK378 alone, LEE011 alone, and the combination of LDK378 and LEE011, with plasma and tumor pharmacokinetics to evaluate for drug-drug interactions. RESULTS: Pairwise combination screening for in vitro cell viability identified synergistic interactions of LDK378, an ALK inhibitor, with LEE011, a CDK4 and CDK6 inhibitor. In mutant and wild-type ALK cell lines there was moderate to strong synergy with combination indices of 0.2 - 0.8 at clinically relevant high effect sizes with the fraction of cells affected ≥ 0.8. Compared to either drug alone, combination LEE011 and LDK378 increased dose dependent abrogation of pALK and pRb, inhibition of proliferation, apoptosis and decreased cell viability. LDK378 did not show significant cellular accumulation after P-gp, BCRP, and MRP2 inhibition or after LEE011 1uM and 10uM. LEE011 showed only modest accumulation with MRP2 inhibition, but not after BCRP or P-gp inhibition. In NB1691 (ALK wild-type) and SHSY5Y (ALK-F1174L, resistant mutation) neuroblastoma xenografts, combination therapy significantly prolonged survival compared to either drug alone (P<0.0001). In SHSY5Y xenografts, combination therapy achieved complete regressions using murine doses that achieved plasma drug exposures comparable to the adult recommended doses for LEE011 and LDK378. Combination therapy increased tumor LEE011 and LDK378 maximum concentration (Cmax) and area under curve (AUC) 2-3 fold over monotherapy, but plasma concentrations were unaltered. CONCLUSION: Dual ALK and CDK4/6 inhibition in neuroblastoma models demonstrates potent on-target in vitro synergy and in vivo activity with augmented abrogation of respective molecular targets, resulting in inhibition of proliferation and cell death. While mechanisms for altered intratumoral drug distribution require further investigation, these data support the development of a combination ALK and CDK4/6 inhibitor clinical trial with eligibility not restricted to cases with somatic ALK mutations. Citation Format: Andrew C. Wood, Kateryna Krytska, Hannah Ryles, Renata Sano, Nanxin Li, Frederick King, Timothy Smith, Tove Tuntland, Sunkyu Kim, Giordano Caponigro, You Qun He, Harris Jennifer, Yael Mosse. Combination CDK4/6 and ALK inhibition demonstrates on-target synergy against neuroblastoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1000. doi:10.1158/1538-7445.AM2014-1000