High-Throughput siRNA-Based Functional Target Validation

RNAi screen identifies a synthetic lethal interaction between PIM1 overexpression and PLK1 inhibition

PURPOSE

To identify genes whose depletion is detrimental to Pim1-overexpressing prostate cancer cells and to validate this finding in vitro and in vivo.

EXPERIMENTAL DESIGN

RNAi screening was used to identify genes whose depletion is detrimental to Pim1-overexpressing cells. Our finding was validated using shRNA or PLK1-specific inhibitor BI 2536. Xenograft studies were performed using both PLK1-knockdown cells and BI 2536 to investigate the effects of PLK1 inhibition on tumorigenesis in Pim1-overexpressing cells. Finally, PLK1 and PIM1 expression patterns in human prostate tumors were examined by immunohistochemistry using tissue microarrays.

RESULTS

We identified the mitotic regulator polo-like kinase (PLK1) as a gene whose depletion is particularly detrimental to the viability of Pim1-overexpressing prostate cancer. Inhibition of PLK1 by shRNA or BI 2536 in Pim1-overexpressing prostate cancer xenograft models resulted in a dramatic inhibition of tumor progression. Notably, Pim1-overexpressing cells were more prone to mitotic arrest followed by apoptosis due to PLK1 inhibition than control cells. Furthermore, inhibition of PLK1 led to the reduction of MYC protein levels both in vitro and in vivo. Our data also suggest that PIM1 and PLK1 physically interact and PIM1 might phosphorylate PLK1. Finally, PLK1 and PIM1 are frequently co-expressed in human prostate tumors, and co-expression of PLK1 and PIM1 was significantly correlated to higher Gleason grades.

CONCLUSIONS

Our findings demonstrate that PIM1-overexpressing cancer cells are particularly sensitive to PLK1 inhibition, suggesting that PIM1 might be used as a marker for identifying patients who will benefit from PLK1 inhibitor treatment.

Phenolic compounds from maté (Ilex paraguariensis) inhibit adipogenesis in 3T3-L1 preadipocytes

Leaves of Ilex paraguariensis are used to prepare a tea known as maté which is a common beverage in several South American countries. The ethanol extract was fractionated to identify the compounds responsible for the anti-adipogenic activity in 3T3-L1 cells. Extracts of both fresh and dried maté leaves were subjected to column chromatography using molecular permeation to obtain the saponin (20 % yields) and the polyphenol extracts (40 % yields) from the fresh and dried leaves. The phenolic content was determined using high-performance liquid chromatography analysis and the Folin-Ciocalteau method. Also, maté extracts (50 μg/ml to 1,000 μg/ml) did not display citotoxicity using MTT. The polyphenol extract from the dried leaves was the most effective (50 μg/ml) in the inhibition of triglyceride accumulation in 3T3-L1 adipocytes, and rutin (100 μg/ml) likely accounted for a large portion of this activity. Additionally, maté extracts had a modulatory effect on the expression of genes related to the adipogenesis as PPARγ2, leptin, TNF-α and C/EBPα.

Advancing cancer drug discovery towards more agile development of targeted combination therapies

Current drug-discovery strategies are typically 'target-centric' and are based upon high-throughput screening of large chemical libraries against nominated targets and a selection of lead compounds with optimized 'on-target' potency and selectivity profiles. However, high attrition of targeted agents in clinical development suggest that combinations of targeted agents will be most effective in treating solid tumors if the biological networks that permit cancer cells to subvert monotherapies are identified and retargeted. Conventional drug-discovery and development strategies are suboptimal for the rational design and development of novel drug combinations. In this article, we highlight a series of emerging technologies supporting a less reductionist, more agile, drug-discovery and development approach for the rational design, validation, prioritization and clinical development of novel drug combinations.

Applications of high content screening in life science research

Over the last decade, imaging as a detection mode for cell based assays has opened a new world of opportunities to measure "phenotypic endpoints" in both current and developing biological models. These "high content" methods combine multiple measurements of cell physiology, whether it comes from sub-cellular compartments, multicellular structures, or model organisms. The resulting multifaceted data can be used to derive new insights into complex phenomena from cell differentiation to compound pharmacology and toxicity. Exploring the major application areas through review of the growing compendium of literature provides evidence that this technology is having a tangible impact on drug discovery and the life sciences.

Lessons for fragment library design: analysis of output from multiple screening campaigns

Over the past 8 years, we have developed, refined and applied a fragment based discovery approach to a range of protein targets. Here we report computational analyses of various aspects of our fragment library and the results obtained for fragment screening. We reinforce the finding of others that the experimentally observed hit rate for screening fragments can be related to a computationally defined druggability index for the target. In general, the physicochemical properties of the fragment hits display the same profile as the library, as is expected for a truly diverse library which probes the relevant chemical space. An analysis of the fragment hits against various protein classes has shown that the physicochemical properties of the fragments are complementary to the properties of the target binding site. The effectiveness of some fragments appears to be achieved by an appropriate mix of pharmacophore features and enhanced aromaticity, with hydrophobic interactions playing an important role. The analysis emphasizes that it is possible to identify small fragments that are specific for different binding sites. To conclude, we discuss how the results could inform further development and improvement of our fragment library.

Median absolute deviation to improve hit selection for genome-scale RNAi screens

High-throughput screening (HTS) of large-scale RNA interference (RNAi) libraries has become an increasingly popular method of functional genomics in recent years. Cell-based assays used for RNAi screening often produce small dynamic ranges and significant variability because of the combination of cellular heterogeneity, transfection efficiency, and the intrinsic nature of the genes being targeted. These properties make reliable hit selection in the RNAi screen a difficult task. The use of robust methods based on median and median absolute deviation (MAD) has been suggested to improve hit selection in such cases, but mean and standard deviation (SD)-based methods are still predominantly used in many RNAi HTS. In an experimental approach to compare these 2 methods, a genome-scale small interfering RNA (siRNA) screen was performed, in which the identification of novel targets increasing the therapeutic index of the chemotherapeutic agent mitomycin C (MMC) was sought. MAD values were resistant to the presence of outliers, and the hits selected by the MAD-based method included all the hits that would be selected by SD-based method as well as a significant number of additional hits. When retested in triplicate, a similar percentage of these siRNAs were shown to genuinely sensitize cells to MMC compared with the hits shared between SD- and MAD-based methods. Confirmed hits were enriched with the genes involved in the DNA damage response and cell cycle regulation, validating the overall hit selection strategy. Finally, computer simulations showed the superiority and generality of the MAD-based method in various RNAi HTS data models. In conclusion, the authors demonstrate that the MAD-based hit selection method rescued physiologically relevant false negatives that would have been missed in the SD-based method, and they believe it to be the desirable 1st-choice hit selection method for RNAi screen results.

An Efficient and Fully Automated High-Throughput Transfection Method for Genome-Scale siRNA Screens

RNA interference (RNAi), combined with the availability of genome sequences, provides an unprecedented opportunity for the massive and parallel investigations of gene function. Small interfering RNA (siRNA) represents a popular and quick approach of RNAi for in vitro loss-of-function genetic screens. Efficient transfection of siRNA is critical for unambiguous interpretation of screen results and thus overall success of any siRNA screen. A high-throughput, lipid-based transfection method for siRNA was developed that can process eighty 384-well microplates in triplicate (for a total of 30,720 unique transfections) in 8 h. Transfection throughput was limited only by the speed of robotics, whereas the cost of screening was reduced. As a proof of principle, a genome-scale screen with a library of 22,108 siRNAs was performed to identify the genes sensitizing cells to mitomycin C at concentrations of 0, 20, and 60 nM. Transfection efficiency, performances of control siRNAs, and other quality metrics were monitored and demonstrated that the new, optimized transfection protocol produced high-quality results throughout the screen. ( Journal of Biomolecular Screening 2008:142-148)

Genome-scale microRNA and small interfering RNA screens identify small RNA modulators of TRAIL-induced apoptosis pathway

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) binds to death receptors 4/5 and selectively induces caspase-dependent apoptosis. The RNA interference screening approach has led to the discovery and characterization of several TRAIL pathway components in human cells. Here, libraries of synthetic small interfering RNA (siRNA) and microRNAs (miRNA) were used to probe the TRAIL pathway. In addition to known genes, siRNAs targeting CDK4, PTGS1, ALG2, CLCN3, IRAK4, and MAP3K8 altered TRAIL-induced caspase-3 activation responses. Introduction of the miRNAs let-7c, mir-10a, mir-144, mir-150, mir-155, and mir-193 also affected the activation of the caspase cascade. Putative targets of these endogenous miRNAs included genes encoding death receptors, caspases, and other apoptosis-related genes. Among the novel genes revealed in the screen, CDK4 was selected for further characterization. CDK4 was the only member of the cyclin-dependent kinase gene family that bore a unique function in apoptotic signal transduction.

Predicting protein druggability

The ability to predict whether a particular protein can bind with high affinity and specificity to small, drug-like compounds based solely on its 3D structure has been a longstanding goal of structural biologists and computational scientists. The promise is that an accurate prediction of protein druggability can capitalize on the huge investments already made in structural genomics initiatives by identifying highly druggable proteins and using this information in target identification and validation campaigns. Here we discuss the potential utility of tools that characterize protein targets and describe strategies for the optimal integration of protein druggability data with bioinformatic approaches to target selection.

Investigating Wnt signaling: a chemogenomic safari

Chemical genomics is a powerful method to complement more traditional genetic techniques (i.e. knockout mice, siRNA) for the dissection of complex signaling networks. Wnt signaling in mammals is a complex and crucial regulator of diverse functions. The Wnt-beta-catenin pathway initiates a signaling cascade that is crucial in both normal development and the initiation and progression of cancer. A key step in Wnt activation of target genes is the nuclear translocation of beta-catenin and the formation of a complex between beta-catenin and members of the T-cell factor (TCF) family of transcription factors. Using a forward chemical genomics strategy, we identified ICG-001, a selective inhibitor of a subset of Wnt-beta-catenin-driven gene expression. This chemogenomic tool enables us to dissect this complex signaling network and to better understand the role of Wnt signaling in both normal and pathophysiological settings.

High-throughput RNAi screening in vitro: from cell lines to primary cells

Small interfering RNAs (siRNAs) are being used to induce sequence-specific gene silencing in cultured cells to study mammalian gene function. Libraries of siRNAs targeting entire human gene classes can be used to identify genes with specific cellular functions. Here we describe high-throughput siRNA delivery methods to facilitate siRNA library screening experiments with both immortalized and primary cells. We adapted chemical reverse transfection for immortalized adherent cell lines in a 96-well format. The method is fast, robust, and exceptionally effective for many cell types. For primary cells and immortalized cells that are recalcitrant to lipofection-based methods, we developed electropermeabilization (electroporation) conditions that facilitate siRNA delivery to a broad range of cell types, including primary human T-cells, hMSC, NHA, NDHF-Neo, HUVEC, DI TNC1, RPTEC, PC12, and K562 cells. To enable high-throughput electropermeabilization of primary cells, we developed a novel 96-well electroporation device that provides highly efficient and reproducible delivery of siRNAs. The combination of high-throughput chemical reverse transfection and electroporation makes it possible to deliver libraries of siRNAs to virtually any cell type, enabling gene function analysis and discovery on a genome scale.

Biomarker discovery and validation: technologies and integrative approaches

The emerging field of biomarkers has applications in the diagnosis, staging, prognosis and monitoring of disease progression, as well as in the monitoring of clinical responses to a therapeutic intervention and the development and delivery of personalized treatments to reduce attrition in clinical trials. Moreover, biomarkers have a positive impact on health economics. The word "biomarker" has been used extensively across therapeutic areas and many disciplines, and its nature takes into consideration clinical, physiological, biochemical, developmental, morphological and molecular measures. In drug trials, biomarkers have been proposed for use in efficacy determination and patient population stratification, in deducing pharmacokinetic-pharmacodynamic relationships and in safety monitoring. The interfacing and integration of different technologies for data collection and analysis are pivotal to biomarker identification, characterization, validation and application. "Integrative functional informatics" represents a novel direction in such technology integration.

Genome scale cytometry: High content analysis for high throughput RNAi phenotype profiling

The combination of RNAi-mediated knockdown of gene expression and high content screening (HCS) allows the determination of the contribution of single genes to a variety of cellular effects varying between growth and survival to subtle alterations in cellular morphology and phenotype. This review examines the current status of research in combining these tools.:

Oncology studies using siRNA libraries: the dawn of RNAi-based genomics

High-throughput, human cell-based applications of RNA-mediated interference (RNAi) have emerged in recent years as perhaps the most powerful of a 'second wave' of functional genomics technologies. The available reagents and methodologies for RNAi screening studies now enable a wide range of different scopes and scales of investigation, from single-parameter assays applied to focused subsets of genes, to comprehensive genome-wide surveys based on rich, multiparameter readouts. As such, RNAi-based screens are offering important new avenues for the discovery and validation of novel therapeutic targets for several disease areas, including oncology. By enabling a 'clean' determination of gene function, that is the creation of direct causal links between gene and phenotype in human cells, RNAi investigations promise levels of pathophysiological relevance, efficiency, and range of applicability never before possible on this scale. The field of oncology, with its many assays using readily transfectable cell lines, has offered particularly fertile ground for showcasing the potential of RNAi-based genomics. However, like any other technology before it, RNAi is not without its own challenges, limitations, and caveats. Many of these issues stem directly from the choice of silencing reagent to be used in such studies, and the design of the overall screening strategy. Here, we discuss the basic design issues, potential advantages, and technical challenges of large-scale RNAi screens based on the use of chemically synthesized siRNA libraries.

Functional informatics: convergence and integration of automation and bioinformatics

The biopharmaceutical industry is currently being presented with opportunities to improve research and business efficiency via automation and the integration of various systems. In the examples discussed, industrial high-throughput screening systems are integrated with functional tools and bioinformatics to facilitate target and biomarker identification and validation. These integrative functional approaches generate value-added opportunities by leveraging available automation and information technologies into new applications that are broadly applicable to different types of projects, and by improving the overall research and development and business efficiency via the integration of various systems.