Mark E. Schurdak

Identification of host genes involved in hepatitis C virus replication by small interfering RNA technology

Hepatitis C virus (HCV) replication is highly dependent on host cell factors. Identification of these host factors not only facilitates understanding of the biology of HCV infection but also enables the discovery of novel targets for anti‐HCV therapy. To identify host genes important for HCV RNA replication, we screened a library of small interfering RNA (siRNA) that targets approximately 4,000 human genes in Huh7‐derived EN5‐3 cells harboring an HCV subgenomic replicon with the nonstructural region NS3‐NS5B from the 1b‐N strain. Nine cellular genes that potentially regulate HCV replication were identified in this screen. Silencing of these genes resulted in inhibition of HCV replication by more than 60% and exhibited minimal toxicity. Knockdown of host gene expression by these siRNAs was confirmed at the RNA level and, in some instances, at the protein level. The level of siRNA silencing of these host genes correlated well with inhibition of HCV. These genes included those that encoded a G‐protein coupled receptor (TBXA2R), a membrane protein (LTβ), an adapter protein (TRAF2), 2 transcription factors (RelA and NFκB2), 2 protein kinases (MKK7 and SNARK), and 2 closely related transporter proteins (SLC12A4 and SLC12A5). Of interest, some of these genes are members of the tumor necrosis factor/lymphotoxin signaling pathway. Conclusion: Findings of this study may provide important information for understanding HCV replication. In addition, these cellular genes may constitute a novel set of targets for HCV antiviral therapy. (HEPATOLOGY 2007.)

Identification of Ras-Related Nuclear Protein, Targeting Protein for Xenopus Kinesin-like Protein 2, and Stearoyl-CoA Desaturase 1 as Promising Cancer Targets from an RNAi-Based Screen

To identify new candidate cancer drug targets, we used RNAi as a tool to functionally evaluate genes that play a role in maintaining human tumor cell survival. We screened a small interfering RNA (siRNA) library directed against approximately 3,700 individual genes to assess the ability of siRNAs to induce cell death in an in vitro cell cytotoxicity assay. We found that siRNAs specifically targeting ras-related nuclear protein (Ran), targeting protein for Xenopus kinesin-like protein 2 (TPX2), and stearoyl-CoA desaturase 1 (SCD1), significantly reduced the survival of multiple human tumor cell lines. Further target validation studies revealed that treatment with Ran and TPX2 siRNAs differentially reduced the survival of activated K-Ras-transformed cells compared with their normal isogenic counterparts in which the mutant K-Ras gene had been disrupted (DKS-8). Knockdown of Ran and TPX2 in activated mutant K-Ras cells selectively induced S-phase arrest or transient G(2)-M arrest phenotypes, respectively, that preceded apoptotic cell death. Given our observations that Ran and TPX2 depletion preferentially reduces the survival of activated K-Ras-transformed cells, these two proteins may serve as useful anticancer targets in tumors expressing the activated K-Ras oncogene.

Survivin depletion preferentially reduces the survival of activated K-Ras-transformed cells

To identify cancer-specific targets, we have conducted a synthetic lethal screen using a small interfering RNA (siRNA) library targeting ∼4,000 individual genes for enhanced killing in the DLD-1 colon carcinoma cell line that expresses an activated copy of the K-Ras oncogene. We found that siRNAs targeting baculoviral inhibitor of apoptosis repeat-containing 5 (survivin) significantly reduced the survival of activated K-Ras-transformed cells compared with its normal isogenic counterpart in which the mutant K-Ras gene had been disrupted (DKS-8). In addition, survivin siRNA induced a transient G2-M arrest and marked polyploidy that was associated with increased caspase-3 activation in the activated K-Ras cells. These results indicate that tumors expressing the activated K-Ras oncogene may be particularly sensitive to inhibitors of the survivin protein. [Mol Cancer Ther 2007;6(1):269–76]

Kinome siRNA-phosphoproteomic screen identifies networks regulating AKT signaling.

To identify regulators of intracellular signaling, we targeted 541 kinases and kinase-related molecules with small interfering RNAs (siRNAs), and determined their effects on signaling with a functional proteomics reverse-phase protein array (RPPA) platform assessing 42 phospho and total proteins. The kinome-wide screen demonstrated a strong inverse correlation between phosphorylation of AKT and mitogen-activated protein kinase (MAPK) with 115 genes that, when targeted by siRNAs, demonstrated opposite effects on MAPK and AKT phosphorylation. Network-based analysis identified the MAPK subnetwork of genes along with p70S6K and FRAP1 as the most prominent targets that increased phosphorylation of AKT, a key regulator of cell survival. The regulatory loops induced by the MAPK pathway are dependent on tuberous sclerosis complex 2 but demonstrate a lesser dependence on p70S6K than the previously identified FRAP1 feedback loop. The siRNA screen also revealed novel bi-directionality in the AKT and GSK3 (Glycogen synthase kinase 3) interaction, whereby genetic ablation of GSK3 significantly blocks AKT phosphorylation, an unexpected observation as GSK3 has only been predicted to be downstream of AKT. This method uncovered novel modulators of AKT phosphorylation and facilitated the mapping of regulatory loops.

An Ultraefficient Affinity-Based High-Throughout Screening Process: Application to Bacterial Cell Wall Biosynthesis Enzyme MurF

The authors describe the discovery of a new class of inhibitors to an essential Streptococcus pneumoniae cell wall biosyn-thesis enzyme, MurF, by a novel affinity screening method. The strategy involved screening very large mixtures of diverse small organic molecules against the protein target on the basis of equilibrium binding, followed by iterative ultrafiltration steps and ligand identification by mass spectrometry. Hits from any affinity-based screening method often can be relatively nonselective ligands, sometimes referred to as “nuisance” or “promiscuous” compounds. Ligands selective in their binding affinity for the MurF target were readily identified through electronic subtraction of an empirically determined subset of promiscuous compounds in the library without subsequent selectivity panels. The complete strategy for discovery and identification of novel specific ligands can be applied to all soluble protein targets and a wide variety of ligand libraries.

RNAi-based screening of the human kinome identifies Akt-cooperating kinases: a new approach to designing efficacious multitargeted kinase inhibitors.

Tumors comprise genetically heterogeneous cell populations, whose growth and survival depend on multiple signaling pathways. This has spurred the development of multitargeted therapies, including small molecules that can inhibit multiple kinases. A major challenge in designing such molecules is to determine which kinases to inhibit in each cancer to maximize efficacy and therapeutic index. We describe an approach to this problem implementing RNA interference technology. In order to identify Akt-cooperating kinases, we screened a library of kinase-directed small interfering RNAs (siRNAs) for enhanced cancer cell killing in the presence of Akt inhibitor A-443654. siRNAs targeting casein kinase I gamma 3 (CSNK1G3) or the inositol polyphosphate multikinase (IPMK) significantly enhanced A-443654-mediated cell killing, and caused decreases in Akt Ser-473 and ribosomal protein S6 phosphorylation. Small molecules targeting CSNK1G3 and/or IPMK in addition to Akt may thus exhibit increased efficacy and have the potential for improved therapeutic index.

Statin-induced mevalonate pathway inhibition attenuates the growth of mesenchymal-like cancer cells that lack functional E-cadherin mediated cell cohesion

The cholesterol reducing drugs, statins, exhibit anti-tumor effects against cancer stem cells and various cancer cell lines, exert potent additivity or synergy with existing chemotherapeutics in animal models of cancer and may reduce cancer incidence and cancer related mortality in humans. However, not all tumor cell lines are sensitive to statins, and clinical trials have demonstrated mixed outcomes regarding statins as anticancer agents. Here, we show that statin-induced reduction in intracellular cholesterol levels correlate with the growth inhibition of cancer cell lines upon statin treatment. Moreover, statin sensitivity segregates with abundant cytosolic vimentin expression and absent cell surface E-cadherin expression, a pattern characteristic of mesenchymal-like cells. Exogenous expression of cell surface E-cadherin converts statin- sensitive cells to a partially resistant state implying that statin resistance is in part dependent on the tumor cells attaining an epithelial phenotype. As metastasizing tumor cells undergo epithelial to mesenchymal transition during the initiation of the metastatic cascade, statin therapy may represent an effective approach to targeting the cells most likely to disseminate.

Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology.

Large-scale generation of human iPSC-derived neural stem cells/early neural progenitor cells and their neuronal differentiation

Induced pluripotent stem cell (iPSC)-based technologies offer an unprecedented opportunity to perform high-throughput screening of novel drugs for neurological and neurodegenerative diseases. Such screenings require a robust and scalable method for generating large numbers of mature, differentiated neuronal cells. Currently available methods based on differentiation of embryoid bodies (EBs) or directed differentiation of adherent culture systems are either expensive or are not scalable. We developed a protocol for large-scale generation of neuronal stem cells (NSCs)/early neural progenitor cells (eNPCs) and their differentiation into neurons. Our scalable protocol allows robust and cost-effective generation of NSCs/eNPCs from iPSCs. Following culture in neurobasal medium supplemented with B27 and BDNF, NSCs/eNPCs differentiate predominantly into vesicular glutamate transporter 1 (VGLUT1) positive neurons. Targeted mass spectrometry analysis demonstrates that iPSC-derived neurons express ligand-gated channels and other synaptic proteins and whole-cell patch-clamp experiments indicate that these channels are functional. The robust and cost-effective differentiation protocol described here for large-scale generation of NSCs/eNPCs and their differentiation into neurons paves the way for automated high-throughput screening of drugs for neurological and neurodegenerative diseases.

Kinase Drug Discovery by Affinity Selection/Mass Spectrometry (ASMS): Application to DNA Damage Checkpoint Kinase Chk1

Kinase enzymes are involved in a vast array of biological processes associated with human disease; therefore, selective kinase inhibition by small molecules and therapeutic antibodies is an area of intense study. The authors show that drug candidates with immediate value for biological preclinical evaluation can be identified directly through ultra-efficient affinity screening of kinase enzymes and random compound mixtures. The screening process comprises sampling and trapping equilibrium binding between candidate ligands and protein in solution, followed by removal of unbound ligands via 3 rounds of ultrafiltration and direct identification of bound ligands by mass spectrometry. Evaluation of significant peaks is facilitated by automated integration and collation of the mass spectral data and import into custom software for analysis. One Chk1-selective ligand found by using this process is presented in detail. The compound is potent in both enzymatic and Chk1-dependent cellular assays, and specific contacts in the Chk1 active site are shown by X-ray crystallography.