High-throughput RNA Interference Screening Research Articles

The host interactome of influenza virus presents new potential targets for antiviral drugs

SUMMARYIncreasing antiviral drug resistance is a major concern for treating influenza, especially in a pandemic setting when the availability of a protective vaccine is uncertain. Resistance is often an issue with drugs directed at viral proteins and for small RNA viruses; there are also a limited number of viral proteins that are amenable to inhibition by a small molecule. A new approach that is gaining support is that cellular proteins, which facilitate virus replication, may be used as alternative targets. Whereas drugs directed at viral proteins tend to be virus‐specific, drugs directed at host targets have the potential to have broad‐spectrum antiviral activity as many viruses may share a dependency on that host function. For influenza virus, we have very limited knowledge of which cellular factors are involved in virus replication, let alone which of these have suitable properties to serve as drug targets. Through the use of high‐throughput RNA interference screens, several studies have addressed this gap in our knowledge. The resulting datasets provide new insight into host pathways that are involved in the influenza virus replication cycle and identify specific host factors in these pathways that may serve as potential targets for future antiviral drug development. Copyright © 2011 John Wiley & Sons, Ltd.

Functional Viability Profiles of Breast Cancer

The design of targeted therapeutic strategies for cancer has largely been driven by the identification of tumor-specific genetic changes. However, the large number of genetic alterations present in tumor cells means that it is difficult to discriminate between genes that are critical for maintaining the disease state and those that are merely coincidental. Even when critical genes can be identified, directly targeting these is often challenging, meaning that alternative strategies such as exploiting synthetic lethality may be beneficial. To address these issues, we have carried out a functional genetic screen in >30 commonly used models of breast cancer to identify genes critical to the growth of specific breast cancer subtypes. In particular, we describe potential new therapeutic targets for PTEN-mutated cancers and for estrogen receptor-positive breast cancers. We also show that large-scale functional profiling allows the classification of breast cancers into subgroups distinct from established subtypes. Despite the wealth of molecular profiling data that describe breast tumors and breast tumor cell models, our understanding of the fundamental genetic dependencies in this disease is relatively poor. Using high-throughput RNA interference screening of a series of pharmacologically tractable genes, we have generated comprehensive functional viability profiles for a wide panel of commonly used breast tumor cell models. Analysis of these profiles identifies a series of novel genetic dependencies, including that of PTEN-null breast tumor cells upon mitotic checkpoint kinases, and provides a framework upon which additional dependencies and candidate therapeutic targets may be identified.

Highlights of This Issue

Brain metastasis from breast cancer is a growing problem, due in part to improved therapies for metastatic disease and the inability of many drugs to cross the blood-brain barrier. McGowan and colleagues investigated the role of cancer stem-like cells and a potential regulator, Notch, on the formation of brain metastases by using a γ-secretase inhibitor and specific Notch1 silencing. Cells with a reduced stem-like phenotype formed fewer metastases. Notch1 shRNA or DAPT treatment reduced the proportion of stemlike cells and the number of metastases formed in vivo. These data suggest that the cancer stem cell phenotype contributes to the development of brain metastases from breast cancer and that this may arise in part from increased Notch activity.Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic malignancy with ineffective treatments and dismal survival rates. To expedite biological testing of putative PDAC metastasis genes, Muniz and coworkers developed a new mouse tumor model that uses intracardiac injections of pancreatic cancer cells and bioluminescence imaging to track tumor dissemination and development in vivo. The model was validated by using the p14ARF tumor suppressor, which acted independently of p53 to inhibit PDAC tumor cell invasiveness and colonization in vivo. These findings establish a unique platform for rapidly identifying genetic events controlling pancreatic cancer metastasis, defining new PDAC targets, and testing innovative therapies.In this study, Shultz and colleagues explore the molecular mechanisms that regulate caspase 9 RNA splicing as well as the biological relevance of this mechanism in the treatment of non–small cell lung cancer (NSCLC). Specifically, a novel intronic splicing enhancer, C9-I6/ISE, was identified and shown to interact with the RNA trans-factor, SRSF1. Furthermore, the direct manipulation of caspase 9 RNA splicing played a key role in the chemotherapy sensitivity of NSCLC cells to individual agents and the synergism of the clinically relevant agents, daunorubicin and erlotinib. Hence, this molecular splicing mechanism is a relevant therapeutic target for NSCLC.Medulloblastoma is the most common malignant brain tumor in children and is associated with poor prognosis in high-risk patients. In this study, Guerreiro and colleagues have used a high-throughput RNA interference screen to identify novel molecular targets in medulloblastoma cell lines. Our results show for the first time that the phosphoinositide 3-kinase (PI3K) isoform p110γ plays a crucial role in the proliferation and chemoresistance of medulloblastoma cells. In addition, p110γ was found to be overexpressed in primary medulloblastoma samples and cell lines. The PI3K isoform p110γ, therefore, represents a potential novel drug target in medulloblastoma.

Synergistic Effect between Erlotinib and MEK Inhibitors in KRAS Wild-Type Human Pancreatic Cancer Cells

The combination of erlotinib and gemcitabine has shown a small but statistically significant survival advantage when compared with gemcitabine alone in patients with advanced pancreatic cancer. However, the overall survival rate with the erlotinib and gemcitabine combination is still low. In this study, we sought to identify gene targets that, when inhibited, would enhance the activity of epidermal growth factor receptor (EGFR)-targeted therapies in pancreatic cancer cells. A high-throughput RNA interference (RNAi) screen was carried out to identify candidate genes. Selected gene hits were further confirmed and mechanisms of action were further investigated using various assays. Six gene hits from siRNA screening were confirmed to significantly sensitize BxPC-3 pancreatic cancer cells to erlotinib. One of the hits, mitogen-activated protein kinase (MAPK) 1, was selected for further mechanistic studies. Combination treatments of erlotinib and two MAP kinase kinase (MEK) inhibitors, RDEA119 and AZD6244, showed significant synergistic effect for both combinations (RDEA119-erlotinib and AZD6244-erlotinib) compared with the corresponding single drug treatments in pancreatic cancer cell lines with wild-type KRAS (BxPC-3 and Hs 700T) but not in cell lines with mutant KRAS (MIA PaCa-2 and PANC-1). The enhanced antitumor activity of the combination treatment was further verified in the BxPC-3 and MIA PaCa-2 mouse xenograft model. Examination of the MAPK signaling pathway by Western blotting indicated effective inhibition of the EGFR signaling by the drug combination in KRAS wild-type cells but not in KRAS mutant cells. Overall, our results suggest that combination therapy of an EGFR and MEK inhibitors may have enhanced efficacy in patients with pancreatic cancer.

High-Throughput RNAi Screening Reveals Novel Regulators of Telomerase

Telomerase is considered an attractive anticancer target on the basis of its common and specific activation in most human cancers. While direct telomerase inhibition is being explored as a therapeutic strategy, alternative strategies to target regulators of telomerase that could disrupt telomere maintenance and cancer cell proliferation are not yet available. Here, we report the findings of a high-throughput functional RNA interference screen to globally profile the contribution of kinases to telomerase activity (TA). This analysis identified a number of novel telomerase modulators, including ERK8 kinase, whose inhibition reduces TA and elicited characteristics of telomere dysfunction. Given that kinases represent attractive drug targets, we addressed the therapeutic implications of our findings, such as demonstrating how limiting TA via kinase blockade could sensitize cells to inhibition of the telomere-associated protein tankyrase. Taken together, our findings suggest novel combinatorial approaches to targeting telomere maintenance as a strategy for cancer therapy.

Abstract 4984: Association of PTEN and p16 mutational status with MITF expression may provide a novel context for a phenotype switch in melanoma

Abstract For the last decade, array-based genomic screening has significantly advanced our understanding of genes involved in cancer development and progression. Moreover, genes identified in those screenings have subsequently been the focus of drug development efforts, ultimately leading to clinical trials. However, the efficient translation of cancer genomics results into the development of more effective therapeutics has been limited in part by the need for robust, high-throughput, functional validation of genes and pathways of interest in well-defined model systems. In order to identify new therapeutic targets in melanoma genomes, we have applied high-throughput RNA interference (RNAi) screening to well-characterized melanoma cell lines. We characterized a panel of 65 melanoma cell lines for genome-wide copy number changes and gene expression, as well as the mutation status of known melanoma genes (BRAF, HRAS, NRAS, KRAS, PTEN, CDKN2A, and TP53). From this panel, 18 cell lines were screened against some 1,250 genes (696 kinases, 550 supplemental; 4 siRNAs per gene) to identify modifiers of melanoma cell survival. A striking finding from our data is that MITF expression appears to be a determinant of invasive context and, furthermore, is associated with changes in both p16 and PTEN status. In the cell lines we examined, high MITF expression correlated with wild-type PTEN status, whereas PTEN was deleted or mutated in 30-35% of cell lines having low MITF expression. Similarly, p16 was unaltered in 40-45% of the cell lines that had high MITF expression but remained unaltered in only 20-25% of low MITF-expressing cell lines. The loss of p16 and PTEN are correlated with an aggressive phenotype in melanoma, and we confirmed by Western analysis that in cell lines with high MITF, p16 is present, but in cell lines with low MITF, p16 expression is absent. In agreement with the current literature, no association could be found with BRAF mutational status. Moreover, these data confirm that MITF is associated with the switch in phenotype from a proliferative to an invasive state in melanoma in a BRAF-independent manner, which in turn is associated with an increase in WNT5A expression, a change we previously have suggested is a critical determinant of melanoma metastasis. Results to be presented, aligned with new studies of sequence variants of MITF (Brown et al., unpublished), may help define a novel context for invasive potential of the important disease. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4984. doi:10.1158/1538-7445.AM2011-4984

Abstract 4964: High-throughput genomic analysis of platinum and taxane resistance in ovarian cancer cells

Abstract Ovarian cancer is the fifth-leading cause of death from cancer in women. The five-year survival rate for ovarian cancer remains low at approximately 45%. Ovarian cancer patients are often treated with a combination of a platinum agent plus a taxane and despite initial success, up to 75% of responders relapse within 18-28 months. We have previously utilized high-throughput siRNA screening to identify gene modulators of cisplatin resistance in ovarian cancer cell lines. Here, we identify genomic characteristics of paclitaxel-resistant and cisplatin-resistant ovarian cancer cells. Combined with our previous cisplatin-resistance studies, we hope to obtain a more complete picture of platinum/taxane resistance in ovarian cancer. We have developed a variant of the A2780 cell line (A2780-pacli) that exhibits a four-log increase in paclitaxel IC50. Array based comparative genomic hybridization (aCGH) has demonstrated a small number of focal chromosomal aberrations between the parent and isogenic derivative cell lines suggesting drug-specific evolutionary changes to the A2780 genome. We also utilized expression microarrays to identify genes that may contribute to drug-resistant phenotypes. cRNA probes generated from A2780-pacli cells or a commercial cisplatin-resistant A2780 cell line (A2780-cis) and were hybridized against cRNA from wild-type A2780 cells (A2780-WT). Differential gene expression analysis identified overlapping and individual drug-specific patterns of gene expression, including 1519 genes over- or under-expressed in both the cis- and pacli-resistant lines. Additionally, we have completed a high-throughput RNA interference (HT-RNAi) screen on A2780-pacli cells involving 572 kinase genes in order to determine mediators of paclitaxel resistance in this cell line. The HT-RNAi assay was developed to quantify the growth inhibition of A2780-pacli cells transfected with siRNA and treated with an EC50 dose of paclitaxel. Cell viability was assessed after 72 hours of drug exposure. The HT-RNAi screening data was normalized and log 2 ratios of drug-treated/vehicle-treated wells were determined to show drug potentiation. Following data analysis, we generated a list of gene targets that, upon silencing, lead to potentiation of cell viability in response to paclitaxel. Validation of these genes will identify potential therapeutic targets for novel paclitaxel combinations in order to improve clinical efficacy. These findings further demonstrate the effectiveness of using HT-RNAi as a tool for identifying sensitizing targets to chemotherapeutic agents. Taken together, the integrated application of genomic survey methods provides insight into mechanisms of drug resistance in ovarian cancer cells. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4964. doi:10.1158/1538-7445.AM2011-4964

Jerky/Earthbound facilitates cell-specific Wnt/Wingless signalling by modulating β-catenin-TCF activity

Wnt/Wingless signal transduction directs fundamental developmental processes, and upon hyperactivation triggers colorectal adenoma/carcinoma formation. Responses to Wnt stimulation are cell specific and diverse; yet, how cell context modulates Wnt signalling outcome remains obscure. In a Drosophila genetic screen for components that promote Wingless signalling, we identified Earthbound 1 (Ebd1), a novel member in a protein family containing Centromere Binding Protein B (CENPB)-type DNA binding domains. Ebd1 is expressed in only a subset of Wingless responsive cell types, and is required for only a limited number of Wingless-dependent processes. In addition, Ebd1 shares sequence similarity and can be functionally replaced with the human CENPB domain protein Jerky, previously implicated in juvenile myoclonic epilepsy development. Both Jerky and Ebd1 interact directly with the Wnt/Wingless pathway transcriptional co-activators β-catenin/Armadillo and T-cell factor (TCF). In colon carcinoma cells, Jerky facilitates Wnt signalling by promoting association of β-catenin with TCF and recruitment of β-catenin to chromatin. These findings indicate that tissue-restricted transcriptional co-activators facilitate cell-specific Wnt/Wingless signalling responses by modulating β-catenin-TCF activity.

Parallel High-Throughput RNA Interference Screens Identify PINK1 as a Potential Therapeutic Target for the Treatment of DNA Mismatch Repair–Deficient Cancers

Synthetic lethal approaches to cancer treatment have the potential to deliver relatively large therapeutic windows and therefore significant patient benefit. To identify potential therapeutic approaches for cancers deficient in DNA mismatch repair (MMR), we have carried out parallel high-throughput RNA interference screens using tumor cell models of MSH2- and MLH1-related MMR deficiency. We show that silencing of the PTEN-induced putative kinase 1 (PINK1), is synthetically lethal with MMR deficiency in cells with MSH2, MLH1, or MSH6 dysfunction. Inhibition of PINK1 in an MMR-deficient background results in an elevation of reactive oxygen species and the accumulation of both nuclear and mitochondrial oxidative DNA lesions, which likely limit cell viability. Therefore, PINK1 represents a potential therapeutic target for the treatment of cancers characterized by MMR deficiency caused by a range of different gene deficiencies.

High-throughput RNA interference screening using pooled shRNA libraries and next generation sequencing

RNA interference (RNAi) screening is a state-of-the-art technology that enables the dissection of biological processes and disease-related phenotypes. The commercial availability of genome-wide, short hairpin RNA (shRNA) libraries has fueled interest in this area but the generation and analysis of these complex data remain a challenge. Here, we describe complete experimental protocols and novel open source computational methodologies, shALIGN and shRNAseq, that allow RNAi screens to be rapidly deconvoluted using next generation sequencing. Our computational pipeline offers efficient screen analysis and the flexibility and scalability to quickly incorporate future developments in shRNA library technology.

Vigilance and Validation: Keys to Success in RNAi Screening

In the 12 years since the process of RNA interference (RNAi) was first discovered, great progress has been made in understanding its mechanism and exploiting its ability to silence gene expression to study gene function at a genome-wide level. Its extensive use as a screening method has yielded many published lists of genes that play novel roles in higher eukaryotes. However, the usefulness of this information is potentially limited by the occurrence of unintended off-target effects. Here we review the potential causes of off-target effects and the impact of this phenomenon in interpreting the results of high-throughput RNAi screens. In addition to targeting the intended gene product, artificial short interfering RNAs (siRNAs) can produce off-target effects by down-regulating the expression of multiple mRNAs through microRNA-like targeting of the 3' untranslated region. We examine why this phenomenon can produce high hit rates in siRNA screens and why independent validation of screening results is critical for the approach to yield new biological insights.

RNAi Screening for Host Factors Involved in <em>Vaccinia</em> Virus Infection using <em>Drosophila</em> Cells

Viral pathogens represent a significant public health threat; not only can viruses cause natural epidemics of human disease, but their potential use in bioterrorism is also a concern. A better understanding of the cellular factors that impact infection would facilitate the development of much-needed therapeutics. Recent advances in RNA interference (RNAi) technology coupled with complete genome sequencing of several organisms has led to the optimization of genome-wide, cell-based loss-of-function screens. Drosophila cells are particularly amenable to genome-scale screens because of the ease and efficiency of RNAi in this system 1. Importantly, a wide variety of viruses can infect Drosophila cells, including a number of mammalian viruses of medical and agricultural importance 2,3,4. Previous RNAi screens in Drosophila have identified host factors that are required for various steps in virus infection including entry, translation and RNA replication 5. Moreover, many of the cellular factors required for viral replication in Drosophila cell culture are also limiting in human cells infected with these viruses 4,6,7,8, 9. Therefore, the identification of host factors co-opted during viral infection presents novel targets for antiviral therapeutics. Here we present a generalized protocol for a high-throughput RNAi screen to identify cellular factors involved in viral infection, using vaccinia virus as an example.

RNAi Screening for Host Factors Involved in <em>Vaccinia</em> Virus Infection using <em>Drosophila</em> Cells

Viral pathogens represent a significant public health threat; not only can viruses cause natural epidemics of human disease, but their potential use in bioterrorism is also a concern. A better understanding of the cellular factors that impact infection would facilitate the development of much-needed therapeutics. Recent advances in RNA interference (RNAi) technology coupled with complete genome sequencing of several organisms has led to the optimization of genome-wide, cell-based loss-of-function screens. Drosophila cells are particularly amenable to genome-scale screens because of the ease and efficiency of RNAi in this system 1. Importantly, a wide variety of viruses can infect Drosophila cells, including a number of mammalian viruses of medical and agricultural importance 2,3,4. Previous RNAi screens in Drosophila have identified host factors that are required for various steps in virus infection including entry, translation and RNA replication 5. Moreover, many of the cellular factors required for viral replication in Drosophila cell culture are also limiting in human cells infected with these viruses 4,6,7,8, 9. Therefore, the identification of host factors co-opted during viral infection presents novel targets for antiviral therapeutics. Here we present a generalized protocol for a high-throughput RNAi screen to identify cellular factors involved in viral infection, using vaccinia virus as an example.

A suite of MATLAB-based computational tools for automated analysis of COPAS Biosort data.

Complex Object Parametric Analyzer and Sorter (COPAS) devices are large-object, fluorescence-capable flow cytometers used for high-throughput analysis of live model organisms, including Drosophila melanogaster, Caenorhabditis elegans, and zebrafish. The COPAS is especially useful in C. elegans high-throughput genome-wide RNA interference (RNAi) screens that utilize fluorescent reporters. However, analysis of data from such screens is relatively labor-intensive and time-consuming. Currently, there are no computational tools available to facilitate high-throughput analysis of COPAS data. We used MATLAB to develop algorithms (COPAquant, COPAmulti, and COPAcompare) to analyze different types of COPAS data. COPAquant reads single-sample files, filters and extracts values and value ratios for each file, and then returns a summary of the data. COPAmulti reads 96-well autosampling files generated with the ReFLX adapter, performs sample filtering, graphs features across both wells and plates, performs some common statistical measures for hit identification, and outputs results in graphical formats. COPAcompare performs a correlation analysis between replicate 96-well plates. For many parameters, thresholds may be defined through a simple graphical user interface (GUI), allowing our algorithms to meet a variety of screening applications. In a screen for regulators of stress-inducible GFP expression, COPAquant dramatically accelerated data analysis and allowed us to rapidly move from raw data to hit identification. Because the COPAS file structure is standardized and our MATLAB code is freely available, our algorithms should be extremely useful for analysis of COPAS data from multiple platforms and organisms. The MATLAB code is freely available at our web site (www.med.upenn.edu/lamitinalab/downloads.shtml).

A High-Content RNAi-Screening Assay to Identify Modulators of Cholesterol Accumulation in Niemann–Pick Type C Cells

Niemann-Pick disease type C (NPC) is an inherited lipid storage disorder characterized by a defect in intracellular trafficking of exogenous cholesterol and glycosphingolipids. A goal for therapeutic treatment of NPC is to decrease/normalize cholesterol accumulation. We developed a functional genomics-based assay, combining high-throughput RNA interference (HT-RNAi) screening with high-content fluorescence imaging to identify specific genes in NPC cells that will result in more normal cholesterol levels in the diseased cells. Conditions for siRNA tranfections were optimized for 2 NPC fibroblast cell lines (GM03123, GM18453) and a normal fibroblast cell line (GM05659). RNAi screening was done using a focused-set siRNA library targeting 40 cholesterol trafficking-associated genes, knowledge mined from the existing literature on NPC disease, and/or their association with NPC1/NPC2 genes. We utilized filipin staining as a measure of cholesterol accumulation in fixed NPC cells. Data analysis of these screens confirmed several genes including LDLR and RAB9A that reduced cholesterol content in NPC cells. Nine genes were validated using filipin staining to detect unesterified cholesterol as well as cholesteryl BODIPY esters to study lipid trafficking. Gene silencing was also confirmed using qRT-PCR. Our results show that this technology can be applied to larger screens to identify genes responsible for lipid accumulation and/or trafficking in NPC disease, which could be instrumental in developing innovative therapies for individuals afflicted with NPC disease.

고속 Genome-Wide RNA 간섭 스크리닝을 위한 세포영상의 자동 분할

최근에 고속 genome-wide RNA 간섭 스크리닝 기술은 복잡한 세포 기능을 이해하는 생명공학 연구의 핵심적인 도구로 자리 잡고 있다. 그러나 관련 연구에서 발생되는 수많은 영상을 수작업을 통해 분석하는 것은 많은 시간과 노력이 요구된다. 따라서 세포영상의 자동분석 기술은 매우 시급히 확보되어야 하는 기술이며, 그 중 영상 분할은 자동분석을 위한 첫 단계로서 가장 중요한 과정이라 할 수 있다. 세포영상의 자동분할에서는 영역의 겹침 현상과 영역별 모양의 다양성 및 영상 특성의 불균일성 등이 정확한 세포 분할을 어렵게 만드는 주원인으로 작용한다. 본 논문에서는 이러한 문제점을 극복하기 위해 영상 특징들의 국부적인 연속성과 특징 벡터 기반의 워터쉐드 알고리즘을 적용한 새로운 자동 세포 분할 알고리즘을 제안한다. 영상 특징들의 연속성을 국부적인 영역으로 제한함으로써 영역별 모양의 다양성 및 영상 특성의 불균일성에 따른 문제점을 극복할 수 있으며, 특징벡터의 사용을 통해 하나의 영상특징만을 고려한 경우 발생되는 겹침 영역에서의 분할 성능 저하를 개선할 수 있다. 세포영상 분석을 위한 소프트웨어 패키지인 Cellprofiler와의 비교/분석 실험을 통해 제안 알고리즘의 효율성을 입증하였다. In recent years, high-throughput genome-wide RNA interference screening is emerging as an essential tool to biologists in understanding complex cellular processes. The manual analysis of the large number of images produced in each study spends much time and the labor. Hence, automatic cellular image analysis becomes an urgent need, where segmentation is the first and one of the most important steps. However, those factors such as the region overlapping, a variety of shapes, and non-uniform local characteristics of cellular images become obstacles to efficient cell segmentation. To avoid the problem, a new watershed-based cell segmentation algorithm using a localized segmentation method and a feature vector is proposed in this paper. Localized approach in segmentation resolves the problems caused by a variety of shapes and non-uniform characteristics. In addition, the poor performance of segmentation in overlapped regions can be improved by taking advantage of a feature vector whose component features complement each other. Simulation results show that the proposed method improves the segmentation performance compared to the method in Cellprofiler.

Abstract 5259: Application of HT-RNAi-based functional genomics in neuroblastoma

Abstract Neuroblastoma is the most common extra-cranial solid cancer in children. About 70% of patients with neuroblastoma have metastatic disease at the time of diagnosis. Children with favorable disease characteristics and younger than one year of age (stages I and II) have a higher likelihood of disease-free survival. However, older children with advanced disease (stages III and IV) have only a 30% chance of survival even with aggressive therapy. Additionally, amplification of the MYC-N gene has been associated with stage III and IV tumors, thus establishing it as a poor prognostic marker. Current treatment primarily consists of combinations of surgery, radiation, and chemotherapy. Newer regimens also include the topoisomerase I inhibitor topotecan, which has been found to be effective against recurrent disease. In order to identify “Achilles heel” targets that modulate growth of neuroblastoma, we applied a functional genomics approach using High Throughput RNA interference (HT-RNAi). Furthermore, by treatment of cells with low dose topotecan, we hope to identify genes the can improve the response to this current therapy. We first identified optimal siRNA transfection conditions for the four neuroblastoma cell lines; MYC-N amplified, IMR-5 and IMR-32 and MYC-N non-amplified, SK-N-AS and NB-EB. Since these cell lines can be difficult to transfect with siRNA, several cationic lipids were tested at varying lipid:siRNA ratios to obtain the optimal reagent and ratio for each cell line. Next, we determined the optimal low dose (IC10-30) of topotecan for each cell line. Following these optimizations, HT-RNAi assays were conducted on the four neuroblastoma cell lines using a kinase siRNA library targeting 572 kinases and a siRNA library targeting 532 apoptosis associated genes treated with vehicle or low dose topotecan. These HT-RNAi screens identified genes whose silencing decreased neuroblastoma cell growth and genes whose silencing improved topotecan response. We are currently in the process of validating these results. After validation, we hope to develop these molecular targets into innovative therapeutics for children affected with this disease. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 5259.

Abstract 3408: RNAi screening identifies STK10 as a novel therapeutic target for Ewing's sarcoma

Abstract Ewing sarcoma family tumors (ESFT) represent ∼ 3% of pediatric cancers and are the second most common bone malignancy in children and adolescents. Rearrangement of the EWS gene on chromosome 22q12 with an ETS gene family member is the underlying molecular genetic abnormality for Ewing's sarcoma. These translocations provide a valuable tool for accurate diagnosis of ESFTs and also represent ideal targets for the development of targeted therapeutics. The most common translocation is t(11;22)(q24;q12), which involves the proteins EWS and Friend Leukemia Integration Site 1 (FLI1). The newly formed EWS-FLI1 fusion protein is a transcription factor that could then lead to aberrant transcription and gives the ES cells a specific tumorigenic context. We employed a functional genomics approach based on high throughput RNA interference (HT-RNAi) analysis to identify “Achilles heel” targets or genes who's silencing affect the proliferation and survival of Ewing's sarcoma cells. We used a human “kinome” library targeting 572 kinases and four ES cell lines, TC-32, TC-71, SK-ES-1 and RD-ES for the HT-RNAi screening. All the screens were done in duplicate and the data was normalized and analyzed using the Z-score method. One gene that was a significant “hit” across all the four cell lines was serine threonine kinase 10 or STK10. Our validation confirmed that reduction in ES cell growth by STK10 siRNA was due to specific STK10 silencing and was not an off target effect. Moreover, silencing of STK10 in ES cells resulted in increased apoptosis. We also showed that normal human fibroblasts did not depend on STK10 for cell growth. Our results have confirmed that STK10, which belongs to the polo like kinase family, is required for the growth of ES cells. After further validation we will use these results for the development of specific drugs targeting STK10 and thereby accelerate the development of improved therapeutics for Ewing's sarcoma. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3408.

High‐throughput RNAi screening to dissect cellular pathways: A how‐to guide

RNA interference (RNAi) has become a powerful tool to dissect cellular pathways and characterize gene functions. The availability of genome-wide RNAi libraries for various model organisms and mammalian cells has enabled high-throughput RNAi screenings. These RNAi screens successfully identified key components that had previously been missed in classical forward genetic screening approaches and allowed the assessment of combined loss-of-function phenotypes. Crucially, the quality of RNAi screening results depends on quantitative assays and the choice of the right biological context. In this review, we provide an overview on the design and application of high-throughput RNAi screens as well as data analysis and candidate validation strategies.

From experimental setup to bioinformatics: An RNAi screening platform to identify host factors involved in HIV‐1 replication

RNA interference (RNAi) has emerged as a powerful technique for studying loss-of-function phenotypes by specific down-regulation of gene expression, allowing the investigation of virus-host interactions by large-scale high-throughput RNAi screens. Here we present a robust and sensitive small interfering RNA screening platform consisting of an experimental setup, single-cell image and statistical analysis as well as bioinformatics. The workflow has been established to elucidate host gene functions exploited by viruses, monitoring both suppression and enhancement of viral replication simultaneously by fluorescence microscopy. The platform comprises a two-stage procedure in which potential host factors are first identified in a primary screen and afterwards re-tested in a validation screen to confirm true positive hits. Subsequent bioinformatics allows the identification of cellular genes participating in metabolic pathways and cellular networks utilised by viruses for efficient infection. Our workflow has been used to investigate host factor usage by the human immunodeficiency virus-1 (HIV-1), but can also be adapted to other viruses. Importantly, we expect that the description of the platform will guide further screening approaches for virus-host interactions. The ViroQuant-CellNetworks RNAi Screening core facility is an integral part of the recently founded BioQuant centre for systems biology at the University of Heidelberg and will provide service to external users in the near future.