<<

(2004) 23, 8376–8383 & 2004 Publishing Group All rights reserved 0950-9232/04 $30.00 www.nature.com/onc

Use of RNA interference libraries to investigate oncogenic signalling in mammalian cells

Julian Downward*,1

1Cancer Research UK London Research Institute, 44 Lincoln’s Inn Fields, London WC2A 3PX, UK

Over the past decade, ‘RNA interference’ has emerged as RNA-induced silencing complex (RISC), which uses one a natural mechanism of silencing of expression. This strand to target complementary mRNA for ancient cellular antiviral response can be manipulated to degradation. provide an effective research tool to knock down the level Artificial introduction of siRNA duplexes into cells of expression of selected target , providing a very can thus silence the expression of selected genes. A powerful new method for the analysis of cell signalling number of methods have been developed for getting pathways. Systematic silencing of genes on a -wide siRNAs of a desired sequence into target mammalian scale using large rationally designed libraries targeting cells. The two most commonly used are to transfect in many thousands of genes provides a novel functional synthetic short double-stranded RNA molecules of the genomics approach to the investigation of many aspects of desired sequence, which then act to engage RISC mammalian cell behaviour, including oncogenic transfor- directly (Elbashir et al., 2001). Alternatively, expression mation. Here, the different approaches taken to use RNA vectors can be introduced into cells, either by transfec- interference libraries to study the phenotype will be tion or the use of , which direct the production of considered, including both selective and high throughput short hairpin RNA sequences that are then processed screens and the use of both vector-based and synthetic into siRNA within the cell by endogenous -based methods for inducing RNA inter- (Brummelkamp et al., 2002a, b; Paddison et al., ference. The advantages and drawbacks of the competing 2002a, b). methodologies will be discussed. RNA interference library Both of these methods of harnessing RNA inter- technology holds great promise for enabling somatic cell ference have recently been used on a large scale as a in tissue culture systems. Whether it can provide functional genomic tool in , and have been significant newinsights into cancer willbe its greatest used for longer periods in lower . System- challenge. atically silencing genes one by one corresponding to a Oncogene (2004) 23, 8376–8383. doi:10.1038/sj.onc.1208073 large fraction of the genome allows the identification of genes that are required for a particular phenotype to Keywords: RNA interference; screening; transforma- occur. In the case of cancer, if genes could be identified tion; library; oncogenesis in this way, as required for the maintenance of the transformed phenotype, the they encode might make excellent targets for the development of therapeu- tic drugs. This promise has led to the development of a number of large collections of RNA interference vectors Introduction or synthetic . These are being used in two different types of screens: high throughput and RNA interference was first described in plants in 1990 selective. In the former, each assay point corresponds to and has subsequently been found as a mechanism of induction of RNA interference against a single gene, in most multicellular eukaryotes. The with a phenotypic change being assayed for (Aza-Blanc mechanistic basis for the silencing of et al., 2003; Brummelkamp et al., 2003; Paddison et al., by RNA interference has been described in great detail 2004). In the latter, many genes are silenced at the and has been the subject of numerous recent reviews same time in a mixed pool of cells, with the screen (Hannon, 2002; Denli and Hannon, 2003; Dykxhoorn being designed in such away that only cells acquiring et al., 2003; Downward, 2004), so will not be discussed the desired phenotype as a result of knock down of in depth here. In a nutshell, double-stranded RNA expression of one of these genes can survive: these cells, molecules in the cell are cleaved by the along with the RNAi sequence they carry are then complex to form small interfering (si) double-stranded identified as they emerge at the end of the screen (Berns RNA molecules, which are some 20 base pairs long. et al., 2004). These are recognized by another enzyme complex, the Here the different approaches taken to use RNA interference libraries to study the cancer phenotype will be considered and the advantages and drawbacks of the *Correspondence: J Downward; E-mail: [email protected] competing methodologies will be discussed. Use of RNAi in oncogenic signalling J Downward 8377 RNA interference library design per gene. Recently developed proprietary software from Cenix BioScience has been reported to achieve a 470% Oligonucleotide libraries gene silencing efficiency with 480% of over 1000 siRNA oligos (http://www.ambion.com/techlib/tn/113/ The principal variable in the design of a large-scale small 14.html), raising the possibility that only one optimally interfering double-stranded oligoribonucleotide (siR- designed oligo per gene could be used to make up NA) collection is the choice of the sequences used to an effective genome scale library. As more siRNA target each gene. In addition, the level of redundancy sequences are experimentally validated for mRNA with which the library is designed will have major knockdown, this approach will become more reliable. implications, both in terms of cost and the design of In addition to testing siRNA oligos for their effect on experiments that can be performed with it. How many expression of endogenous target genes, it is also possible oligos are used to target each gene will depend on the to rapidly screen them against hybrid mRNA fused to a likelihood that any given oligo will successfully knock reporter construct (Kumar et al., 2003). down its cognate mRNA. The use of multiple siRNA oligos for each gene raises The original criteria for designing siRNA sequences the issue of whether they should be used singly or as were laid down as a simple set of empirical guidelines by pools with other oligos targeting the same gene. In Tuschl in 2001 (Elbashir et al., 2001). Subsequently, a addition to reducing the number of assays that need to combination of increased understanding of the structure be performed in a screen, an advantage of pooling three and function of the RISC complex and an empirical or four oligos together is that one maximizes the chance analysis of the efficiency of RNA interference induction of using an oligo that knocks down expression very by very large numbers of siRNA oligos has led to effectively. Concerns about the use of pools have considerable improvements in siRNA design algorithms. focused on the possibility of increasing the likelihood Recently, optimized design criteria have been published of occurrence of off-target effects. However, as these by a number of groups (Elbashir et al., 2002; Khvorova effects are thought to be dose dependent, if the total et al., 2003; Schwarz et al., 2003; Reynolds et al., 2004). oligo concentration applied to the cells remains con- Criteria for effective RNA interference include: low stant, pools may be less likely to produce significant off- G þ C content (30–50%), low internal stability at 50 target effects than single oligos. Whether this turns out antisense strand, high internal stability at 50 sense to be true or not, the importance of verifying effects with strand, absence of internal repeats or palindromes, A- a second siRNA sequence against the same gene means form helix between target mRNA and siRNA, presence that if the library used is only available as pools of of A at position 3, U at position 10 and A at position 19 oligos, secondary follow-up assays will require the of , absence of G at position 13 and G or C acquisition of individual siRNA oligos, which may at position 19 of sense strand, and lack of close incur extra cost and delay. to other gene sequences. As RNA interference targets mRNA in the cyto- Publicly available siRNA design algorithms have been plasm, different siRNAs can be used to target different created based on these criteria (Cui et al., 2004; Wang splice variants transcribed from the same gene. Given and Mu, 2004). A selection of siRNA design algorithms the high level of alternative splicing in mammalian readily available via the internet are: EMBOSS siRNA , a library targeting all possible splice variants algorithm (http://athena.bioc.uvic.ca/cgi-bin/emboss. individually would need to be much larger than one pl?_action ¼ input&_app ¼ sirna), Promega siRNA Target targeting common exons. Designer (http://www.promega.com/siRNADesigner/ The high degree of specificity of RNA interference program/), GeneScript siRNA target finder (https:// coupled with the considerable differences in sequence www.genscript.com/ssl-bin/app/rnai), Ambion siRNA between human and rodent genes makes it very unlikely predictor (http://www.ambion.com/techlib/misc/silencer_ that a library designed against one species would work siRNA_template.html), OligoEngine siRNA software effectively on the other. Different libraries will need to (http://www.oligoengine.com/Home/mid_prodSirna.html be designed for each species studied, although it is #sirna_tool), Whitehead siRNA prediction (http://jura. possible that some degree of crossreaction will be seen wi.mit.edu/pubint/http://iona.wi.mit.edu/siRNAext/), with closely related species. Sfold rational siRNA design (http://sfold.wadsworth. org/index.pl), Hannon Lab RNAi OligoRetriever Vector libraries (http://katahdin.cshl.org:9331/RNAi/html/rnai.html), Sonnhammer Group siSearch siRNA Similar criteria to the above are used in the design of design (http://sonnhammer.cgb.ki.se/siSearch/siSearch_1. short hairpin RNA sequences for vector-based RNA 4.html). interference. However, a critical factor in the success or Most publicly accessible siRNA design programs are otherwise of these libraries is the choice of vector likely to predict siRNA oligo sequences that will silence backbone. The two large mammalian vector-based gene expression reasonably efficiently (470% reduction RNA interference libraries that have been reported to in cognate mRNA) about 50–60% of the time. The use date use constructs that can be introduced into cells of three such oligos against each gene provides a high either as retroviral particles or by DNA probability of success, but does require considerable (Berns et al., 2004; Paddison et al., 2004). Berns et al. extra expenditure compared to the use of just one oligo used pRETRO SUPER, a retroviral vector in which the

Oncogene Use of RNAi in oncogenic signalling J Downward 8378 sequence encoding the shRNA hairpin is driven by mode using oligos or vectors, one gene at a time, or in a RNA polymerase III acting on the H1 RNA gene selective mode using large pools of vectors (Figure 1). (Brummelkamp et al., 2002a). The gene High throughput screening has a number of advantages, sequence-specific inserts are designed to form hairpins but also some drawbacks. with 19 base pairs of double-stranded RNA, plus a To screen on a genome-wide scale in high throughput nine invariant loop. The vector carries a mode can be a daunting prospect, as it requires many puromycin-resistance marker. Three sequences were thousands of assays to be performed. This is likely to be targeted in each of the 7914 human genes. time consuming and costly. It is essential that screens are Paddison et al. used a different retroviral vector, designed to minimize these two factors. This requires pSHAG MAGIC, in which the sequence encoding the that assays are highly robust and reproducible, reducing hairpin is driven by RNA polymerase III acting on the the need for multiple replicates or rescreens. All high U6 RNA gene promoter. In all, 29 hairpins throughput RNAi screens performed to date have used were used, with a four nucleotide loop. A 27-nucleotide some sort of fluorescent readout, which has the U6 RNA leader sequence was also included as this was advantage of being very easy to measure. It is also found to improve knockdown efficiency. The vector also important that good positive controls exist to optimize carries puromycin resistance and has a separate unique the assays. 60-nucleotide ‘barcode’ built in (see below). To aid in Cost considerations also favour assays that can be manipulation of the vectors, a recombination system performed on a very small scale, such as a 96- or 384- is built into the vector (‘Mating-assisted genetically well plate format. Aza-Blanc et al. (2003) used a library integrated cloning’) that allows easy exchange of the of 510 siRNA oligos to transfect HeLa cells in 384-well hairpin sequences between different vector backbones. plates and then test them for TRAIL-induced apoptosis, In all, 9610 human genes and 5563 mouse genes were using a cell viability assay with a fluorescent readout. targeted, mostly with threefold redundancy. This assay successfully identified several modulators of In addition to these two vectors, a wide range of other the apoptotic response, some of which might possibly RNA interference vectors have been designed that could be misregulated during . The amount of be used for library construction. Incorporation of a siRNA oligo transfected was about 10 pmoles/well, fluorescent marker such as GFP could be useful in meaning that commercially supplied libraries, for a library to allow assessment of transfection efficiency: a example, from Dharmacon, Ambion, or Qiagen, which number of commercial RNAi vectors include this typically provide 2 nmoles as standard, would in theory feature, including constructs derived from pRETRO be sufficient for about 200 screen runs. While the costs SUPER by Oligoengine, the pSIRENs series from BD of these commercial libraries may appear prohibitive for Biosciences Clontech, and the GeneSilencers series from academic users, the potential for sharing them between Gene Therapy Systems, Inc. Alternatively, a different several labs may help alleviate this somewhat. When viral delivery system could be used, such as adenoviral considering costs, it should also be noted that synthetic RNAi vectors (Arts et al., 2003; Zhao et al., 2003), oligos and both require the use of transfection available from BD Biosciences Clontech, Ambion and reagents such as lipofection mixes for introduction into Invitrogen, or lentiviral vectors (Abbas-Terki et al., cells. Large-scale screening can consume a lot of these 2002; Dirac and Bernards, 2003; Rubinson et al., 2003), expensive consumables and should be factored into any available from Invitrogen. Adenoviral vectors are likely costing of the screen. to achieve higher levels of expression of the shRNA, Other ways of stretching valuable resources even while lentiviral vectors will enable expression in further can be achieved using reverse transfection in a nonproliferating cells. format. In a series of screens to investigate A further future development that could potentially proteasome function and cytokinesis, both potentially be useful in a vector-based RNA interference library is important in carcinogenesis, Silva et al. (2004) spotted the incorporation of inducibility. Several tetracycline- siRNA oligos, and also plasmids, in a gelatin solution inducible RNAi vectors have been reported, both along with transfection reagent onto glass slides. Cells based (Chen et al., 2003; Czauderna et al., were overlaid onto the spotted array and took up the 2003; van de Wetering et al., 2003) and based siRNAs, showing significant transient knock down of (Wiznerowicz and Trono, 2003). An ecdysone-inducible the expression of the target genes and resulting RNA interference system has also been reported (Gupta phenotypic changes. In this way, very small amounts et al., 2004). It is not yet clear whether these systems are of reagents are used and large numbers of assay sufficiently robust to work effectively on a large scale can be achieved at one time, providing without individual optimization. that the end readout can be assessed microscopically. The major limitations of this methodology are that high efficiency of transfection is needed, otherwise spots will need to be very large to find a significant number of RNA interference library use transfected cells. This is less of a problem with synthetic High throughput screening with oligonucleotide libraries siRNA oligos than with plasmid-based shRNA vectors – for which Silva et al. solved the problem by using 293 As mentioned in the introduction, RNA interference cells, although these are not ideal for the study of many library screens can be carried out in a high throughput signalling pathways. The other limitation is that cell

Oncogene Use of RNAi in oncogenic signalling J Downward 8379 Arrayed RNAi libraries Pooled RNAi libraries Another screen of this kind performed with relevance synthetic oligos plasmid vectors viral vectors viral vectors to cancer identified the familial cylindromatosis tumour suppressor as a deubiquitinating enzyme transfect transfect package, package, infect infect important in the regulation of NF-kB (Brummelkamp et al., 2003). This small-scale screen focused on genes with sequence homology to known deubiquitinating High throughput assay Selective screen for enzymes. U2-OS cells were transiently cotransfected for altered phenotype(s) altered phenotype with an NF-kB luciferase reporter construct and shRNA vectors individually targeting 50 candidate human Amplify barcodes, Sequence hairpins Secondary assay to validate hits Fluorescently label, or barcodes deubiquitinating enzymes. The cells were then treated Hybridise to microarray to identify hits with TNF-a and NF-kB was activity measured by with barcode oligos luciferase fluorescence. Targeting the CYLD gene led to Secondary assay to upregulation of the NF-kB response, suggesting that the validate hits benign tumours commonly seen in familial cylindroma- tosis patients may be due to increased antiapoptotic Figure 1 Different approaches to large-scale RNA interference screens. See text for details signalling by NF-kB. More complex readouts can be measured in these screens than simply a ratio of fluorescence at two motility will restrict how long cells can be followed and wavelengths. Recently, several companies have devel- how close together elements can be placed. oped automated fluorescent microscopy systems, for Once hits have been identified in a high throughput example, the INCell Analyser 1000 and 3000 from screen, a good secondary screen is needed to check out Amersham Biosciences and the Discovery-1 from their significance. As the first assay will ideally give a Molecular Devices. These allow, among other things, numerical value, consideration should be given to how the automated measurement of the distribution of a big a change from the negative control is needed to be fluorescent between different cellular compart- worth pursuing in the secondary screen. This will be ments, such as the cytosol and the nucleus or the cytosol influenced by the overall size of the initial screen, the and the plasma membrane. Such measurements can be ease with which the secondary screen can be carried out performed rapidly in a multiwell format and can add and the level of confidence in the initial results. The considerable flexibility to the design of high throughput secondary screen can be designed to rule out possible RNAi screens. off-target effects of the siRNA oligos: for example, A promising approach to screening for potential using a different sequence against the same gene, or cancer therapeutic targets using these methods is to look deconvoluting a pool of oligos against the same gene for synthetic lethality between a transforming oncogene into their individual components. and an siRNA. At its simplest, this would involve screening closely related normal and oncogene- High throughput screening with vector libraries transformed cells with an siRNA library looking for cell death, or less optimally arrest, specifically in the Many of the same considerations as those above exist untransformed but not the normal cells. Owing to the for high throughput screens using vector-based libraries. fact that the microevolutionary process involved in The major difference is that due to the much lower cancer formation tends to result in the cancer cells transfection efficiency of plasmids compared to oligos, becoming dependent on oncogenic signalling for their it is necessary to mark the transfected cells so that continued survival – a process termed ‘oncogene their behaviour can be distinguished from that of the addiction’ (Weinstein, 2002) – such screens may reveal untransfected cells, or to give a measure of the trans- targets that would allow selective killing of the tumour fection efficiency of the whole cell population in that cells. assay sample for normalization purposes. Paddison et al. (2004) performed a high throughput vector library Selective screening with vector libraries screen of proteasome function by cotransfecting 293 cells with individual shRNA plasmids, a DsRed The other major assay mode used with RNA inter- fluorescent protein encoding plasmid and an ZsGreen ference libraries is the selective screen. A selective fluorescent protein fused to a PEST sequence containing pressure is applied that will cause negative control cells degron from mouse ornithine decarboxylase. In negative to die, growth arrest or in some other way be eliminated controls, the PEST sequence ensures proteasome- from the culture. The only cells that can survive and mediated degradation of the ZsGreen fluorescent expand in the culture are those that have received an protein fusion, giving a high ratio of red to green RNAi sequence that knocks down a gene needed for fluorescence. Any shRNA plasmid that leads to pro- sensitivity to the selective pressure. The resistant cells teasome malfunction promotes the levels of ZsGreen can be grown and the sequence of the RNAi sequence and thus reduces the ratio of red to green fluorescence. determined. The dual constraints of needing relatively The screen performed impressively, identifying a high long-term selections and having to be able to determine proportion of known proteasomal subunit from a the RNAi sequence present in the resistant cells limits library of 7000 shRNAs tested. this screening methodology to vector-based RNAi and

Oncogene Use of RNAi in oncogenic signalling J Downward 8380 not synthetic oligos. The final determination of the value to reapplying selective pressure to cell populations RNAi sequence in the resistant cells is carried out by that have already been selected, as there is no PCR amplification and sequencing of the gene-specific differential selection against the false positives that have insert from invariant primers based on the vector already accumulated. Backgrounds can sometimes be backbone sequence. This can either be carried out on reduced by screening a number of single-cell clones of single clones or on populations of resistant cells. parental cells for low background levels in response to The major example of this type of screen to date was a the selective pressure. selection for RNAi sequences that would allow escape of As with the high throughput screens, a good human diploid fibroblasts from p53-mediated senes- secondary screen is very important for verifying hits. cence (Berns et al., 2004). Human BJ primary fibroblasts Again, this is a good stage at which to check that a expressing telomerase were conditionally immortalized different sequence targeted against the same gene can using temperature-sensitive SV40 large T antigen. Upon give a positive result, reducing the likelihood of off- shift to the nonpermissive temperature, the cells senesce target effects. It is also useful to check that in both unless they have received an RNAi sequence that blocks primary and secondary screens, the induction of a this response. Six novel hits were identified that positive phenotype is associated with knockdown of the appeared to play a role in p53-mediated senescence. presumed target mRNA. This also applies to high There are several advantages to the use of selective throughput screens, but is particularly important when screens. A major one is the ability to pool large numbers using vector-based systems in a stable, rather than of RNAi vectors together, allowing only a relatively transient, manner where knockdown efficiencies tend to small number of pools to be screened. While this is be lower. A consequence of this is that the secondary potentially very useful, these screens have significant screen here may need to repeat the whole selection limitations. Since the aim of pooling is to achieve a protocol to allow cells with a good level of target complex mixture of cells each carrying a very small knockdown to emerge, rather than assuming that all number of RNAi sequences, rather than a homogeneous cells receiving the identified RNAi construct will show mixture of cells all carrying a very complex mixture of sufficiently good knockdown to score as phenotypically RNAi sequences, this is only possible with viral- positive. mediated delivery and not with transfection. Viral A specific problem with selective screens with regard delivery into human cells normally requires high-level to research into the acquisition and maintenance of the biological containment, but this can be avoided in the cancer phenotype is that they tend to operate in the case of by packaging into an ecotropic reverse direction to that which one would want. By their delivery system that will only infect mouse cells and very nature, cancer cells are able to prosper under using these to screen human cells that have been circumstances where normal cells do not. For example, engineered to express the mouse ecotropic they will grow without attachment or without serum. receptor (see Berns et al., 2004). An ideal screen would be to select for loss of the It is hard to assess optimal RNAi pool sizes for these transformed phenotype, but there are very few selections screens. Ideally, a good positive control RNAi vector that will efficiently yield up normal cells against a should be available from knowledge of the system background of transformed cells, whereas many that studied. This can then be mixed into increasingly large will do the reverse. One possibility is to screen for genes pool sizes at the same ratio as the other components and that when knocked down will promote transformation tested to see what pool size still allows unequivocal in the hope that these will be biologically significant detection of the positive control. A typical pool size used tumour suppressor genes. While these are unlikely to is about a 100 genes; in the case of the NKI library, this provide therapeutic targets directly, they might yield was made up of some 300 different retroviruses, significant prognostic markers or point to the identity of allowing for the threefold redundancy (Berns et al., enzymes that reverse their activity, which could be 2004). promising cancer drug targets. Viable pool size will also be strongly dependent on the background level of false positives: high backgrounds Screening using barcodes will severely limit the possible degree of pooling used and require larger numbers of individual assays. In A possible way around the difficulty of selecting for a practice, one of the greatest constraints on this type of normal cell phenotype from a transformed cell back- screen is provided by the need for low background ground may be offered by combining selective screens levels. One approach to easing this is to perform screens with microarray technology. This strategy, termed iteratively. Ideally this is done by isolating the RNAi ‘barcode’ screening (Brummelkamp and Bernards, sequence inserts from resistant cells, for example, by 2003; Berns et al., 2004; Paddison et al., 2004), makes PCR in the case of the NKI library. This mix of inserts use of a gene-specific sequence incorporated into each can then be recloned into the RNAi vector and shRNA vector in the library. In the case of the CSHL reintroduced into a fresh population of parental cells, library (Paddison et al., 2004), this sequence is separate which are reselected. This can be repeated a number of from the short hairpin sequence, while in the case of the times until a limited number of sequences are repro- NKI library, it is the short hairpin sequence itself (Berns ducibly obtained. While this process is time consuming, et al., 2004). Pools of vectors are introduced into cells, it can alleviate background problems. There is limited which are then selected, for example, by a stress that can

Oncogene Use of RNAi in oncogenic signalling J Downward 8381 result in the loss of cells where a potential therapeutic down if the screen is to succeed. This is the most target gene has been knocked down. In normal screens demanding situation imaginable for achieving gene it would be impossible to determine what sequences silencing. However, if the background in a selective were targeted in these cells, as they would be lost to screen is sufficiently low, it may be possible to identify follow-up. However, by amplifying all the barcodes rare cells in which the vector is integrated in a from before and after the selection, labelling them with particularly favourable location, resulting in a much two different colours fluorescent dyes and hybridizing better knockdown than average for that construct. them to microarrays on which all the barcodes are represented, it is possible to identify genes whose Problems handling large collections of constructs There targeting results in loss of cells from the population. is a particular difficulty dealing with large numbers of This has obvious applications for cancer drug discovery. plasmids that is not an issue with oligonucleotide In theory, the system could greatly simplify RNAi collections. Preparing transfectable DNA from large screening and could be well adapted to screens of numbers (thousands) of plasmids for high throughput relevance to cancer, such as synthetic lethal effects with vector library screens is time consuming and costly. It . Berns et al. used it on a small scale to study also subjects the carrying the plasmids to p53-mediated senescence and were able to identify p53 strong selective pressure that can result in recombina- itself as a positive control. Paddison et al. also tested the tion events. Replicating multiple copies of a gridded bar code system in control experiments, concluding that library can run into similar problems. Both the NKI barcodes that were separate from the hairpin sequences and CSHL RNAi libraries have suffered from pro- were usable, but that the hairpin itself could not be used blems with recombination resulting in loss of hairpin effectively. Presumably this is due to the fact that the use sequences. There is also a problem when using pooled of hairpin sequences from the vectors to hybridize vectors that the complexity of the pool is reduced when against hairpin sequences on the microarray is likely to the bacteria are grown. It is likely that even if the cause significant problems due to secondary structure, originally produced libraries are exactly as intended, by but it is unclear why this worked for Berns et al. but not the time they have been distributed and manipulated for Paddison et al. While the barcode strategy clearly by multiple users, they will be significantly less than holds out significant promise for the future, it is not yet optimal. a fully validated technology and no novel findings have yet been reported using it. Off-target effects There are conflicting views as to how Problems with RNA interference library methodology large a problem this is. Two forms of off-target effect exist: sequence specific and sequence independent. The A number of problems that arise in RNA interference former is caused by siRNAs targeting expression of library screens have been raised above. Particularly, genes with related sequence to the desired target. critical problem areas or issues not yet addressed are: Systematic studies using microarrays have concluded either that this is a significant problem, with similarities Redundancy of target genes As a genetic approach, as low as 11 contiguous bases causing offtarget effects RNAi library screening may be limited by redundancy (Jackson et al., 2003), or that it is not a significant of the target genes. This is a much greater problem in problem (Chi et al., 2003). While the former study seems mammalian systems than in such as worms likely to be an overly pessimistic view, it does underscore and flies, where a great deal of RNAi screening has been the importance of making sure that hits from the screens carried out already. In the case of high throughput are not due to crossreaction, most readily by using screens, judicial pooling of RNAi oligos or constructs different sequences targeting the same gene in a against two or three very closely related proteins might secondary screen and in the subsequent follow-up. All alleviate this. However, in selective screens using large hits from these screens require extensive follow-up, so in viral pools, this is unlikely to be workable as each cell practice this is not much of an added burden. While the takes up only a very small number of viruses from the studies cited above studied mRNA degradation, it is far complex pool and the chances of getting the desired less clear how much off-target activity might result from combination would be very low. inhibition of mRNA by imperfectly matched sequences, so-called micro RNA effects (He and Low efficiency of knock down As the algorithms for Hannon, 2004). selecting optimal sequences for RNAi improve, this The major concern with sequence-independent effects problem may recede. This is a particular concern with is the induction of responses (Bridge et al., vector-based RNAi, which tends to be less efficient than 2003). It is still unclear how significant this problem synthetic oligonucleotide-driven silencing. Stable expres- is, but it is relatively simple to incorporate an assay for sion of RNAi vectors tends to be still less efficient at interferon induction as part of follow-up screens, silencing than transient, making this problem the for example quantitative PCR for expression of an greatest for selective screens. In selective screens using interferon-induced gene such as OAS1. All off-target complex viral mixtures, it is highly likely that cells will effects will be concentration dependent, so it is only carry one integrated copy of any given construct, so important to use no more siRNA agent than necessary, this must be capable of providing an effective knock especially in transient expression screens.

Oncogene Use of RNAi in oncogenic signalling J Downward 8382 Conclusions and future prospects particular, involving developments in fluorescence microscopy, is also greatly strengthening the power The use of RNA interference in mammalian cells is and versatility of these screens. Of the two assay only 3 years old, but it has already been scaled up such strategies, high throughput and selective, high through- that the function of very significant fractions of the put screening is clearly the most versatile, and can be genome can be interrogated using RNA interference adapted to investigate a very wide range of biological libraries. Several groups have been quick to see the phenomena. In particular, it can readily be used to potential of this approach to the discovery of novel study several of the major characteristics associated components of signalling pathways important in with cancer. By contrast, the potential use of selective cancer, some of which may prove to be useful new screens is much more limited due to the requirement for drug targets. While some important findings have a stringent elimination of all cells apart from those with already been reported, it is clear that the methodology the desired phenotype during the course of the assay. used so far is in its infancy, although it is developing This can be very challenging to achieve and would rule very fast. The two large mammalian vector-based RNA out straightforward assays for reversion for transfor- interference libraries reported to date have significant mation. However, when successfully designed, they can limitations and probably should be viewed only as deliver novel components of pathways that may be prototypes, but will no doubt lead to the development important in cancer, especially in restraint of transfor- of new generation libraries with much improved mation. It is clear that the near future will see a great efficiency. Rapid improvements in our understanding increase in the use of the RNA interference library of what sequences are likely to induce effective knock- approach to study cancer and may well start to uncover down of gene expression will greatly improve the large numbers of potential new therapeutic targets that effectiveness of both vector- and oligonucleotide-based would have taken a very long time to find by previous libraries. In addition, improved assay technology, in methodology.

References

Abbas-Terki T, Blanco-Bose W, Deglon N, Pralong W and Dirac AM and Bernards R. (2003). J. Biol. Chem., 278, Aebischer P. (2002). Hum. Gene. Ther., 13, 2197–2201. 11731–11734. Arts GJ, Langemeijer E, Tissingh R, Ma L, Pavliska H, Downward J. (2004). BMJ, 328, 1245–1248. Dokic K, Dooijes R, Mesic E, Clasen R, Michiels F, van der Dykxhoorn DM, Novina CD and Sharp PA. (2003). Nat. Rev. Schueren J, Lambrecht M, Herman S, Brys R, Thys K, Mol. Cell. Biol., 4, 457–467. Hoffmann M, Tomme P and van Es H. (2003). Genome. Elbashir SM, Harborth J, Lendeckel W, Yalcin A, Weber K Res., 13, 2325–2332. and Tuschl T. (2001). Nature, 411, 494–498. Aza-Blanc P, Cooper CL, Wagner K, Batalov S, Deveraux QL Elbashir SM, Harborth J, Weber K and Tuschl T. (2002). and Cooke MP. (2003). Mol. Cell, 12, 627–637. Methods, 26, 199–213. Berns K, Hijmans EM, Mullenders J, Brummelkamp TR, Gupta S, Schoer RA, Egan JE, Hannon GJ and Mittal V. Velds A, Heinerikx M, Kerkhoven RM, Madiredjo M, (2004). Proc. Natl. Acad. Sci. USA, 101, 1927–1932. Nijkamp W, Weigelt B, Agami R, Ge W, Cavet G, Hannon GJ. (2002). Nature, 418, 244–251. Linsley PS, Beijersbergen RL and Bernards R. (2004). He L and Hannon GJ. (2004). Nat. Rev. Genet., 5, Nature, 428, 431–437. 522–531. Bridge AJ, Pebernard S, Ducraux A, Nicoulaz AL and Iggo R. Jackson AL, Bartz SR, Schelter J, Kobayashi SV, Burchard J, (2003). Nat. Genet., 34, 263–264. Mao M, Li B, Cavet G and Linsley PS. (2003). Nat. Brummelkamp TR and Bernards R. (2003). Nat. Rev. Cancer, Biotechnol., 21, 635–637. 3, 781–789. Khvorova A, Reynolds A and Jayasena SD. (2003). Cell, 115, Brummelkamp TR, Bernards R and Agami R. (2002a). Cancer 209–216. Cell, 2, 243–247. Kumar R, Conklin DS and Mittal V. (2003). Genome Res., 13, Brummelkamp TR, Bernards R and Agami R. (2002b). 2333–2340. , 296, 550–553. Paddison PJ, Caudy AA, Bernstein E, Hannon GJ and Brummelkamp TR, Nijman SM, Dirac AM and Bernards R. Conklin DS. (2002a). Genes Dev., 16, 948–958. (2003). Nature, 424, 797–801. Paddison PJ, Caudy AA and Hannon GJ. (2002b). Proc. Natl. Chen Y, Stamatoyannopoulos G and Song CZ. (2003). Cancer Acad. Sci. USA, 99, 1443–1448. Res., 63, 4801–4804. Paddison PJ, Silva JM, Conklin DS, Schlabach M, Li M, Chi JT, Chang HY, Wang NN, Chang DS, Dunphy N Aruleba S, Balija V, O’Shaughnessy A, Gnoj L, Scobie K, and Brown PO. (2003). Proc. Natl. Acad. Sci. USA, 100, Chang K, Westbrook T, Cleary M, Sachidanandam R, 6343–6346. McCombie WR, Elledge SJ and Hannon GJ. (2004). Nature, Cui W, Ning J, Naik UP and Duncan MK. (2004). Comput. 428, 427–431. Methods Prog. Biomed., 75, 67–73. Reynolds A, Leake D, Boese Q, Scaringe S, Marshall WS and Czauderna F, Santel A, Hinz M, Fechtner M, Durieux B, Khvorova A. (2004). Nat. Biotechnol., 22, 326–330. Fisch G, Leenders F, Arnold W, Giese K, Klippel A and Rubinson DA, Dillon CP, Kwiatkowski AV, Sievers C, Kaufmann J. (2003). Nucleic Acids Res., 31, e127. Yang L, Kopinja J, Rooney DL, Ihrig MM, McManus Denli AM and Hannon GJ. (2003). Trends Biochem. Sci., 28, MT, Gertler FB, Scott ML and Van Parijs L. (2003). Nat. 196–201. Genet., 33, 401–406.

Oncogene Use of RNAi in oncogenic signalling J Downward 8383 Schwarz DS, Hutvagner G, Du T, Xu Z, Aronin Nand Agami R and Clevers H. (2003). EMBO Rep., 4, Zamore PD. (2003). Cell, 115, 199–208. 609–615. Silva JM, Mizuno H, Brady A, Lucito R and Hannon GJ. Wang L and Mu FY. (2004). Bioinformatics, 20, 1818–1820. (2004). Proc. Natl. Acad. Sci. USA, 101, 6548–6552. Weinstein IB. (2002). Science, 297, 63–64. van de Wetering M, Oving I, Muncan V, Pon Fong MT, Wiznerowicz M and Trono D. (2003). J. Virol., 77, 8957–8961. Brantjes H, van Leenen D, Holstege FC, Brummelkamp TR, Zhao LJ, Jian H and Zhu H. (2003). Gene., 316, 137–141.

Oncogene