artykuł 4.pdf

Oncogene (2004) 23, 8376–8383

www.nature.com/onc

Use of RNA interference libraries to investigate oncogenic signalling

in mammalian cells

Julian Downward* ,1

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

Over the past decade, ‘RNA interference’ has emerged as

a natural mechanism of silencing of gene expression. This

ancient cellular antiviral response can be manipulated to

provide an effective research tool to knock down the level

of expression of selected target genes, providing a very

powerful new method for the analysis of cell signalling

pathways. Systematic silencing of genes on a genome-wide

scale using large rationally designed libraries targeting

many thousands of genes provides a novel functional

genomics approach to the investigation of many aspects of

mammalian cell behaviour, including oncogenic transfor-

mation. Here, the different approaches taken to use RNA

interference libraries to study the cancer phenotype will be

considered, including both selective and high throughput

screens and the use of both vector-based and synthetic

oligonucleotide-based methods for inducing RNA inter-

ference. The advantages and drawbacks of the competing

methodologies will be discussed. RNA interference library

technology holds great promise for enabling somatic cell

genetics in tissue culture systems. Whether it can provide

signiﬁcant newinsights into cancer will be its greatest

challenge.

Oncogene (2004)23,8376–8383.doi:10.1038/sj.onc.1208073

RNA-inducedsilencingcomplex(RISC),whichusesone

strand to target complementary mRNA molecules for

degradation.

Artiﬁcial introduction of siRNA duplexes into cells

can thus silence the expression of selected genes. A

number of methods have been developed for getting

siRNAs of a desired sequence into target mammalian

cells. The two most commonly used are to transfect in

synthetic short double-stranded RNA molecules of the

desired sequence, which then act to engage RISC

directly (Elbashir et al., 2001). Alternatively, expression

vectors can be introduced into cells, either by transfec-

tionortheuseofviruses,whichdirecttheproductionof

short hairpin RNA sequences that are then processed

into siRNA within the cell by endogenous enzymes

(Brummelkamp et al., 2002a,b; Paddison et al.,

2002a,b).

Both of these methods of harnessing RNA inter-

ference have recently been used on a large scale as a

functional genomic tool in mammals, and have been

used for longer periods in lower eukaryotes. System-

atically silencing genes one by one corresponding to a

large fraction of the genome allows the identiﬁcation of

genes that are required for a particular phenotype to

occur. In the case of cancer, if genes could be identiﬁed

in this way, as required for the maintenance of the

transformed phenotype, the proteins they encode might

make excellent targets for the development of therapeu-

tic drugs. This promise has led to the development of a

numberoflarge collections ofRNA interference vectors

or synthetic oligonucleotides. These are being used in

two different types of screens: high throughput and

selective. In the former, each assay point corresponds to

induction of RNA interference against a single gene,

with a phenotypic change being assayed for (Aza-Blanc

et al., 2003; Brummelkamp et al., 2003; Paddison et al.,

2004). In the latter, many genes are silenced at the

same time in a mixed pool of cells, with the screen

being designed in such away that only cells acquiring

the desired phenotype as a result of knock down of

expression of one of these genes can survive: these cells,

along with the RNAi sequence they carry are then

identiﬁed as they emerge at the end of the screen (Berns

et al., 2004).

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

competing methodologies will be discussed.

Keywords: RNA interference; screening; transforma-

tion; library; oncogenesis

Introduction

RNA interference was ﬁrst described in plants in 1990

and has subsequently been found as a mechanism of

gene silencing in most multicellular eukaryotes. The

mechanistic basis for the silencing of gene expression

by RNA interference has been described in great detail

and has been the subject of numerous recent reviews

(Hannon, 2002; Denli and Hannon, 2003; Dykxhoorn

et al., 2003; Downward, 2004), so will not be discussed

in depth here. In a nutshell, double-stranded RNA

molecules in the cell are cleaved by the Dicer enzyme

complex to form small interfering (si) double-stranded

RNA molecules, which are some 20 base pairs long.

These are recognized by another enzyme complex, the

*Correspondence: J Downward; E-mail: downward@cancer.org.uk

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RNA interference library design

per gene. Recently developed proprietary software from

Cenix BioScience has been reported to achieve a 470%

gene silencing efﬁciency with 480% of over 1000

siRNA oligos (http://www.ambion.com/techlib/tn/113/

14.html), raising the possibility that only one optimally

designed oligo per gene could be used to make up

an effective genome scale library. As more siRNA

sequences are experimentally validated for mRNA

knockdown, this approach will become more reliable.

In addition to testing siRNA oligos for their effect on

expressionofendogenoustargetgenes,itisalsopossible

to rapidly screen them against hybrid mRNA fused to a

reporter construct (Kumar et al., 2003).

The use of multiple siRNA oligos for each gene raises

the issue of whether they should be used singly or as

pools with other oligos targeting the same gene. In

addition to reducing the number of assays that need to

be performed in a screen, an advantage of pooling three

or four oligos together is that one maximizes the chance

of using an oligo that knocks down expression very

effectively. Concerns about the use of pools have

focused on the possibility of increasing the likelihood

of occurrence of off-target effects. However, as these

effects are thought to be dose dependent, if the total

oligo concentration applied to the cells remains con-

stant,poolsmaybe lesslikelytoproducesigniﬁcantoff-

target effects than single oligos. Whether this turns out

tobetrueornot,theimportanceofverifyingeffectswith

a second siRNA sequence against the same gene means

that if the library used is only available as pools of

oligos, secondary follow-up assays will require the

acquisition of individual siRNA oligos, which may

incur extra cost and delay.

As RNA interference targets mRNA in the cyto-

plasm, different siRNAs can be used to target different

splice variants transcribed from the same gene. Given

the high level of alternative splicing in mammalian

genomes, a library targeting all possible splice variants

individually would need to be much larger than one

targeting common exons.

The high degree of speciﬁcity of RNA interference

coupled with the considerable differences in sequence

between human and rodent genes makes it very unlikely

that a library designed against one species would work

effectively on the other. Different libraries will need to

be designed for each species studied, although it is

possible that some degree of crossreaction will be seen

with closely related species.

Oligonucleotide libraries

Theprincipalvariableinthedesignofalarge-scalesmall

interfering double-stranded oligoribonucleotide (siR-

NA) collection is the choice of the sequences used to

target each gene. In addition, the level of redundancy

with which the library is designed will have major

implications, both in terms of cost and the design of

experiments that can be performed with it. How many

oligos are used to target each gene will depend on the

likelihood that any given oligo will successfully knock

down its cognate mRNA.

The original criteria for designing siRNA sequences

werelaiddownasasimplesetofempiricalguidelinesby

Tuschl in 2001 (Elbashir et al., 2001). Subsequently, a

combination ofincreasedunderstandingofthestructure

and function of the RISC complex and an empirical

analysis of the efﬁciency of RNA interference induction

by very large numbers of siRNA oligos has led to

considerableimprovementsinsiRNAdesignalgorithms.

Recently, optimized design criteria have been published

by a number of groups (Elbashir et al., 2002; Khvorova

et al., 2003; Schwarz et al., 2003; Reynolds et al., 2004).

Criteria for effective RNA interference include: low

G þ C content (30–50%), low internal stability at 5 0

antisense strand, high internal stability at 5 0 sense

strand, absence of internal repeats or palindromes, A-

form helix between target mRNA and siRNA, presence

ofAatposition3,Uatposition10andAatposition19

of sense strand, absence of G at position 13 and G or C

at position 19 of sense strand, and lack of close

homology to other gene sequences.

PubliclyavailablesiRNAdesignalgorithmshavebeen

created based on these criteria (Cui et al., 2004; Wang

and Mu, 2004). A selection of siRNA design algorithms

readily available via the internet are: EMBOSS siRNA

algorithm (http://athena.bioc.uvic.ca/cgi-bin/emboss.

pl?_action ¼ input&_app ¼ sirna),PromegasiRNATarget

Designer (http://www.promega.com/siRNADesigner/

program/), GeneScript siRNA target ﬁnder (https://

www.genscript.com/ssl-bin/app/rnai), Ambion siRNA

predictor (http://www.ambion.com/techlib/misc/silencer_

siRNA_template.html), OligoEngine siRNA software

(http://www.oligoengine.com/Home/mid_prodSirna.html

#sirna_tool), Whitehead siRNA prediction (http://jura.

wi.mit.edu/pubint/http://iona.wi.mit.edu/siRNAext/),

Sfold rational siRNA design (http://sfold.wadsworth.

org/index.pl), Hannon Lab RNAi OligoRetriever

(http://katahdin.cshl.org:9331/RNAi/html/rnai.html),

Sonnhammer Bioinformatics Group siSearch siRNA

design(http://sonnhammer.cgb.ki.se/siSearch/siSearch_1.

4.html).

Most publicly accessible siRNA design programs are

likely to predict siRNA oligo sequences that will silence

gene expression reasonably efﬁciently (470% reduction

in cognate mRNA) about 50–60% of the time. The use

of three such oligos against each gene provides a high

probability of success, but does require considerable

extra expenditure compared to the use of just one oligo

Vector libraries

Similar criteria to the above are used in the design of

short hairpin RNA sequences for vector-based RNA

interference. However, a critical factor in the success or

otherwise of these libraries is the choice of vector

backbone. The two large mammalian vector-based

RNA interference libraries that have been reported to

date use constructs that can be introduced into cells

either as retroviral particles or by DNA transfection

(Berns et al., 2004; Paddison et al., 2004). Berns et al.

used pRETRO SUPER, a retroviral vector in which the

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sequence encoding the shRNA hairpin is driven by

RNA polymerase III acting on the H1 RNA gene

promoter (Brummelkamp et al., 2002a). The gene

sequence-speciﬁc inserts are designed to form hairpins

with 19 base pairs of double-stranded RNA, plus a

nine nucleotide invariant loop. The vector carries a

puromycin-resistance marker. Three sequences were

targeted in each of the 7914 human genes.

Paddison et al. used a different retroviral vector,

pSHAG MAGIC, in which the sequence encoding the

hairpin is driven by RNA polymerase III acting on the

U6 RNA gene promoter. In all, 29 base pair hairpins

were used, with a four nucleotide loop. A 27-nucleotide

U6 RNA leader sequence was also included as this was

foundtoimproveknockdownefﬁciency.Thevectoralso

carries puromycin resistance and has a separate unique

60-nucleotide ‘barcode’ built in (see below). To aid in

manipulation of the vectors, a recombination system

is built into the vector (‘Mating-assisted genetically

integrated cloning’) that allows easy exchange of the

hairpin sequences between different vector backbones.

In all, 9610 human genes and 5563 mouse genes were

targeted, mostly with threefold redundancy.

Inadditiontothesetwovectors,awiderangeofother

RNAinterferencevectorshavebeendesignedthatcould

be used for library construction. Incorporation of a

ﬂuorescent marker such as GFP could be useful in

alibrarytoallowassessmentoftransfectionefﬁciency:a

number of commercial RNAi vectors include this

feature, including constructs derived from pRETRO

SUPER by Oligoengine, the pSIREN s series from BD

BiosciencesClontech,andtheGeneSilencer s seriesfrom

Gene Therapy Systems, Inc. Alternatively, a different

viral delivery system could be used, such as adenoviral

RNAi vectors (Arts et al., 2003; Zhao et al., 2003),

available from BD Biosciences Clontech, Ambion and

Invitrogen, or lentiviral vectors (Abbas-Terki et al.,

2002; Dirac and Bernards, 2003; Rubinson et al., 2003),

available from Invitrogen. Adenoviral vectors are likely

to achieve higher levels of expression of the shRNA,

while lentiviral vectors will enable expression in

nonproliferating cells.

A further future development that could potentially

be useful in a vector-based RNA interference library is

the incorporation of inducibility. Several tetracycline-

inducible RNAi vectors have been reported, both

plasmid based (Chen et al., 2003; Czauderna et al.,

2003; van de Wetering et al., 2003) and lentivirus based

(Wiznerowicz and Trono, 2003). An ecdysone-inducible

RNA interferencesystemhasalsobeenreported(Gupta

et al., 2004). It is not yet clear whether these systems are

sufﬁciently robust to work effectively on a large scale

without individual optimization.

mode using oligos or vectors, one gene at a time, or in a

selective mode using large pools of vectors (Figure 1).

Highthroughputscreeninghasanumberofadvantages,

but also some drawbacks.

To screen on a genome-wide scale in high throughput

mode can be a daunting prospect, as it requires many

thousands of assays to be performed. This is likely to be

timeconsumingandcostly.Itisessentialthatscreensare

designed to minimize these two factors. This requires

that assays are highly robustandreproducible, reducing

the need for multiple replicates or rescreens. All high

throughput RNAi screens performed to date have used

some sort of ﬂuorescent readout, which has the

advantage of being very easy to measure. It is also

important that good positive controls exist to optimize

the assays.

Cost considerations also favour assays that can be

performed on a very small scale, such as a 96- or 384-

well plate format. Aza-Blanc et al. (2003) used a library

of 510 siRNA oligos to transfect HeLa cells in 384-well

platesandthentestthemforTRAIL-inducedapoptosis,

using a cell viability assay with a ﬂuorescent readout.

This assay successfully identiﬁed several modulators of

the apoptotic response, some of which might possibly

be misregulated during carcinogenesis. The amount of

siRNA oligo transfected was about 10pmoles/well,

meaning that commercially supplied libraries, for

example, from Dharmacon, Ambion, or Qiagen, which

typically provide 2nmoles as standard, would in theory

be sufﬁcient for about 200 screen runs. While the costs

ofthesecommerciallibrariesmayappearprohibitivefor

academic users, the potential for sharing them between

several labs may help alleviate this somewhat. When

considering costs, it should also be noted that synthetic

oligos and plasmids both require the use of transfection

reagents such as lipofection mixes for introduction into

cells. Large-scale screening can consume a lot of these

expensive consumables and should be factored into any

costing of the screen.

Other ways of stretching valuable resources even

further can be achieved using reverse transfection in a

microarray format. In a series of screens to investigate

proteasome function and cytokinesis, both potentially

important in carcinogenesis, Silva et al. (2004) spotted

siRNA oligos, and also plasmids, in a gelatin solution

along with transfection reagent onto glass slides. Cells

were overlaid onto the spotted array and took up the

siRNAs, showing signiﬁcant transient knock down of

the expression of the target genes and resulting

phenotypic changes. In this way, very small amounts

of reagents are used and large numbers of assay

transfections can be achieved at one time, providing

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

transfected cells. This is less of a problem with synthetic

siRNAoligosthanwithplasmid-basedshRNAvectors–

for which Silva et al. solved the problem by using 293

cells, although these are not ideal for the study of many

signalling pathways. The other limitation is that cell

RNA interference library use

High throughput screening with oligonucleotide libraries

As mentioned in the introduction, RNA interference

library screens can be carried out in a high throughput

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Arrayed RNAi libraries

Pooled RNAi libraries

viral vectors

Another screen of this kind performed with relevance

to cancer identiﬁed the familial cylindromatosis tumour

suppressor gene product as a deubiquitinating enzyme

important in the regulation of NF-kB (Brummelkamp

et al., 2003). This small-scale screen focused on genes

with sequence homology to known deubiquitinating

enzymes. U2-OS cells were transiently cotransfected

withanNF-kBluciferasereporterconstructandshRNA

vectors individually targeting 50 candidate human

deubiquitinating enzymes. The cells were then treated

with TNF-a and NF-kB was activity measured by

luciferase ﬂuorescence. Targeting the CYLD gene led to

upregulationoftheNF-kBresponse,suggestingthatthe

benign tumours commonly seen in familial cylindroma-

tosis patients may be due to increased antiapoptotic

signalling by NF-kB.

More complex readouts can be measured in these

screens than simply a ratio of ﬂuorescence at two

wavelengths. Recently, several companies have devel-

oped automated ﬂuorescent microscopy systems, for

example, the INCell Analyser 1000 and 3000 from

Amersham Biosciences and the Discovery-1 from

Molecular Devices. These allow, among other things,

the automated measurement of the distribution of a

ﬂuorescent protein between different cellular compart-

ments,suchasthecytosolandthenucleusorthecytosol

and the plasma membrane. Such measurements can be

performed rapidly in a multiwell format and can add

considerable ﬂexibility to the design of high throughput

RNAi screens.

A promising approach to screening for potential

cancertherapeutictargetsusingthesemethodsistolook

for synthetic lethality between a transforming oncogene

and an siRNA. At its simplest, this would involve

screening closely related normal and oncogene-

transformed cells with an siRNA library looking for

cell death, or less optimally arrest, speciﬁcally in the

untransformed but not the normal cells. Owing to the

fact that the microevolutionary process involved in

cancer formation tends to result in the cancer cells

becoming dependent on oncogenic signalling for their

continued survival – a process termed ‘oncogene

addiction’ (Weinstein, 2002) – such screens may reveal

targets that would allow selective killing of the tumour

cells.

synthetic oligos

plasmid vectors

viral vectors

transfect

package,

infect

package,

infect

High throughput assay

for altered phenotype(s)

Selective screen for

altered phenotype

Secondary assay to validate hits

Amplify barcodes,

Fluorescently label,

with barcode oligos

Sequence hairpins

or barcodes

to identify hits

Hybridise to microarray

Secondary assay to

validate hits

Figure 1 Different approaches to large-scale RNA interference

screens. See text for details

motility will restrict how long cells can be followed and

how close together elements can be placed.

Once hits have been identiﬁed in a high throughput

screen, a good secondary screen is needed to check out

their signiﬁcance. As the ﬁrst assay will ideally give a

numerical value, consideration should be given to how

big a change from the negative control is needed to be

worth pursuing in the secondary screen. This will be

inﬂuenced by the overall size of the initial screen, the

ease with which the secondary screen can be carried out

and the level of conﬁdence in the initial results. The

secondary screen can be designed to rule out possible

off-target effects of the siRNA oligos: for example,

using a different sequence against the same gene, or

deconvoluting a pool of oligos against the same gene

into their individual components.

High throughput screening with vector libraries

Many of the same considerations as those above exist

forhighthroughputscreensusingvector-basedlibraries.

The major difference is that due to the much lower

transfection efﬁciency of plasmids compared to oligos,

it is necessary to mark the transfected cells so that

their behaviour can be distinguished from that of the

untransfected cells, or to give a measure of the trans-

fection efﬁciency of the whole cell population in that

assaysamplefornormalizationpurposes.Paddison et al.

(2004) performed a high throughput vector library

screen of proteasome function by cotransfecting 293

cells with individual shRNA plasmids, a DsRed

ﬂuorescent protein encoding plasmid and an ZsGreen

ﬂuorescentproteinfusedtoaPESTsequencecontaining

degronfrommouseornithinedecarboxylase.Innegative

controls, the PEST sequence ensures proteasome-

mediated degradation of the ZsGreen ﬂuorescent

protein fusion, giving a high ratio of red to green

ﬂuorescence. Any shRNA plasmid that leads to pro-

teasome malfunction promotes the levels of ZsGreen

and thus reduces the ratio of red to green ﬂuorescence.

The screen performed impressively, identifying a high

proportion of known proteasomal subunit from a

library of 7000 shRNAs tested.

Selective screening with vector libraries

The other major assay mode used with RNA inter-

ference libraries is the selective screen. A selective

pressure is applied that will cause negative control cells

to die, growth arrestor insome otherwaybe eliminated

from the culture. The only cells that can survive and

expand in the culture are those that have received an

RNAi sequence that knocks down a gene needed for

sensitivity to the selective pressure. The resistant cells

can be grown and the sequence of the RNAi sequence

determined. The dual constraints of needing relatively

long-term selections and having to be able to determine

the RNAi sequence present in the resistant cells limits

this screening methodology to vector-based RNAi and

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not synthetic oligos. The ﬁnal determination of the

RNAi sequence in the resistant cells is carried out by

PCR ampliﬁcation and sequencing of the gene-speciﬁc

insert from invariant primers based on the vector

backbone sequence. This can either be carried out on

single clones or on populations of resistant cells.

Themajorexampleofthistypeofscreentodatewasa

selectionforRNAisequencesthatwouldallowescapeof

human diploid ﬁbroblasts from p53-mediated senes-

cence(Berns et al.,2004).HumanBJprimaryﬁbroblasts

expressing telomerase were conditionally immortalized

using temperature-sensitive SV40 large T antigen. Upon

shift to the nonpermissive temperature, the cells senesce

unless they havereceived anRNAisequence thatblocks

this response. Six novel hits were identiﬁed that

appeared to play a role in p53-mediated senescence.

There are several advantages to the use of selective

screens.Amajoroneistheabilitytopoollargenumbers

of RNAi vectors together, allowing only a relatively

small number of pools to be screened. While this is

potentially very useful, these screens have signiﬁcant

limitations. Since the aim of pooling is to achieve a

complex mixture of cells each carrying a very small

numberofRNAisequences,ratherthanahomogeneous

mixture of cells all carrying a very complex mixture of

RNAi sequences, this is only possible with viral-

mediated delivery and not with transfection. Viral

delivery into human cells normally requires high-level

biological containment, but this can be avoided in the

case of retroviruses by packaging into an ecotropic

delivery system that will only infect mouse cells and

using these to screen human cells that have been

engineered to express the mouse ecotropic retrovirus

receptor (see Berns et al., 2004).

It is hard to assess optimal RNAi pool sizes for these

screens. Ideally, a good positive control RNAi vector

should be available from knowledge of the system

studied. This can then be mixed into increasingly large

poolsizesatthesameratioastheothercomponentsand

tested to see what pool size still allows unequivocal

detectionofthepositivecontrol.Atypicalpoolsizeused

is about a 100 genes; in the case of the NKI library, this

was made up of some 300 different retroviruses,

allowing for the threefold redundancy (Berns et al.,

2004).

Viablepoolsizewillalsobestronglydependentonthe

background level of false positives: high backgrounds

will severely limit the possible degree of pooling used

and require larger numbers of individual assays. In

practice, one of the greatest constraints on this type of

screen is provided by the need for low background

levels. One approach to easing this is to perform screens

iteratively. Ideally this is done by isolating the RNAi

sequence inserts from resistant cells, for example, by

PCR in the case of the NKI library. This mix of inserts

can then be recloned into the RNAi vector and

reintroduced into a fresh population of parental cells,

which are reselected. This can be repeated a number of

times until a limited number of sequences are repro-

ducibly obtained. While this process is time consuming,

it can alleviate background problems. There is limited

valueto reapplyingselective pressureto cellpopulations

that have already been selected, as there is no

differential selection against the false positives thathave

already accumulated. Backgrounds can sometimes be

reduced by screening a number of single-cell clones of

parental cells for low background levels in response to

the selective pressure.

As with the high throughput screens, a good

secondary screen is very important for verifying hits.

Again, this is a good stage at which to check that a

different sequence targeted against the same gene can

give a positive result, reducing the likelihood of off-

target effects. It is also useful to check that in both

primary and secondary screens, the induction of a

positive phenotype is associated with knockdown of the

presumed target mRNA. This also applies to high

throughput screens, but is particularly important when

using vector-based systems in a stable, rather than

transient, manner where knockdown efﬁciencies tend to

be lower. A consequence of this is that the secondary

screen here may need to repeat the whole selection

protocol to allow cells with a good level of target

knockdown to emerge, rather than assuming that all

cells receiving the identiﬁed RNAi construct will show

sufﬁciently good knockdown to score as phenotypically

positive.

A speciﬁc problem with selective screens with regard

to research into the acquisition and maintenance of the

cancer phenotype is that they tend to operate in the

reversedirectiontothatwhichonewouldwant.Bytheir

very nature, cancer cells are able to prosper under

circumstances where normal cells do not. For example,

they will grow without attachment or without serum.

An ideal screen would be to select for loss of the

transformedphenotype,butthereareveryfewselections

that will efﬁciently yield up normal cells against a

background of transformed cells, whereas many that

will do the reverse. One possibility is to screen for genes

that when knocked down will promote transformation

in the hope that these will be biologically signiﬁcant

tumour suppressor genes. While these are unlikely to

provide therapeutic targets directly, they might yield

signiﬁcantprognosticmarkersorpointtotheidentityof

enzymes that reverse their activity, which could be

promising cancer drug targets.

Screening using barcodes

A possible way around the difﬁculty of selecting for a

normal cell phenotype from a transformed cell back-

ground may be offered by combining selective screens

with microarray technology. This strategy, termed

‘barcode’ screening (Brummelkamp and Bernards,

2003; Berns et al., 2004; Paddison et al., 2004), makes

use of a gene-speciﬁc sequence incorporated into each

shRNA vector in the library. In the case of the CSHL

library (Paddison et al., 2004), this sequence is separate

from the short hairpin sequence, while in the case of the

NKIlibrary,itistheshorthairpinsequenceitself(Berns

et al., 2004). Pools of vectors are introduced into cells,

whicharethenselected,forexample,byastressthatcan

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