One of the fruits of the genomic age has been the development of powerful genetic techniques that enable interrogation of protein function. Genome-wide, pathway-focused (targeting apoptosis, kinases and phosphatases), and custom made-to-order RNAi libraries are commercially available in siRNA and shRNA formats. Whereas siRNA elicits short-term knockdown (2–5 days) and delivery is limited to cell types that may be easily transfected, shRNA libraries may be transduced (using viral particles) into cell types that are difficult to transfect, enabling stable knockdown and facilitating screens of longer duration.
Commercial RNAi libraries are available in pooled or well formats. The experimental setups for pool- and well-based experiments are illustrated in ; these experiments can implicate a protein in mediating the effect of a compound. For example, the cells transfeced/transduced with the interfering RNA can be treated with an anticancer compound at a concentration know to give quantitative cell death. Any surviving cells, therefore, must have an mRNA knocked down that was important in the cell death induced by the compound.
An overview of the (A) pooled- and (B) well-based format RNAi screen experiments.
Well-based experiments may require high-throughput screening intensive methods (depending on the library size), are typically more costly, but allow more freedom in the phenotype being investigated and are suited to both positive and negative selection screens. A variety of read-outs may be employed, including high-content imaging, flow cytometry, ELISA, and cell viability assays (). As an alternative to plate based assays, well-format libraries may be printed onto microarrays upon which adherent cells may be grown, and results observed using high content imaging techniques. In comparison to well-format RNAi, pooled-libraries are more cost-effective and screens can often be performed by a single researcher; however, the phenotypes that may be investigated are limited. In addition, the experimental protocol employed in pooled-library toxicity screens may bias them towards positive selection, although negative selection screens are possible if conditions are optimized.41
Pooled shRNA screens require transduction of cells such that the shRNA multiplicity of infection (MOI) is less than 1. The cells are split into two pools and one is treated with vehicle while the other is treated with the small molecule (). For screens involving toxic molecules, selection is typically performed over 2–3 weeks. The total genomic RNA is isolated, the shRNA constructs are amplified by PCR, and the half-hairpin sequences are then hybridized to complementary DNA microarrays. By comparing the levels of shRNA constructs in treated versus non-treated cells, it is possible to identify shRNAs that are enriched (positive selection) or depleted (negative selection) as a result of small molecule treatment ().
While genome-wide RNAi libraries may allow a systematic and unbiased approach to interrogating cell biology, there are pitfalls associated with RNAi such as lack of target-specificity and knockdown efficiency, which ultimately lead to false positives and false negatives, respectively. Both pooled and well-based libraries typically contain multiple constructs targeting the same gene, increasing the likelihood that a protein will be effectively targeted; this redundancy also helps discern likely true-positives from false-positives arising from off-target effects. Furthermore, as shRNA/siRNA constructs continue to be validated for knockdown efficacy, revised construct design will continue to improve the quality of RNAi libraries. Despite this, it is not always clear if mRNA knockdown is sufficient to modulate the cellular level of a protein such that its function is affected. Protein longevity, expression levels, and contribution to functional pathways in a particular cell line are factors that affect the success of RNAi-based experiments.
Despite these limitations, the use of RNAi libraries may significantly aid investigations of the mechanism of small molecules. As described below, several proof-of-principle studies have investigated compounds with known modes of action using RNAi screens. A particular appeal of this technique is the ability to identify key proteins that are the compound’s direct target, or regulators of the target. Evidence suggests that upstream proteins are more likely to be identified, as proteins considerably downstream of the direct target may be unable confer long-term survival, especially given that selections are performed over 2–3 weeks. Of course, if a protein’s down-regulation itself induces toxicity, this may preclude its identification as a small molecule target. A list of such proteins that may elude identification may be inferred from the study by Luo and coworkers, which identified 268 essential genes common to 12 cell lines.41
These genes were enriched for pathways involving ribosomal proteins, mRNA processing and splicing, translation factors and proteasome degradation.41
The ability of whole genome pooled shRNA barcode screens to reveal the molecular target of the small molecule etoposide () was demonstrated by Luo and coworkers using a 45,000 shRNA library that targeted 9,500 genes.41
H82 small-cell lung cancer cells were transduced with the shRNA library and treated with 1.7 µM etoposide for three weeks (10 independent transductions and treatments). This dose of etoposide was sufficient to kill >99% of treated cells within 7 days. PCR amplification of the shRNA constructs of surviving cells versus control untreated cells revealed 3 of the 5 shRNA constructs targeting topoisomerase II, the known target of etoposide, with >40 fold enrichment.
Small molecules and proteins that have been investigated in RNAi screens.
A positive selection screen (similar to etoposide) for gleevec-treated K562 cells transduced with a shRNA library was performed over 21 days by Luo and coworkers.41
A dose of 125 nM gleevec () was used, which was sufficient to kill >90% of the treated cells within the first 7 days of treatment. Bcr-Abl, the known target of gleevec, is essential for the survival of K562 cells and thus precluded its identification through this positive selective screen. PTPN1 was one of the genes identified to confer resistance. Encouragingly, this gene was also identified in a shRNA screen to identify genes that confer survival to Bcr-Abl RNAi in K562 cells.41
PTPN1 is a negative regulator of Bcr-Abl and shRNAs targeted against PTPN1 were able to increase phosphorylation of Bcr-Abl thus conferring resistance to gleevec. The shRNA screen thus identified a Bcr-Abl negative regulator that is involved in gleevec induced cell death.
Fas-Activating Antibody (Fas-Ab)
The identification of proteins involved in Fas-Ab induced Jurkat T cell death using a pooled whole genome shRNA positive selection screen was also performed by Luo and coworkers.41
The knockdown of FAS, FADD, and CASP8 genes were found to confer resistance to Fas-Ab. Fas, Fadd and caspase 8 form the death-inducing signaling complex (DISC) that is critical to initiating the extrinsic apoptotic pathway upon binding of Fas-Ab to the Fas receptor. Two novel genes, ARID1A and CBX1, were also identified in this screen whose knockdown prevented caspase-8 activation thus identifying their role upstream of caspase-8 activation in Fas-Ab induced apoptosis. In a separate study, Tsujji and coworkers identified CASP8, BID and FAS as genes whose knockdown prevented Fas-Ab mediated cell death in the D98/AH2 (derived from HeLa) cell line.42
The inability to identify FADD in this study may be due to technical differences in the experiment/RNAi library or cell line-specific effects.
In order to identify genes that play a role in nutlin-3 mediated cell death, a barcode pooled shRNA screen was conducted in MCF-7 (wild-type p53) breast cancer cells.43
Nutlin-3 () is a small molecule inhibitor of the MDM2-p53 protein-protein interaction. MDM2 binding to p53 inhibits p53-dependent apoptosis by suppressing transcriptional activation of p53 in response to DNA damage, exporting p53 out of the nuclease and targeting p53 for proteasomal degradation due to E3 ligase activity of MDM2. The shRNA screen was performed by treating cells with Nutlin-3 for 14 days at a concentration of 4 µM, was sufficient to induce cell cycle arrest without inducing apoptosis. Despite the use of non-toxic concentrations of nutlin-3, shRNAs that enabled cell proliferation would be amplified under these conditions. Several proteins involved in the p53-pathway were identified which included p53 itself, a p53 binding protein (53BP1), and a MDM2 target known to be a transcriptional activator of p53 (hnRNPK). Further shRNA experiments determined p53BP1 enables p53 transcriptional activity but does not affect induction of p53 protein. As 53BP1 is a component of the ATM-CHK-53BP1 pathway that induces p53 upon activation by DNA double strand breaks, it may explain why cancer cells are more susceptible to nutlin-3 as normal fibroblast cells exhibited considerably less 53BP1-containing nuclear foci than MCF-7 breast cancer cells. This data suggests that combination of nutlin-3 with DNA damaging anticancer agents should be avoided as this may result in undesired toxicity towards normal cells.
Gemcitabine combination therapy
In addition to mechanism elucidation, RNAi libraries may aid the identification of effective combination therapies. Gemcitabine (), a nucleoside analog that replaces cytidine during DNA replication and prevents the attachment of other nucleosides, is commonly used for the treatment of pancreatic cancer. Using the well-format Qiagen kinase siRNA library (2 siRNA constructs per kinase targeting 572 kinases), a screen was performed to identify kinases whose knockdown would potentiate gemcitabine toxicity in the MIA PaCa-2 pancreatic cancer cell line.44
Although several kinases were identified that modestly increased toxicity, two siRNA constructs targeting CHK1 were identified that were able to sensitize cells to gemcitabine by >10 fold. Using the small molecule inhibitors of CHK-1, SB 218078 and PD 407824, a 2.6 and 3.5 fold potentiation of gemcitabine was observed, respectively. CHK1, a protein kinase that was known to be activated upon DNA damage by gemcitabine, serves to induce cell cycle arrest and allow DNA repair and inhibition of CHK1 induces apoptosis by preventing DNA repair. The fact that CHK2 did not potentiate gemcitabine suggests that CHK2, unlike CHK1, is not involved in gemcitabine-induced DNA damage response and sheds further light on the mechanism of gemcitabine and functional differences between CHK kinases.
Apart from investigating the mechanism and potential therapeutic combination strategies, RNAi screens have aided the identification of mechanisms of resistance to the effects of small molecules. The resistance of ovarian cancer cell lines to carboplatin () was investigated in a siRNA screen targeting 90 genes associated with resistance to carboplatin/paclitaxel combination therapy.45
The candidate genes comprised of 39 genes enriched (>2 fold) in post-chemotherapy tumors versus primary tumors and 51 genes enriched (>2 fold) post-chemotherapy versus primary chemoresistant tumors. The screen identified the ENPP2 gene which encodes for autotoxin, a protein with lysophoslipase D activity, as a contributor to carboplatin resistance. Autotaxin produces the pro-survival factors, lysophosphatidic acid (LPA) and sphingosine 1-phosphate (S1P). Experiments using siRNA and a chemical inhibitor confirmed autotoxin inhibition accelerates carboplatin-induced apoptosis in ovarian cancer cells thus supporting the role of autotaxin in conferring resistance to carboplatin.
ABT-737 (), a potent inhibitor of the antiapoptotic proteins Bcl-2, Bcl-XL
and Bcl-w has demonstrated toxicity against small-cell lung carcinomas (SCLC) in culture and preclinical models.46
Some SCLC cell lines and cell lines derived from other cancers are, however, resistant to the effects of ABT-737.46
To identify the mechanism of ABT-737 resistance Lin and coworkers conducted a well-format siRNA screen against 4000 druggable genes using the NCI-H196 SCLC derived cell line.47
RNAi against FGFR2, TNFRSF13B, and PRDM13 were initially identified to confer sensitivity however testing of multiple constructs against these genes revealed the effects to be off-target as no correlation was observed between sensitivity to ABT-737 and the level of target gene knockdown.47
One of the major contributions to off-target effects arises from the complementation of nucleotides 2–8 of the antisense siRNA strand, otherwise known as the ‘seed’ region, and the 3’ UTR of unintended targets.48, 49
A BLAST analysis of the ‘seed’ regions of effective FGFR2, TNFRSF13B, and PRDM13 siRNA constructs suggested an overwhelmingly large number (343) of possible off-targets. However from this list, a particular Bcl-2 antiapoptotic protein, Mcl-1 was identified which had implicated in conferring resistance to ABT-737 in other studies. Mcl-1 is Bcl-2 family member protein that is not susceptible to inhibition by ABT-737. Further experiments confirmed that the effective siRNAs of FGFR2, TNFRSF13B, and PRDM13 induced off-target silencing of Mcl-1 and siRNAs against Mcl-1 were able to confer sensitivity to ABT-737. This study exemplifies one of the pitfalls associated with RNAi-based screening, and emphasizes the necessity of thorough experimental validation of candidate ‘hit’ genes.