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Utilizing RNA interference to enhance cancer drug discovery

Key Points

  • RNA interference (RNAi) allows for the specific silencing of genes. With the development of RNAi libraries, the effects of inhibiting specific genes can now be carried out in a high-throughput and systematic manner.

  • We survey the pros and cons of existing RNAi libraries and screening strategies, and also suggest the salient points to be considered when designing an RNAi screen.

  • RNAi screening is now showing potential as an invaluable tool in the process of target identification.

  • RNAi is also showing promise as a useful tool in target validation.

  • Although RNAi has already been used in target identification and validation processes, we suggest that it can also be used in the stages of compound identification and lead optimization.

  • There is particular utility in using RNAi to generate gene-expression signatures that characterize the specific inhibition of a potential drug target. These signatures can be compared to gene expression signatures from small-molecule inhibitors and can be used to identify more specific compounds. The signatures can also be used to understand the mechanism of action of small-molecule inhibitors.

  • Although RNAi is not a panacea to all of the rate-limiting steps of drug discovery, it does have potential in certain areas of this process. We discuss the limitations of RNAi screening and in particular, the problem of off-target effects.

Abstract

With the development of RNA interference (RNAi) libraries, systematic and cost-effective genome-wide loss-of-function screens can now be carried out with the aim of assessing the role of specific genes in neoplastic phenotypes, and the rapid identification of novel drug targets. Here, we discuss the existing applications of RNAi in cancer drug discovery and highlight areas in this process that may benefit from this technology in the future.

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Figure 1: The mechanism of experimental RNAi.
Figure 2: RNAi screening approaches.
Figure 3: Utilizing RNAi to enhance drug discovery.
Figure 4: Using RNAi screens to identify targets controlling the hallmarks of cancer.
Figure 5: Using the Connectivity Map to identify compounds targeting the same pathways as RNAi-screen hits.

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References

  1. Collins, I. & Workman, P. New approaches to molecular cancer therapeutics. Nature Chem. Biol. 2, 689–700 (2006).

    Article  CAS  Google Scholar 

  2. Kamb, A., Wee, S. & Lengauer, C. Why is cancer drug discovery so difficult? Nature Rev. Drug Discov. 6, 115–120 (2007).

    Article  CAS  Google Scholar 

  3. Pan, Q. et al. Protein kinase C epsilon is a predictive biomarker of aggressive breast cancer and a validated target for RNA interference anticancer therapy. Cancer Res. 65, 8366–8371 (2005).

    Article  CAS  Google Scholar 

  4. Horvath, S. et al. Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target. Proc. Natl Acad. Sci. USA 103, 17402–17407 (2006).

    Article  CAS  Google Scholar 

  5. Zhang, Z., Jiang, G., Yang, F. & Wang, J. Knockdown of mutant K-ras expression by adenovirus-mediated siRNA inhibits the in vitro and in vivo growth of lung cancer cells. Cancer Biol. Ther. 5, 1481–1486 (2006).

    Article  CAS  Google Scholar 

  6. Napoli, C., Lemieux, C. & Jorgensen, R. Introduction of a chimeric chalcone synthase gene into petunia results in reversible co-suppression of homologous genes in trans. Plant Cell 2, 279–289 (1990).

    Article  CAS  Google Scholar 

  7. Stram, Y. & Kuzntzova, L. Inhibition of viruses by RNA interference. Virus Genes 32, 299–306 (2006).

    Article  CAS  Google Scholar 

  8. Cerutti, H. & Casas-Mollano, J. A. On the origin and functions of RNA-mediated silencing: from protists to man. Curr. Genet. 50, 81–99 (2006).

    Article  CAS  Google Scholar 

  9. Meister, G. et al. Human Argonaute2 mediates RNA cleavage targeted by miRNAs and siRNAs. Mol. Cell 15, 185–197 (2004).

    Article  CAS  Google Scholar 

  10. Brummelkamp, T. R., Bernards, R. & Agami, R. A system for stable expression of short interfering RNAs in mammalian cells. Science 296, 550–553 (2002).

    Article  CAS  Google Scholar 

  11. Paddison, P. J., Caudy, A. A., Bernstein, E., Hannon, G. J. & Conklin, D. S. Short hairpin RNAs (shRNAs) induce sequence-specific silencing in mammalian cells. Genes Dev. 16, 948–958 (2002).

    Article  CAS  Google Scholar 

  12. Kanda, A. et al. Aurora-B/AIM-1 kinase activity is involved in Ras-mediated cell transformation. Oncogene 24, 7266–7272 (2005).

    Article  CAS  Google Scholar 

  13. Kortlever, R. M., Higgins, P. J. & Bernards, R. Plasminogen activator inhibitor-1 is a critical downstream target of p53 in the induction of replicative senescence. Nature Cell Biol. 8, 877–884 (2006).

    Article  CAS  Google Scholar 

  14. Paddison, P. J. et al. A resource for large-scale RNA-interference-based screens in mammals. Nature 428, 427–431 (2004). Describes one of the first of two large-scale RNAi screens in human cells.

    Article  CAS  Google Scholar 

  15. Berns, K. et al. A large-scale RNAi screen in human cells identifies new components of the p53 pathway. Nature 428, 431–437 (2004). Describes one of the first of two large-scale RNAi screens in human cells.

    Article  CAS  Google Scholar 

  16. Yang, D. et al. Short RNA duplexes produced by hydrolysis with Escherichia coli RNase III mediate effective RNA interference in mammalian cells. Proc. Natl Acad. Sci. USA 99, 9942–9947 (2002).

    Article  CAS  Google Scholar 

  17. Kittler, R. et al. An endoribonuclease-prepared siRNA screen in human cells identifies genes essential for cell division. Nature 432, 1036–1040 (2004).

    Article  CAS  Google Scholar 

  18. Kittler, R. et al. Genome-wide resources of endoribonuclease-prepared short interfering RNAs for specific loss-of-function studies. Nature Methods 4, 337–344 (2007).

    Article  CAS  Google Scholar 

  19. Graat, H. C. et al. Different susceptibility of osteosarcoma cell lines and primary cells to treatment with oncolytic adenovirus and doxorubicin or cisplatin. Br. J. Cancer 94, 1837–1844 (2006).

    Article  CAS  Google Scholar 

  20. Moffat, J. et al. A lentiviral RNAi library for human and mouse genes applied to an arrayed viral high-content screen. Cell 124, 1283–1298 (2006).

    Article  CAS  Google Scholar 

  21. MacKeigan, J. P., Murphy, L. O. & Blenis, J. Sensitized RNAi screen of human kinases and phosphatases identifies new regulators of apoptosis and chemoresistance. Nature Cell Biol. 7, 591–600 (2005).

    Article  CAS  Google Scholar 

  22. Silva, J. M., Mizuno, H., Brady, A., Lucito, R. & Hannon, G. J. RNA interference microarrays: high-throughput loss-of-function genetics in mammalian cells. Proc. Natl Acad. Sci. USA 101, 6548–6552 (2004).

    Article  CAS  Google Scholar 

  23. Bailey, S. N., Ali, S. M., Carpenter, A. E., Higgins, C. O. & Sabatini, D. M. Microarrays of lentiviruses for gene function screens in immortalized and primary cells. Nature Methods 3, 117–122 (2006).

    Article  CAS  Google Scholar 

  24. Brummelkamp, T. R. et al. An shRNA barcode screen provides insight into cancer cell vulnerability to MDM2 inhibitors. Nature Chem. Biol. 2, 202–206 (2006). A report on the first large-scale positive-selection barcode RNAi screen.

    Article  CAS  Google Scholar 

  25. Ngo, V. N. et al. A loss-of-function RNA interference screen for molecular targets in cancer. Nature 441, 106–110 (2006). A report on the first negative-selection barcode RNAi screen.

    Article  CAS  Google Scholar 

  26. Collins, C. S. et al. A small interfering RNA screen for modulators of tumor cell motility identifies MAP4K4 as a promigratory kinase. Proc. Natl Acad. Sci. USA 103, 3775–3780 (2006).

    Article  CAS  Google Scholar 

  27. Kaelin, W. G. Jr . The concept of synthetic lethality in the context of anticancer therapy. Nature Rev. Cancer 5, 689–698 (2005).

    Article  CAS  Google Scholar 

  28. Weinstein, I. B. Cancer. Addiction to oncogenes — the Achilles heal of cancer. Science 297, 63–64 (2002).

    Article  CAS  Google Scholar 

  29. Deininger, M., Buchdunger, E. & Druker, B. J. The development of imatinib as a therapeutic agent for chronic myeloid leukemia. Blood 105, 2640–2653 (2005).

    Article  CAS  Google Scholar 

  30. Davis, R. E., Brown, K. D., Siebenlist, U. & Staudt, L. M. Constitutive nuclear factor κB activity is required for survival of activated B cell-like diffuse large B cell lymphoma cells. J. Exp. Med. 194, 1861–1874 (2001).

    Article  CAS  Google Scholar 

  31. Sarthy, A. V. et al. Survivin depletion preferentially reduces the survival of activated K-Ras-transformed cells. Mol. Cancer Ther. 6, 269–276 (2007).

    Article  CAS  Google Scholar 

  32. Rottmann, S., Wang, Y., Nasoff, M., Deveraux, Q. L. & Quon, K. C. A TRAIL receptor-dependent synthetic lethal relationship between MYC activation and GSK3β/FBW7 loss of function. Proc. Natl Acad. Sci. USA 102, 15195–15200 (2005).

    Article  CAS  Google Scholar 

  33. Hanahan, D. & Weinberg, R. A. The hallmarks of cancer. Cell 100, 57–70 (2000).

    Article  CAS  Google Scholar 

  34. Westbrook, T. F. et al. A genetic screen for candidate tumor suppressors identifies REST. Cell 121, 837–848 (2005).

    Article  CAS  Google Scholar 

  35. Farmer, H. et al. Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature 434, 917–921 (2005).

    Article  CAS  Google Scholar 

  36. Hartwell, L. H., Szankasi, P., Roberts, C. J., Murray, A. W. & Friend, S. H. Integrating genetic approaches into the discovery of anticancer drugs. Science 278, 1064–1068 (1997).

    Article  CAS  Google Scholar 

  37. Torrance, C. J., Agrawal, V., Vogelstein, B. & Kinzler, K. W. Use of isogenic human cancer cells for high-throughput screening and drug discovery. Nature Biotech. 19, 940–945 (2001).

    Article  CAS  Google Scholar 

  38. Dolma, S., Lessnick, S. L., Hahn, W. C. & Stockwell, B. R. Identification of genotype-selective antitumor agents using synthetic lethal chemical screening in engineered human tumor cells. Cancer Cell 3, 285–296 (2003).

    Article  CAS  Google Scholar 

  39. Morgan-Lappe, S. et al. RNAi-based screening of the human kinome identifies Akt-cooperating kinases: a new approach to designing efficacious multitargeted kinase inhibitors. Oncogene 25, 1340–1348 (2006).

    Article  CAS  Google Scholar 

  40. Giroux, V., Iovanna, J. & Dagorn, J. C. Probing the human kinome for kinases involved in pancreatic cancer cell survival and gemcitabine resistance. FASEB J. 20, 1982–1991 (2006).

    Article  CAS  Google Scholar 

  41. Whitehurst, A. W. et al. Synthetic lethal screen identification of chemosensitizer loci in cancer cells. Nature 446, 815–819 (2007). Describes the first genome-wide chemosensitization siRNA screen with extensive validation and characterization of hits.

    Article  CAS  Google Scholar 

  42. Gupta, G. P. et al. Mediators of vascular remodelling co-opted for sequential steps in lung metastasis. Nature 446, 765–770 (2007).

    Article  CAS  Google Scholar 

  43. Neve, R. M. et al. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell 10, 515–527 (2006).

    Article  CAS  Google Scholar 

  44. Williams, N. S. et al. Identification and validation of genes involved in the pathogenesis of colorectal cancer using cDNA microarrays and RNA interference. Clin. Cancer Res. 9, 931–946 (2003).

    CAS  PubMed  Google Scholar 

  45. Hoeflich, K. P. et al. Oncogenic BRAF is required for tumor growth and maintenance in melanoma models. Cancer Res. 66, 999–1006 (2006).

    Article  CAS  Google Scholar 

  46. Austin, C. P. et al. The knockout mouse project. Nature Genet. 36, 921–924 (2004).

    Article  CAS  Google Scholar 

  47. Kunath, T. et al. Transgenic RNA interference in ES cell-derived embryos recapitulates a genetic null phenotype. Nature Biotech. 21, 559–561 (2003).

    Article  CAS  Google Scholar 

  48. Xia, X. G., Zhou, H., Samper, E., Melov, S. & Xu, Z. Pol II-expressed shRNA knocks down Sod2 gene expression and causes phenotypes of the gene knockout in mice. PLoS Genet. 2, e10 (2006).

    Article  Google Scholar 

  49. Kissler, S. et al. In vivo RNA interference demonstrates a role for Nramp1 in modifying susceptibility to type 1 diabetes. Nature Genet. 38, 479–483 (2006).

    Article  CAS  Google Scholar 

  50. Xue, W. et al. Senescence and tumour clearance is triggered by p53 restoration in murine liver carcinomas. Nature 445, 656–660 (2007). A study highlighting the power of inducible RNAi in vivo.

    Article  CAS  Google Scholar 

  51. Ventura, A. et al. Restoration of p53 function leads to tumour regression in vivo. Nature 445, 661–665 (2007).

    Article  CAS  Google Scholar 

  52. Doench, J. G., Petersen, C. P. & Sharp, P. A. siRNAs can function as miRNAs. Genes Dev. 17, 438–442 (2003).

    Article  CAS  Google Scholar 

  53. Echeverri, C. J. et al. Minimizing the risk of reporting false positives in large-scale RNAi screens. Nature Methods 3, 777–779 (2006). A description of how to minimize the problems of off-target effects.

    Article  CAS  Google Scholar 

  54. Knight, Z. A. & Shokat, K. M. Chemical genetics: where genetics and pharmacology meet. Cell 128, 425–430 (2007).

    Article  CAS  Google Scholar 

  55. Ditchfield, C. et al. Aurora B couples chromosome alignment with anaphase by targeting BubR1, Mad2, and Cenp-E to kinetochores. J. Cell Biol. 161, 267–280 (2003).

    Article  CAS  Google Scholar 

  56. Hemann, M. T. et al. An epi-allelic series of p53 hypomorphs created by stable RNAi produces distinct tumor phenotypes in vivo. Nature Genet. 33, 396–400 (2003).

    Article  CAS  Google Scholar 

  57. Eggert, U. S. et al. Parallel chemical genetic and genome-wide RNAi screens identify cytokinesis inhibitors and targets. PLoS Biol. 2, e379 (2004). The first study to combine chemical, genetic and RNAi screens to identify compounds and targets simultaneously.

    Article  Google Scholar 

  58. Lamb, J. et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science 313, 1929–1935 (2006). A description of the Connectivity Map, an important resource for comparing gene-expression signatures to identify similar profiles from any platform.

    Article  CAS  Google Scholar 

  59. Friedman, A. & Perrimon, N. A functional RNAi screen for regulators of receptor tyrosine kinase and ERK signalling. Nature 444, 230–234 (2006).

    Article  CAS  Google Scholar 

  60. Boutros, M. et al. Genome-wide RNAi analysis of growth and viability in Drosophila cells. Science 303, 832–835 (2004).

    Article  CAS  Google Scholar 

  61. Zhang, J. H., Chung, T. D. & Oldenburg, K. R. A simple statistical parameter for use in evaluation and validation of high throughput screening assays. J. Biomol. Screen. 4, 67–73 (1999).

    Article  CAS  Google Scholar 

  62. Stone, D. J. et al. High-throughput screening by RNA interference: control of two distinct types of variance. Cell Cycle 6, 898–901 (2007).

    Article  CAS  Google Scholar 

  63. Birmingham, A. et al. 3′ UTR seed matches, but not overall identity, are associated with RNAi off-targets. Nature Methods 3, 199–204 (2006).

    Article  CAS  Google Scholar 

  64. Tuschl, T., Zamore, P. D., Lehmann, R., Bartel, D. P. & Sharp, P. A. Targeted mRNA degradation by double-stranded RNA in vitro. Genes Dev. 13, 3191–3197 (1999).

    Article  CAS  Google Scholar 

  65. Meister, G. & Tuschl, T. Mechanisms of gene silencing by double-stranded RNA. Nature 431, 343–9 (2004).

    Article  CAS  Google Scholar 

  66. Rychahou, P. G., Jackson, L. N., Farrow, B. J. & Evers, B. M. RNA interference: mechanisms of action and therapeutic consideration. Surgery 140, 719–725 (2006).

    Article  Google Scholar 

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Correspondence to Alan Ashworth.

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DATABASES

OMIM

Breast cancer

Non-small-cell lung cancer

FURTHER INFORMATION

cellHTS

NIH Knockout Mouse Project

The Breakthrough Breast Cancer Research Centre

The Connectivity Map

Glossary

Glioblastoma

A high-grade brain malignancy arising from astrocytes with abnormal cellular proliferation and increased tumour angiogenesis. This cancer is usually refractory to chemotherapy and has a poor prognosis.

Isogenic-paired cell lines

These consist of two cell lines that are of identical origin, but differ at a known genetic locus.

Chemosensitization

The ability of a defined change to increase the sensitivity of a cell to a chemotherapeutic agent.

CRE-loxP system

Murine strains can be engineered with loxP sites flanking a gene of interest. Expression of CRE recombinase, an enzyme that causes selective excision of all genetic material between two loxP sites, allows for ablation of the gene of interest. Expression of CRE under the control of different promoter elements enables temporal and tissue-specific deletion of the gene of interest.

Tet-off system

Murine strains can be engineered to contain a transgene of interest that is either induced (tet-ON) or repressed (tet-OFF) by tetracycline analogues (such as doxycycline). An advantage of tet-regulation is that the gene of interest can be serially induced or repressed by withdrawing or adding doxycycline to the animal's drinking water.

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Iorns, E., Lord, C., Turner, N. et al. Utilizing RNA interference to enhance cancer drug discovery. Nat Rev Drug Discov 6, 556–568 (2007). https://doi.org/10.1038/nrd2355

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