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issue. Subtle gene ‘knock-in’ or correction events in human cells, while possible when ZFNs are co- delivered with a second donor-homology vector, are less efficient due to the fact that dsDNA breaks are predominantly repaired by error-prone non- homologous end joining pathways.

Meganucleases: These are analogous to ZFNs, but possess greater specificity due to having a much larg- er DNA-recognition footprint. However, they are not as flexible in their design as ZFNs and the high cost of creating Meganucleases to a target locus of inter- est means they have been limited to performing high- value projects such as transgenesis in plants.

TALEN-nucleases: This is a new nuclease player in the field. Their advantage is that they are almost completely modular and deterministic in their assembly, allowing the simple and cost-effective design to almost any genome location in theory. Moreover, since modules are extendible into very large DNA-recognition footprints they are possibly much more specific. For these reasons and public domain construction algorithms, they look set to compete with established nuclease methods. Their ability to perform subtle knock-ins has not yet been tested, but they will logically be subject to the same limitations as other dsDNA break-inducing methodologies. Consequently, their prime advan- tage will lie in performing efficient gene knock- outs and transgene insertions in ‘safe harbour’ loci in a broad range of animal and plant systems.

rAAV: Recombinant adeno-associated viruses are non-pathogenic single stranded DNA-viruses and they have a unique and powerful capability to con- vert direct ‘HR-only’ vectors into a system that is ~1,000-fold greater efficiency at performing all forms of gene-editing compared to older-style dsDNA homology vectors (Figure 1). It is not entirely known why they are so efficient, but it appears that a distinct form of DNA-repair oper- ates to faithfully recombine ss-DNA species into target genomic loci, which is independent of many of the factors typically seen to be important for dsDNA-mediated HR, eg Rad51 and Rad54b. rAAV was first used in human gene-therapy due to its efficient mode of delivery and its ability to per- form precise targeted gene corrections, and then more widely in the field of in vitro genome editing and disease modelling. While not as efficient as nuclease methods at performing bi-allelic gene knock-outs currently, this may improve with fur- ther research into ssDNA-mediated HR mecha- nism, and in the meantime allows users complete


confidence that when you have successfully target- ed a gene, it does not also come with other con- founding off-target events. For this reason, it is becoming the method of choice for the definitive dissection of gene-function, as well as performing precision disease modelling. It is also likely to be preferred for creating enhanced bioproduction cell- lines, especially now the CHO genome has been sequenced, wherein dsDNA break methods can cause long-term genome stability issues and are even prone to integrating trace levels of non-human DNA present in cell-culture media, via highly effi- cient non-homologous recombination events.

Disease models in early stage drug discovery

Coming now to applications of gene targeting and genetically-defined disease models, the first thing any drug developer has to do is to choose a specif- ic target, preferably a good one given how long and expensive it is. However, prior to recent large- scale, consortium-based, cancer genome profiling efforts, choosing a ‘good’ cancer target was very hard to qualify or quantitate in some way. All too often a ‘validated’ target was simply one that another company was working on, but not too many as this would be overly competitive. True disease validation was effectively minimal, with elevated expression or perceived pathway rele- vance typically being the best marker of cancer rel- evance, which is often misleading.

DNA-alterations (mutations and/or copy number gains or losses) in contrast, are unambiguous events and, if present in high enough frequency in a cancer type, are, more often than not, key drivers of the disease. Now we have a plethora of such informa- tion, several new issues actually arise: Firstly, most ‘cancer genes’ are tumour suppressors, which are either inactivated or completely lost in tumours, and thus are unrealistic targets for small-molecules that are typically easier to design as inhibitors of protein function. Secondly, many gain-of-function ‘oncogenes’ are also hard to drug, such as non- enzymatic transcription factors. Thirdly and of practical importance, most newly identified candi- date cancer genes, including the drugable ones, have very low tumour mutation frequencies (often <5%), which could simply represent passenger ‘noise’ in genetically unstable tumours. Due to all these factors, there is currently a heavy operational bias towards drugging signalling pathway kinases, which if directly implicated in disease progression can be highly effective, but are also subject to rapid onset of resistance via compensatory signalling pathways or events. This may also be exacerbated

Drug Discovery World Spring 2011

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