Corporate Comment
tau tangles and neuronal cell death. Most AD model mice do develop amyloid deposits, but most do not develop tau tan- gles or show neuronal cell death. In addi- tion, it is still unclear how well any of these mouse models reproduce the underlying mechanisms of AD, especially for sporadic AD. And, to date, none of the many drug candidates developed in mouse models of AD has proven effective in halting or even slowing disease progression in human clin- ical trials.
Issues that likely contribute to the imper- fect accuracy of mouse models of disease include: l Major differences in the basic biology of rodents and humans. l Lack of homology of molecular targets: eg, mice and humans express different iso- forms of beta-amyloid26. l Lack of homology in molecular path- ways: transcription factors bind to overlap- ping but different sets of genes in mouse versus humans, and in some cases tran- scriptome changes in mouse models of a particular disease barely resemble those seen in humans25,27-30. l Lack of genetic diversity in inbred mice versus humans. l Comorbid conditions associated with age-related diseases in humans that are not reproduced in mouse models. l Environmental risk factors that con- tribute to most common human diseases but not reproduced in mouse models of those diseases.
Despite these limitations, mouse models nonetheless have been invaluable for estab- lishing causative roles of specific genes and gene variants in disease, for understanding biological pathways of disease and identify- ing new drug targets. They have also been critical in the development of the 10% of drug candidates that do make it through clinical trials. To give just a few examples: l Despite the fact that mouse models of rheumatoid arthritis (RA) do not perfectly model human RA, these models were piv- otal in the development of anti-tumour necrosis factor (anti-TNF; a translational success that helped launch the biopharma- ceutical industry)31. l The recent discovery of the first therapy for SMA would likely have been impossible
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without SMN2 transgenic mice4,5. lThe development of most successful anti- cancer drugs has relied on mouse xenograft models32.
It is also possible that many cases of ‘fail- ure to translate’ are due to poor design and interpretation of preclinical studies rather than to inadequacies in the animal models studied13. Nonetheless, given the expense and ethical issues of working with vertebrate animals, we should not only improve the design of preclinical studies, but also develop the best models we can and also account for gene/environment interactions33-35. In ‘reverse translational’ (or ‘bedside-to- bench’) research, data from human subjects is used to develop new hypotheses for test- ing in the laboratory and to develop new animal models and therapeutics. Although reverse translation is a recently-coined term, this kind of research has been done for centuries. For example, Edward Jenner’s 1796 discovery of the first small- pox vaccine was based on the observation that milkmaids who had previously caught cowpox developed resistance to smallpox, and the vaccine’s success helped lay the foundation for modern immunology36. Over the past few years, molecular profil- ing of human patients has yielded vast quan- tities of ‘omics’ data that can be harnessed for reverse translational research. For exam- ple, genome-wide association studies (GWAS) and next-generation sequencing (NGS) have identified hundreds of novel genes and gene variants associated with risk of, or protection against, human diseases, including common sporadic disorders. These data can be used to create new genet- ically-engineered iPSC (induced pluripotent stem cell) models as well as animal models of disease, which then can be used both to explore the functions of the newly-identified genes, and to discover new disease pathways and candidate drug targets37-39. This kind of reverse translational approach to generat- ing animal models offers a special boon for the study of rare inherited diseases, for many of which no animal models have pre- viously been available40,41.
Molecular profiling of patient tissue samples can be used to identify patterns of RNA and protein expression that correlate with disease resistance and/or responsive-
ness to therapeutics. In the cancer field, for example, gene and protein expression pro- filing of tumours has begun to define molecular signatures associated with better responses to immunotherapy and higher patient survival rates; these signatures can also suggest new targets for drug develop- ment42-45. Molecular profiling can also be used to screen and optimise cell-based ther- apeutics. In one recent study, molecular profiling of more than 100 different prepa- rations of dendritic cell (DC) vaccines tar- geting prostate cancer identified a signature of DC gene and protein expression that correlated with the induction of strong anti-tumour responses in patients46. In a modern spin on the development of the smallpox vaccine, immune profiling of humans who show resistance to certain dis- eases (Alzheimer’s Disease, progressive multifocal leukoencephalopathy) has been used to develop antibody therapies for these diseases47,48.
Another important application of the reverse translational approach is in the anal- ysis of results of failed clinical trials49,50. In one example, the anti-IL-12B p40 antibody, which showed promise as a therapeutic for multiple sclerosis (MS) based on results in mice and marmoset models of experimental autoimmune encephalomyelitis (EAE), failed in human trials. Subsequent analysis of dis- ease progression in mouse and marmoset EAE models versus human MS showed that the initiation and progression phases of the disease are driven by different mechanisms in primates, the mouse replicates only the initi- ation mechanism and the drug blocks only the initiation mechanism50.
During the past few years, researchers involved in translational science and drug discovery have been harnessing exciting new technologies to enable the reappraisal and fine-tuning of traditional models, and to create new models. As detailed above, there is increasing emphasis on overcoming limitations of currently available in vitro and in vivo models by improving ease and cost of use and predictive validity. These innovative model systems include new ani- mal models that more closely recapitulate human disease syndromes, and new in vitro models that support easier, deeper study of human disease pathways and ‘personalised’ drug testing.
DDW Drug Discovery World Fall 2017
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