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Commentary |
Authors' Affiliations: 1 Department of Urology, Herbert Irving Comprehensive Cancer Center, Columbia University College of Physicians and Surgeons; 2 Strang Cancer Prevention Center, Weill Medical College of Cornell University, New York, New York; 3 Departments of Medicine and Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas; 4 Laboratory of Cancer Prevention, National Cancer Institute, Frederick, Maryland; 5 Department of Cell Biology and Anatomy, Arizona Cancer Center, University of Arizona, Tucson, Arizona; 6 Laboratory of Cancer Biology and Genomics, National Cancer Institute, Bethesda, Maryland; 7 Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, Maryland; and 8 Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina
Requests for reprints: Cory Abate-Shen, Herbert Irving Comprehensive Cancer Center, Room 217A, 1130 St. Nicholas Street, New York, NY 10032. Phone: 212-851-4731; Fax: 212-851-4572; E-mail: cabateshen{at}columbia.edu.
| Abstract |
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Key Words: chemoprevention mouse models review
| Introduction: Modeling Cancer Prevention in Genetically Engineered Mutant Mice |
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GEM models of human cancer refer to mouse strains in which the genome has been manipulated to achieve gain or loss of oncogene or tumor suppressor gene function, the consequences of which are manifested in tumor phenotypes (2). Similar to chemically induced rodent models, which historically have been widely used in prevention research, GEM models provide an opportunity to investigate carcinogenesis in the context of the whole organism. However, GEM models are distinct from chemically induced rodent models because their tumor phenotypes are induced by manipulating a specific gene or genetic pathway rather than inducing with carcinogens and/or other cancer promoting agents. Thus, GEM models enable the assessment of specific molecular pathways for tumorigenesis in the context of the whole organism.
GEM models are also distinct from xenograft models, which are typically based on the propagation of human tumors and/or cell lines in immune-deficient mice. Whereas xenograft models have the obvious advantage of being developed from human cancer cells, they are often derived from established tumors or cancer cell lines (and often from advanced tumors or metastases), and therefore are unlikely to precisely model early events in carcinogenesis. Moreover, because xenografts are propagated in immunodeficient mice, they do not recapitulate the contributions of the tumor microenvironment, bacterial flora, or host immune system for carcinogenesis, which is of considerable concern because it is becoming increasingly apparent that these play critical roles in carcinogenesis, particularly at early disease stages (3–5). Moreover, xenograft models are not suitable for testing immunomodulators for cancer prevention.
However, critics of GEM models argue that their relevance for human cancer has not been established (6), and they cite examples in which studies in mouse models have not been validated to human cancer (see below). On the other hand, proponents of GEM models contend that the problem is not that the models are not relevant, but that the experimental parameters have not been designed in such as way as to effectively translate studies from mice to human cancer (7–9). Indeed, the applicability of prevention studies done in GEM models of human cancer will invariably depend on the choice of the model, the design of the experiment, and many other logistical issues. Ultimately, for prevention studies in GEM models to be applicable to humans, the models need to be appropriately chosen such that their biological and pathologic properties are relevant for the experimental question being asked and, conversely, the experimental design of the study should be analogous to design of prevention research in humans.
Accordingly, it is imperative to establish criteria for evaluating the relevance of a particular GEM model for a given experimental paradigm. Such criteria should include (a) pathologic analyses—Does the model display histologic and pathologic features in common with human cancer or a subtype thereof? (b) Disease evolution—Does the model recapitulate the stages of disease progression as occurs in humans? (c) Tumor microenvironment—Does the model effectively recapitulate the contribution of host factors including the tumor stroma, bacterial flora, and immune response for cancer progression? (d) Molecular pathways—Does the model display relevant genetic, genomic, epigenetic, and/or proteomic alterations that are known to be relevant for their human counterpart? (e) Environmental factors—Do hormonal, dietary, or other factors affect disease progression in the mouse models in a similar way as they do in humans?
Notably, it is often the case that in the course of characterizing these criteria for GEM models, new insights emerge that are relevant for understanding the molecular and biological properties of the human disease. For example, analyses of GEM mice have elucidated critical biological mechanisms of tumorigenesis, including the role of telomere length in disease pathogenesis (10) and, more recently, the role of cellular senescence in tumor suppression in vivo (11). Similarly, comparative analyses of the molecular properties of mouse and human tumors have enabled comprehensive analyses of global alterations in genomic pathways (12), as well as the identification of specific genes that are novel biomarkers of disease outcome in humans (13, 14). Furthermore, improvements in modeling disease evolution have led to new mouse models that display metastases as well as adenocarcinoma (15–17).
In the discussion that follows, we provide a historical perspective on the types of GEM models that are available for prevention research. Following which, we discuss past experiences using mouse models in prevention research and consider how these experiences can affect the design of future studies. Finally, we consider opportunities for using GEM models as well as obstacles that need to be overcome to effectively capitalize on their application for prevention research.
| The First Generation: The Oncomice |
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| The Second Generation: Loss of Function of Tumor Suppressors |
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Another potential limitation of germ-line mutant alleles is that they are more similar to inherited forms of cancer than sporadic forms, which are far more prevalent in humans. However, improved technologies for manipulating the mouse genome have led to more sophisticated gene targeting approaches, wherein selected genes of interest are conditionally inactivated (or conditionally activated) in spatially and temporally restricted domains. These conditional models include those based on loss of function of tumor suppressor genes, such as Trp53 and Pten, as well as gain of function of oncogenes, such as Kras (reviewed in ref. 2). Conditional gene targeting offers many advantages over traditional gene targeting in the germ line, such as overcoming the problem of embryonic lethality, which often precludes analyses of homozygous germ-line deletion of tumor suppressor genes, such as Rb1 and Pten. In addition, selective gene targeting to specific cell or tissue compartments often yields GEM models with a more restricted spectrum of tumor phenotypes, which are more suitable for preclinical studies.
| The "Next" Generation of Mouse Models of Cancer |
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In addition to Cre recombinase, other strategies for achieving regulatable expression are enabling the spatial and temporal control of multiple genes in specific tissue contexts. For example, other important technological approaches include the utilization of systems in which gene expression can be turned on or off using tetracycline-regulated activators affecting the responsive promoters driving the transcription of a gene of interest (17), which has been applied to several organ systems, including lung, lymphoid, and breast, to study the roles of oncogenes in tumor maintenance and the mechanisms of tumor recurrence (26, 27). Other approaches for manipulating gene expression include targeted expression of the TVA receptor in specific mouse tissues (28), which has led to the generation of valuable models of central nervous system and other tissues (29). Moreover, as an alternative to gene targeting approaches, new technologies for the stable "knockdown" of gene expression in vivo by delivery of RNA interference moieties are proving to be effective for developing mouse models of cancer (30, 31).
Finally, there have been major technological advances in small animal imaging approaches including bioluminescence, ultrasound, positron emission tomography imaging, and magnetic resonance imaging (32). These technologies now enable the effective visualization of tumors in vivo, which has made a huge effect on the effective utilization of GEM models and will surely be an asset for their application for cancer prevention. Indeed, it is now possible to visualize small clusters of activated cells or early lesions in vivo (33), which can be particularly advantageous for early intervention studies.
In summary, a robust generation of GEM models is now available or in the pipeline, which are based on the restricted loss or gain of function of gene expression in highly selective tissue-specific compartments and with precise temporal kinetics. Several of these models have already been validated to the human cancers they emulate, often to specific subtypes of the disease, and are now being exploited for the development of novel therapeutic approaches in academic and industrial settings. However, it is important to note that relatively few studies of cancer prevention have been done using this "next" generation of more sophisticated GEM models of human cancer. Thus, the potential promise of GEM models for cancer prevention research remains largely unexplored.
| Lessons from the Past: Successes or Failures? |
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Extensive epidemiologic evidence has shown that individuals consuming a high-fat "Western-style" diet have a higher incidence of many cancers and that agents such as vitamin D have a protective effect against cancer. Preclinical studies done in the ApcMin model to investigate the consequences of a Western-style diet, including reduced calcium and vitamin D and increased fat, for colon carcinogenesis resulted in elevated cancer-rates in the mutant mice, in agreement with the epidemiologic data (34, 35). However, some subsequent prospective clinical trials did not confirm that altering dietary factors led to prevention of colon cancer (37), which led to concerns about the relevance of these preclinical studies in mice for human colon cancer. Skeptics of using mouse models for cancer prevention have offered these data as an indictment of the limited relevance of these models to human cancer. However, proponents of mouse models have noted that the trial design and endpoints of the clinical trial were quite different than those of the epidemiologic and preclinical studies, and have suggested that the discrepancy between these findings may reflect differences in experimental design rather than actual differences between the mouse and human situations (38).
Indeed, whereas it is customary to consider the criteria of the best model, perhaps it may be more relevant to consider the most appropriate model for the experimental question; surely, any model, no matter how relevant, can be considered nonpredictive if it is not used in the appropriate contextual framework. Importantly, because any model will undoubtedly have certain limitations, the issue is not whether a given model recapitulates every aspect of the human disease (which would be nearly impossible!) but rather whether it provides reliable information for the experimental question that is being addressed and whether the experimental design will ultimately lead to insights that will be applicable to human cancer.
| The Challenge of Using GEM Models for Cancer Prevention |
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One key problem is that prevention research requires the integration of multiple scientific perspectives. Improving ways of bringing together epidemiologists, basic scientists, mouse modelers, geneticists, bioinformaticians, and clinicians will be imperative for making real headway in cancer prevention. Unfortunately, communication between these multiple areas of research has been limited, particularly with respect to the potential application of GEM models for prevention research.
A second major problem is one of cost. Preclinical studies in mutant mice are expensive and difficult to recover from standard funding mechanisms. Although GEM models are now being increasingly used for experimental therapeutics by the pharmaceutical industry, most prevention research has been focused in academic settings and there has been little opportunity for cost-sharing with industry.
Another major stumbling block for virtually all studies using GEM models of cancer is the lack of sufficient numbers of pathologists that can critically evaluate GEM models relative to the human cancers they represent. Whereas the involvement of pathologists will be key to the successful establishment of a concerted effort in applying mouse models to cancer prevention, the number of veterinary and academic medical pathologists available for such collaborative efforts is limited.
Finally, a significant impediment to the use of GEM models has been intellectual property issues. In particular, broad patents on the use of genetically engineered mice for cancer studies have hampered preclinical testing of compounds using GEM models in academic and industrial settings (9, 18). Fortunately, the recognition that GEM models may play a critical role in identifying compounds that are more likely to succeed in human clinical trials has begun to accelerate their use in both academic and industry settings (9).
| Opportunities for Using GEM Models for Cancer Prevention |
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Finally, appropriately designed preclinical studies in GEM models can provide an important resource for investigating the efficacy of novel chemopreventive agents, as well as the consequences of dietary, chemical, hormonal, and/or environmental influences on carcinogenesis. In particular, studies in GEM models can enable the initial testing of pharmacologic agents, individually or in combination, and can also provide initial insights into their toxicity limits and mechanisms of action in vivo (9, 42, 43). Moreover, GEM models offer a resource for investigating the consequences of environmental influences (e.g., the contribution of diet), the intestinal flora, or hormonal influences in carcinogenesis (44–46).
In summary, GEM models offer a unique opportunity for providing biological and mechanistic insights into the interplay between genetic and environmental factors that influence cancer initiation, as well as preclinical models to test the consequences of targeting specific factors for alleviating carcinogenesis. Whereas analyses of mouse models will never be a suitable replacement for human clinical studies, such analyses can surely aid in the refinement of such studies to the considerable benefit of the human population assuming that the appropriate models are used in the appropriate experimental paradigms.
| Disclosure of Potential Conflicts of Interest |
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| Acknowledgements |
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| Footnotes |
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Note: The authors were among the participants of a National Cancer Institute–sponsored Think Tank on the use of genetically engineered mice for chemoprevention, and this article represents, in part, a synopsis of the conclusions of this meeting.
Received for publication April 18, 2008.
Revision received May 13, 2008.
Accepted May 13, 2008
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