The availability of robust GEM models facilitates a detailed analysis of human cancer that cannot be easily accomplished by studying primary human tumors (see Opportunities provided by employing GEM cancer models). First, the ability to more effectively treat human cancers requires a detailed understanding of molecular and cellular pathogenesis to identify specific molecular targets. Second, there is also a great need to define those individuals at greatest risk for developing cancer as well as those most likely to respond to any given therapeutic regimen. These studies require large numbers of individuals and are often not possible for less common cancers. Last, the identification of surrogate markers of tumor formation and early response to therapy, which would have tremendous impact on current treatment strategies, is another unmet need.
Evaluation of standard human antitumor therapies.
One of the often neglected uses of GEM cancer models is the validation of conventional therapies employed for the treatment of cognate tumors in humans. For example, accurate GEM models of astrocytoma or pancreatic cancer should ideally respond to the same treatments currently used to treat these cancers (i.e., temozolomide and gemcitibene, respectively). In addition, GEM models afford the opportunity to define the mechanism(s) underlying the antitumor effects. Tumors from mice treated with anticancer therapies can be analyzed to determine whether regression results from decreased cell growth, increased cell death, decreased tumor angiogenesis, or necrosis. Failure to observe any effects on GEM tumors may reflect problems with bioavailability (e.g., inability to cross the blood-brain barrier), differences in the metabolic processing of drugs in rodents (e.g., pharmacokinetic and pharmacodynamic [PK/PD] issues), and/or genetic differences between mouse strains that dictate the response to therapy (e.g., modifier loci).
Experience with a mouse model of acute promyelocytic leukemia (APL) suggests that GEM models respond to human cancer treatments and can be used to improve therapy. In APL, blasts are arrested at the promyelocytic stage of differentiation due to chromosomal translocations that fuse the retinoic acid receptor alpha
) gene to a variety of partner genes including promyelocytic leukemia
) and promyelocytic leukemia zinc finger
-retinoic acid (ATRA) induces complete remissions in approximately 80% of patients with APL who have a PML-RARA
translocation by relieving the differentiation block (22
) but does not induce remission in those individuals with PLZF-RARA
). Similarly, ATRA induces remissions in PML-RARA
transgenic mice but is ineffective in a PLZF-RARA
strain that also develops APL (24
). In addition, mouse models of APL have been harnessed to test new therapeutic approaches such as arsenic trioxide (As2
) and the potential synergy between ATRA and As2
The role of specific cancer genes.
GEM strains have been generated that model the inactivation of genes mutated in inherited cancer syndromes (e.g., neurofibromatosis 1
in sporadic cancers (e.g., KRAS
and in both types of cancer (e.g., TP53
). GEM models based on these tumor suppressors and oncogenes provide unique opportunities to clearly define the causative role of each of these genetic changes in tumor formation and progression. This information is critical for the design of targeted (biologically based) therapies for individual cancers with these specific tumor-associated mutations.
GEM cancer models can be used to determine whether the success or failure of a given therapy reflects the ability of the drug to reach the tumor and inhibit its target. An illustrative example of how GEM cancer models can provide insights into mechanisms of drug activity comes from studies that evaluated the efficacy and putative biochemical targets of farnesyltransferase (FTase) inhibitors (FTIs). Ras processing is initiated by cytosolic prenyltransferases, which attach either a farnesyl or geranylgeranyl isoprenoid lipid to the thiol group of the cysteine. Geranylgeranyl transferase 1 (GGTase-1) and FTase catalyze the transfer of isoprenoid groups, which are donated by geranylgeranyl pyrophosphate and farnesyl pyrophosphate, respectively. FTIs were developed as cancer therapeutics based on their potential as Ras inhibitors in xenograft models. However, KRAS and NRAS are also good GGTase-1 substrates and are processed by this enzyme when FTase is inhibited. Preclinical studies of the efficacy of FTIs gave variable results in transgenic mouse models of breast cancer induced by expressing oncogenic HRAS or KRAS from the murine mammary tumor virus promoter (47
) and in a model of myeloproliferative disease induced by inactivating the Nf1
tumor suppressor (50
), which encodes a GTPase-activating protein that negatively regulates RAS signaling. Importantly, careful biochemical investigation of tumor tissues from these mouse models unequivocally showed no inhibition of KRAS or NRAS processing at the maximally tolerated dose (MTD) of FTI. Based on these data, it was concluded that any therapeutic effects of FTIs were due to “off-target” activities that were not related to the original goal of inhibiting hyperactive RAS.
Defining the discrete steps of tumorigenesis.
GEM cancer models can be used to dissect the cellular and molecular changes associated with each stage of neoplasia, including tumor formation, tumor maintenance, and malignant progression. Studies focused on defining the events associated with tumor formation in multistep cancers are essentially chemoprevention investigations. Direct chemoprevention studies in people at risk for cancer are difficult, owing to the genetic heterogeneity in human populations and the difficulties in accurately measuring exposure, which necessitate large and enormously expensive long-term studies. By contrast, experiments in GEM cancer models can be performed on a uniform genetic background in which environmental exposures are rigorously controlled. GEM cancer models have been employed to establish causal relationships with environmental exposures (e.g., asbestos in mesothelioma, tobacco and lung cancer; diet in colon cancer) (51
The ability of a tumor to continue to survive and proliferate in an otherwise inhospitable environment requires additional molecular and cellular changes. Studies of tumor maintenance are typically focused on defining the key signals required for these processes and form the basis for targeted chemotherapy. Studies in GEM models and in human patients have implied that molecular changes important for cancer formation are also necessary for maintenance. For example, studies in which tetracycline-regulatable alleles of oncogenic RAS
were “shut off” in established tumors resulted in dramatic tumor regression (56
). Furthermore, the emergence of imatinib-resistant mutant alleles of BCR-ABL
in patients with chronic myeloid leukemia (59
) argues strongly that the cancer-initiating mutation remains central to the tumor’s growth advantage. However, other data suggest that cancer cells can escape from dependence on the initiating oncogenic lesion under some circumstances (61
). The exact mechanisms underlying “tumor escape” have not been fully elucidated; but they may reflect a change in the histologic phenotype of the tumor, loss of expression of the initiating oncogene, or the acquisition of additional genetic changes (63
). The ability of some cancers to free themselves from dependence on the initiating molecular event likely has implications for the design of targeted therapies for recurrent tumors.
Tumors frequently evolve from a benign neoplastic lesion to a more malignant cancer. This progression involves the acquisition of additional genetic changes, which also serve as targets for chemotherapeutic drug design. For example, during the progression to malignant cancer, some low-grade astrocytomas somatically acquire a constitutively active version of the EGFR. This signature genetic event formed the basis for the development of targeted therapies directed against this mutant EGFR in both mice and humans (64
). GEM models were important in demonstrating that the EGFR mutation is a causative genetic change that accelerates malignant transformation (66
GEM cancer models have been powerful tools for examining the contribution of the tumor microenvironment to tumor formation. Studies of peripheral and central nervous system tumors in a mouse model of the NF1 familial cancer syndrome demonstrated that tumor formation requires that loss of Nf1
expression in Schwann cells (neurofibromas) or astrocytes (optic glioma) occur in the context of a heterozygous germline Nf1
). These data demonstrate that heterozygous Nf1
mutant cells in the microenvironment of preneoplastic lesions participate in tumorigenesis. Nonmalignant stromal cells also contribute to mammary carcinoma, in which loss of TGF-β receptor expression in fibroblasts promotes mammary ductal carcinoma growth and invasion by upregulating specific signaling networks (68
). Last, angiogenesis plays a fundamental role in tumor formation and progression and has formed the biological basis for numerous clinical trials using antiangiogenic therapies (70
). GEM models have been instructive in defining the molecular basis for new blood vessel formation by tumors and the impact of angiogenesis on tumor progression (72
Radiologic and serum biomarkers.
The ability to define individuals at high risk of developing cancer and the ability to noninvasively monitor disease burden during and after cancer treatment have substantial implications for clinical practice. GEM models have been employed to identify serum biomarkers for cancer using advanced proteomics methods. While these studies are still in their early phases of discovery, one serum biomarker has been identified for murine prostate cancer that correlated well with tumor weight and response to hormone therapy (74
). In addition to serum biomarkers, MRI has recently been evaluated for its ability to provide information regarding therapeutic efficacy in brain tumors. MRI of mice bearing brain tumors demonstrated that the tissue diffusion values obtained early after standard chemotherapy correlated with tumor response (75
). These results prompted an investigation of human brain tumors, which showed that tissue diffusion values obtained 3 weeks after the initiation of chemotherapy could predict patient response (76
). Similar to serum biomarkers, the ability of MRI to define patients with recurrent disease or who do not respond to first-line therapy would allow for early intervention and the administration of alternative therapies.
Unlike humans, GEM models can be generated on homogeneous genetic backgrounds, which greatly facilitate identifying modifier genes that influence the incidence or clinical behavior of specific cancers. Numerous candidate genetic loci have been found that influence tumor number and size in mouse lung and colon cancer (77
) as well as tumor type in mice harboring identical genetic mutations. For example, the tumor spectrum in mice harboring mutations in the p53
genes is dictated by the genetic background, which led to the identification of a locus on mouse chromosome 11 that determined susceptibility to astrocytoma (80
). Last, genes that function to identify DNA polymerase errors during DNA replication (DNA mismatch repair genes) have been shown to modify colon cancer tumor burden and survival in GEM (81