A preclinical orthotopic model for glioblastoma recapitulates key features of human tumors and demonstrates sensitivity to a combination of MEK and PI3K pathway inhibitors.

Current therapies for glioblastoma multiforme (GBM), the highest grade malignant brain tumor, are mostly ineffective, and better preclinical model systems are needed to increase the successful translation of drug discovery efforts into the clinic. Previous work describes a genetically engineered mouse (GEM) model that contains perturbations in the most frequently dysregulated networks in GBM (driven by RB, KRAS and/or PI3K signaling and PTEN) that induce development of Grade IV astrocytoma with properties of the human disease. Here, we developed and characterized an orthotopic mouse model derived from the GEM that retains the features of the GEM model in an immunocompetent background; however, this model is also tractable and efficient for preclinical evaluation of candidate therapeutic regimens. Orthotopic brain tumors are highly proliferative, invasive and vascular, and express histology markers characteristic of human GBM. Primary tumor cells were examined for sensitivity to chemotherapeutics and targeted drugs. PI3K and MAPK pathway inhibitors, when used as single agents, inhibited cell proliferation but did not result in significant apoptosis. However, in combination, these inhibitors resulted in a substantial increase in cell death. Moreover, these findings translated into the in vivo orthotopic model: PI3K or MAPK inhibitor treatment regimens resulted in incomplete pathway suppression and feedback loops, whereas dual treatment delayed tumor growth through increased apoptosis and decreased tumor cell proliferation. Analysis of downstream pathway components revealed a cooperative effect on target downregulation. These concordant results, together with the morphologic similarities to the human GBM disease characteristics of the model, validate it as a new platform for the evaluation of GBM treatment.

Pathway-specific engineered mouse allograft models functionally recapitulate human serous epithelial ovarian cancer.

The high mortality rate from ovarian cancers can be attributed to late-stage diagnosis and lack of effective treatment. Despite enormous effort to develop better targeted therapies, platinum-based chemotherapy still remains the standard of care for ovarian cancer patients, and resistance occurs at a high rate. One of the rate limiting factors for translation of new drug discoveries into clinical treatments has been the lack of suitable preclinical cancer models with high predictive value. We previously generated genetically engineered mouse (GEM) models based on perturbation of Tp53 and Rb with or without Brca1 or Brca2 that develop serous epithelial ovarian cancer (SEOC) closely resembling the human disease on histologic and molecular levels. Here, we describe an adaptation of these GEM models to orthotopic allografts that uniformly develop tumors with short latency and are ideally suited for routine preclinical studies. Ovarian tumors deficient in Brca1 respond to treatment with cisplatin and olaparib, a PARP inhibitor, whereas Brca1-wild type tumors are non-responsive to treatment, recapitulating the relative sensitivities observed in patients. These mouse models provide the opportunity for evaluation of effective therapeutics, including prediction of differential responses in Brca1-wild type and Brca1-deficient tumors and development of relevant biomarkers.

Perturbation of Rb, p53, and Brca1 or Brca2 cooperate in inducing metastatic serous epithelial ovarian cancer.

The majority of human high-grade serous epithelial ovarian cancer (SEOC) is characterized by frequent mutations in p53 and alterations in the RB and FOXM1 pathways. A subset of human SEOC harbors a combination of germline and somatic mutations as well as epigenetic dysfunction for BRCA1/2. Using Cre-conditional alleles and intrabursal induction by Cre-expressing adenovirus in genetically engineered mice, we analyzed the roles of pathway perturbations in epithelial ovarian cancer initiation and progression. Inactivation of RB-mediated tumor suppression induced surface epithelial proliferation with progression to stage I carcinoma. Additional biallelic inactivation and/or missense p53 mutation in the presence or absence of Brca1/2 caused progression to stage IV disease. As in human SEOC, mice developed peritoneal carcinomatosis, ascites, and distant metastases. Unbiased gene expression and metabolomic profiling confirmed that Rb, p53, and Brca1/2-triple mutant tumors aligned with human SEOC, and not with other intraperitoneal cancers. Together, our findings provide a novel resource for evaluating disease etiology and biomarkers, therapeutic evaluation, and improved imaging strategies in epithelial ovarian cancer.

Temporal molecular and biological assessment of an erlotinib-resistant lung adenocarcinoma model reveals markers of tumor progression and treatment response.

Patients with lung cancer with activating mutations in the EGF receptor (EGFR) kinase, who are treated long-term with tyrosine kinase inhibitors (TKI), often develop secondary mutations in EGFR associated with resistance. Mice engineered to develop lung adenocarcinomas driven by the human EGFR T790M resistance mutation are similarly resistant to the EGFR TKI erlotinib. By tumor volume endpoint analysis, these mouse tumors respond to BIBW 2992 (an irreversible EGFR/HER2 TKI) and rapamycin combination therapy. To correlate EGFR-driven changes in the lung with response to drug treatment, we conducted an integrative analysis of global transcriptome and metabolite profiling compared with quantitative imaging and histopathology at several time points during tumor progression and treatment. Responses to single-drug treatments were temporary, whereas combination therapy elicited a sustained response. During tumor development, metabolomic signatures indicated a shift to high anabolic activity and suppression of antitumor programs with 11 metabolites consistently present in both lung tissue and blood. Combination drug treatment reversed many of the molecular changes found in tumored lung. Data integration linking cancer signaling networks with metabolic activity identified key pathways such as glutamine and glutathione metabolism that signified response to single or dual treatments. Results from combination drug treatment suggest that metabolic transcriptional control through C-MYC and SREBP, as well as ELK1, NRF1, and NRF2, depends on both EGFR and mTORC1 signaling. Our findings establish the importance of kinetic therapeutic studies in preclinical assessment and provide in vivo evidence that TKI-mediated antiproliferative effects also manifest in specific metabolic regulation.