Karuppiah Kannan

Components of the Rb pathway are critical targets of UV mutagenesis in a murine melanoma model

Epidemiological studies support a link between melanoma risk and UV exposure early in life, yet the molecular targets of UVs mutagenic actions are not known. By using well characterized murine models of melanoma, we provide genetic and molecular evidence that identifies components of the Rb pathway as the principal targets of UV mutagenesis in murine melanoma development. In a melanoma model driven by H-RAS activation and loss of p19ARF function, UV exposure resulted in a marked acceleration in melanoma genesis, with nearly half of these tumors harboring amplification of cyclin-dependent kinase (cdk) 6, whereas none of the melanomas arising in the absence of UV treatment possessed cdk6 amplification. Moreover, UV-induced melanomas showed a strict reciprocal relationship between cdk6 amplification and p16INK4a loss, which is consistent with the actions of UV along the Rb pathway. Most significantly, UV exposure had no impact on the kinetics of melanoma driven by H-RAS activation and p16INK4a deficiency. Together, these molecular and genetic data identify components of the Rb pathway as critical biological targets of UV-induced mutagenesis in the development of murine melanoma in vivo.

Both products of the mouse INK4a/ARF locus suppress melanoma formation in vivo

Deletion of the INK4a/ARF locus at 9p21 is detected with high frequency in human melanoma. Within a short genomic distance, this locus encodes several proteins with established tumor-suppressor roles in a broad spectrum of cancer types. Several lines of evidence support the view that p16INK4a and p19ARF exert the tumor-suppressor activities of this locus, although their relative importance in specific cancer types such as melanoma has been less rigorously documented on the genetic level. Here, we exploit a well-defined mouse model of RAS-induced melanomas to examine the impact of germline p16INK4a or p19ARF nullizygosity on melanoma formation. We demonstrate that loss of either Ink4a/Arf product can cooperate with RAS activation to produce clinically indistinguishable melanomas. In line with the common phenotypic end point, we further show that RAS+ p16INK4a−/− melanomas sustain somatic inactivation of p19ARF-p53 and, correspondingly, that RAS+ p19ARF−/− melanomas experience high-frequency loss of p16INK4a. These genetic studies provide definitive proof that p16INK4a and p19ARF cooperate to suppress the development of melanoma in vivo.

De novo Discovery of a γ-Secretase Inhibitor Response Signature Using a Novel In vivo Breast Tumor Model

Notch pathway signaling plays a fundamental role in normal biological processes and is frequently deregulated in many cancers. Although several hypotheses regarding cancer subpopulations most likely to respond to therapies targeting the Notch pathway have been proposed, clinical utility of these predictive markers has not been shown. To understand the molecular basis of gamma-secretase inhibitor (GSI) sensitivity in breast cancer, we undertook an unbiased, de novo responder identification study using a novel genetically engineered in vivo breast cancer model. We show that tumors arising from this model are heterogeneous on the levels of gene expression, histopathology, growth rate, expression of Notch pathway markers, and response to GSI treatment. In addition, GSI treatment of this model was associated with inhibition of Hes1 and proliferation markers, indicating that GSI treatment inhibits Notch signaling. We then identified a pretreatment gene expression signature comprising 768 genes that is significantly associated with in vivo GSI efficacy across 99 tumor lines. Pathway analysis showed that the GSI responder signature is enriched for Notch pathway components and inflammation/immune-related genes. These data show the power of this novel in vivo model system for the discovery of biomarkers predictive of response to targeted therapies, and provide a basis for the identification of human breast cancers most likely to be sensitive to GSI treatment.

Abstract B18: Variation in response to VEGFR inhibitor tivozanib in a unique population‐based tumor model enables the development of a multigene response biomarker

Variation is a hallmark of human tumors. Within any human tumor population, significant inter‐tumor variation in genetic context underlies variation in phenotype, prognosis, and response to a given therapeutic agent. The ability to identify associations between genetic context and drug response lies at the core of much of translational research in cancer. However, current preclinical models fail to adequately represent this variation in a manner suitable for correlating genetic context with drug response. To address this challenge, we used complex genetically engineered murine tumors to develop a population based model comprising over 100 HER2 INK4A‐/‐ driven breast tumors, each with associated expression microarray, array CGH, histology, as well as protein and biochemical characteristics. Similar to that observed in human tumor populations, this breast tumor archive exhibited significant inter‐tumor variation in RNA and DNA profiles, and variation in many measurable tumor phenotypes, including tumor vasculature. The VEGF/VEGFR axis is postulated to be the dominant human tumor angiogenesis mediator. However, in contrast to robust activities observed in traditional xenograft models, anti‐VEGF/VEGFR agents have thus far elicited relatively modest activity in human clinical studies (e.g. single agent RECIST response rates vary between 0–11% in several breast cancer studies). To better model the observed human variation in response to VEGF pathway antagonism, and to explore the development of a predictive biomarker for patient selection, we determined the responsiveness of tumors across the population based model to a potent, selective VEGFR inhibitor, tivozanib (AV‐951). Tivozanib exhibits picomolar inhibitory activity against all three VEGF receptors, is active in a broad array of traditional xenografts, exhibits a multiday T1/2 in humans, and demonstrates robust clinical activity in renal cell carcinoma, with RECIST response rates of 25–40%. Interestingly, a significant variation in response to tivozanib was observed among 25 tumors in the population model, with the majority exhibiting intrinsic resistance to tivozanib9s anti‐angiogenic activity. Combining the efficacy data, extensive IHC analyses, the comprehensive expression profiles and a novel bioinformatics approach, we identified a multigene biomarker of on‐target drug resistance. Using the same multigene biomarker identified in the murine model to examine human tumor microarray datasets, subsets of breast, lung, colon and kidney cancer human populations were predicted to exhibit tivozanib resistance. These data demonstrate the promise of population based preclinical models for translational research and provide a readily testable multigene biomarker for the potent VEGF pathway antagonist tivozanib. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):B18.

Abstract A233: Generation of in vitro and in vivo tumor models driven by insulin‐like growth factor receptor (IGF1R) and their use in the development of OSI‐906, a selective IGF1R inhibitor

The emergence of insulin‐like growth factor‐1 receptor IGF1R as an important cancer target is evidenced by the growing number of clinical trials currently underway for both small molecule inhibitors and antibody therapeutics developed against it. In preclinical studies, perturbation in IGF1R signaling has been associated with tumor growth inhibition, blockade of metastasis, and enhanced sensitivity to therapeutic agents, including cytotoxic chemotherapeutics and molecular targeted agents. Currently agents directed against IGF1R are being evaluated in clinical trials for their therapeutic utility. Given the differential dependence on IGF1R exhibited by human tumors and xenograft lines, there is a need for additional preclinical models in which the relationship between genetic context and drug response in solid tumors can be better understood in an in vivo setting. To this end, we utilized our HER2 driven inducible breast cancer model to create a panel of genetically‐engineered mouse tumors, each driven by the human IGF1R. Some of the models were also engineered to express a cognate ligand IGF2. In these models, tumors initially driven by human HER2 expression are re‐programmed by the addition of the human IGF1R cDNA upon withdrawal of the original HER2 expression. Thus, the newly introduced IGF1R‐ IGF2 cDNA functionally maintains tumor survival by re‐directing downstream signalling effectors in a process referred to as ‘Directed Complementation’ (DC). Using this approach, introduction of IGF1R strongly complemented tumor formation across the panel, whereas introduction of the ligands, either IGF1 or IGF2, alone or in combination did not. We recently showed that treatment of IGF1R/IGF2 DC tumors with OSI‐906, a potent, selective orally active inhibitor of IGF1R, resulted in tumor regression within a week of treatment, with corresponding loss of phospho‐IGF1R signaling (AACR 2009: Abstract # 2902, Lerner, et al). These results demonstrate the singular dependence of these tumors on IGF1R signaling, as well as the in vivo efficacy of the compound. Next, we sought to extend the utility of these validated tumor models to drug discovery by establishing IGF1R‐dependent cell lines for high‐throughput screening. Here we describe detailed molecular characterization of these cell lines derived from the IGF1R/IGF2 DC tumor models as well as their drug sensitivities. Importantly, we show that the IGF1R/IGF2 DC cell lines, like their parent tumors, retain activation of the pathway as well as sensitivity to OSI‐906. Therefore, these tumor models and derived cell lines provide an effective preclinical tool for the development of targeted anti‐IGF1R therapies. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):A233.