Abstract
Background:
Tumors from patients exhibit significant inter-tumor variation, where each tumor harbors a unique set of genetic alterations that impact prognosis and response to treatment. Unfortunately, this variation contributes to low response rates in the clinic and creates significant challenges for treating patients with appropriate drugs. Cancer cell line based xenografts have traditionally been the preclinical model of choice to assess the efficacy of clinical compounds; however, such in vitro models exhibit inherent artifacts, and are unable to adequately capture natural variation seen in human tumor populations. It has therefore become a priority in oncology and personalized medicine to match patients to drugs that will result in a favorable treatment outcome. In this report, we describe a population based approach for response prediction featuring naturally occurring variation in tumors derived from genetically defined human-in-mouse models of cancer. Materials and Methods:
A population of De novo human breast tumors were generated by genetically engineering normal primary human breast epithelial cells with HER2 and SV40 early region (HER2/SV40er) or KRAS and SV40 early region (KRAS/SV40er) in an in vivo Human-In-Mouse (HIM) tissue transgenic model (Wu et al, Proc Natl Acad Sci U S A 2009, 106: 7022-2027). Each tumor of the population has been comprehensively characterized histopathologically, and at the RNA and DNA level. Furthermore, the population has been adapted to conduct quantitative efficacy studies of anti-cancer agents and combinations. Results:
The HER2/SV40er and the KRAS/SV40er HIM tumors develop as invasive human breast adenocarcinoma that are histologically similar to those observed in patients. Microarray and CGH profiling demonstrated significant inter-tumor variation among the established tumors, as has been reported for patient tumors. Moreover, the KRAS/SV40er tumors clustered with basal type breast cancers from patients, a poor prognosis human breast cancer subtype. Both HER2/SV40er and KRAS/SV40er tumors exhibited variable responses to treatments with the potent selective triple VEGFR inhibitor, tivozanib. Further characterization of those tumors, both pre-and post-treatment, identified potential biomarkers for tumor response to tivozanib. Discussion:
The genetically defined human-in-mouse tumors exhibited natural variations similar to that occurs in human cancer. This population-based HIM system enables us to identify and validate biomarkers of therapeutic response in an in vivo human tumor model. Figure available in online version.
Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P1-03-06.
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