Abstract 4189: Utilization of Champions Tumorgraft™ models to identify putative biomarkers and signatures of response

Abstract

Abstract Champions Biotechnology has developed an innovative platform for oncology research that utilizes the implantation of primary human tumors in immune-deficient mice in a manner that preserves the biological properties of the original human tumor. Given the unique features and extensive characterization of the Champions Tumorgraft™ platform, it can be utilized for the identification and validation of putative biomarkers and signatures of response which predict resistance or sensitivity to anti cancer agents in specific patient populations. Models of colorectal cancer, NSCLC, and pancreatic cancer were subjected to cetuximab or irinotecan, cisplatin or paclitaxel, and gemcitabine, respectively. Tumor growth inhibition of 50% was utilized as the criteria to delineate sensitive versus resistant models. Baseline whole genome-transcriptome profiles were compared in sensitive and resistant models, and the top 100 genes differentially expressed between these phenotypes were selected by signal-to-noise metric. Pathways up regulated in sensitive and resistant Tumorgraft™ models were determined by an unbiased gene set enrichment analysis. Colon Tumorgraft™ models treated with either cetuximab or irinotecan showed sensitivity in 6/14 models and 8/11 models, respectively. NSCLC Tumorgraft™ models treated with either cisplatin or paclitaxel showed sensitivity in 4/12 models and 10/13 models, respectively. Lastly, pancreatic Tumorgraft™ models treated with gemcitabine showed sensitivity in 15/17 models. Bioinformatic analysis revealed, for example, that a number of signaling pathways involved in survival, proliferation, angiogenesis, adhesion, cell cycle control, metabolism, and apoptosis are significantly modulated in these sensitive and resistant cancer models. Validation of key genes and pathways is onging. Together, these results demonstrate that Champions TumorgraftTM models can be utilized to identify potential biomarkers of response and represent a novel in vivo platform capable of predicting the clinical effectiveness of anti cancer drugs. Furthermore, the combined framework of Champions Tumorgrafts™ and bioinformatic analyses, as described here, can not only be applied to clinically approved agents, but also to agents in development, hereby increasing the efficiency of oncology drug development by identifying those patients most likely to respond to a given therapy. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4189. doi:10.1158/1538-7445.AM2011-4189