Abstract Tumour growth is governed by the interaction with its microenvironment through pathways that regulate tumour cell function, angiogenesis, and recruitment of associated stromal cells and immune infiltrate. These complicated biological networks can be studied in tumour xenografts using a combination of gene expression, protein and histological analysis. The majority of gene expression studies either probe expression of specific transcripts by RT-qPCR, or use broad Affymetrix microarrays to examine 1000s of genes. RT-PCR experiments may be too focussed studying the interaction of a small number of pathways, while Affymetrix is often not sensitive enough to detect low abundance transcripts, or is limited by species specificity of the probe sets. For example studying tumour stromal and endothelial cells can be challenging because these cells comprise only a small proportion of the tumour. In this study we have used high throughput RT-qPCR to specifically analyse 180 human and mouse genes (or orthologues) thought to regulate key stromal/tumour interactions in a broad xenograft panel. This approach enabled us to determine the expression patterns of potential angiogenic, migratory and survival drives of a diverse range of tumour xenograft models. Across the xenograft panel these genes distinguished tumours with an Epithelial and Mesenchymal phenotype. Interestingly we find that the transcript profile of the supporting stroma (all murine transcripts) is similar between models and key genes cluster with physiological characteristics such vessel, stromal or inflammatory phenotypes. We also used this approach to assess pharmacodynamic changes in gene expression in the tumour and host compartments in response to a VEGF signalling inhibitor. Surprisingly there was little modulation in the expression of genes in the tumour cell compartment. However, there was a clear down regulation of transcripts corresponding to endothelial cells with a concomitant reduction in the tumour vasculature. This approach has enabled us to gain insight into pre-clinical models and the response to a host targetted therapy. The data provides information that enhances understanding that can be derived using histological analysis and standard protein expression. 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 1564. doi:10.1158/1538-7445.AM2011-1564