This article is part of the supplement: Selected Proceedings of the 2010 AMIA Summit on Translational Bioinformatics
Stromal microenvironment processes unveiled by biological component analysis of gene expression in xenograft tumor models
- Equal contributors
1 Section of Genetic Medicine, Dept. of Medicine, University of Chicago, IL, USA
2 Sect. of Hematology/Oncology, Dept. of Medicine, University of Chicago, IL, USA
3 Dept. of Pathology and of Radiation and Cellular Oncology; University of Chicago, IL, USA
4 UC Comprehensive Cancer Centre; Ludwig Centre for Metastasis Research; University of Chicago, IL, USA
5 Institute of Genomics and Systems Biology; Institute for Translational Medicine; Computational Institute, University of Chicago, IL, USA
BMC Bioinformatics 2010, 11(Suppl 9):S11 doi:10.1186/1471-2105-11-S9-S11Published: 28 October 2010
Mouse xenograft models, in which human cancer cells are implanted in immune-suppressed mice, have been popular for studying the mechanisms of novel therapeutic targets, tumor progression and metastasis. We hypothesized that we could exploit the interspecies genetic differences in these experiments. Our purpose is to elucidate stromal microenvironment signals from probes on human arrays unintentionally cross-hybridizing with mouse homologous genes in xenograft tumor models.
By identifying cross-species hybridizing probes from sequence alignment and cross-species hybridization experiment for the human whole-genome arrays, deregulated stromal genes can be identified and then their biological significance were predicted from enrichment studies. Comparing these results with those found by the laser capture microdissection of stromal cells from tumor specimens resulted in the discovery of significantly enriched stromal biological processes.
Using this method, in addition to their primary endpoints, researchers can leverage xenograft experiments to better characterize the tumor microenvironment without additional costs. The Xhyb probes and R script are available at http://www.lussierlab.org/publications/Stroma webcite