Description
Cancer cells interact with surrounding stromal fibroblasts during tumorigenesis, but the complex molecular rules that govern these interactions remain poorly understood, thus hindering the development of therapeutic strategies to target cancer stroma. We have taken a mathematical approach to begin defining these rules by performing large-scale quantitative analysis of fibroblast effects on cancer cell proliferation across more than four hundred heterotypic cell line pairings. Systems-level modeling of this complex dataset using singular value decomposition revealed that normal tissue fibroblasts variably express at least two functionally distinct activities, one which reflects transcriptional programs associated with activated mesenchyme, that act either coordinately or at cross-purposes to modulate cancer cell proliferation. To gain insight into the molecular identity of these fibroblast activities, we isolated RNA from 36 human skin and lung fibroblast cell line monocultures from Coriell Repositories or ATCC and performed microarray-based gene expression profiling using Affymetrix gene chips.