A26
A systems biology approach to modelling cell-to-cell communication in cancer
Victor Trevino1, John Herbert1, Rita Gupta1, Sarah Durant1, Philipp Antczcak1, Andreas Bikfalvi2, Roy Biknell1, Francesco Falciani1
1University of Birmingham, UK, 2University Bordeaux I, Bordeaux, France
The recent development of genome-wide functional genomics techniques (i.e. microarray-based expression profiling), coupled with the ability to dissect specific cell types from a complex tissues have created an unprecedented opportunity to characterise the molecular identity of specific cell types in the context of a complex tissue. This has contributed to establish that components of the transcriptional profile of tumour cells are predictive of both tumour features and clinical outcome in a variety of human cancers.
The availability of this unprecedented amount of information has also stimulated the development of advanced computational methods for the analysis and interpretation of complex multi-dimensional datasets. Among these, methods which allow the inference of gene regulatory networks from observational data have been used to generating more robust hypothesis on the molecular interaction underlying the patho-physiology of Cancer. However, so far these approaches did not explicitly include cell interaction in the model structure.
Here we describe the development of a new methodology to infer the structure of regulatory networks involved in the interaction between different cell types. We have applied this methodology to two different gene expression datasets representing micro-dissected human normal and tumour prostate epithelial cells. Our models suggest the existence of signals produced by normal epithelial cells which controls biological functions that are rate limiting for cell division. In vitro co-culture experiments designed to validate the model predictions support these hypotheses and further validate the computational approach.
We conclude by discussing the biological implications of our hypothesis and support the general validity of our approach with preliminary results based on an in vivo angiogenesis experimental model.
