Developing new cancer therapies or diagnostic tests relies on our comprehension of the molecular switches regulating the progress of cancer. Although advances have been made recently our knowledge about these molecular switches remains incomplete. A new approach to understanding cancer progression is to construct gene regulatory networks for specific cell types. Gene regulatory networks are constructed from high-quality gene array data from hundreds of disruptant and/or time-course experiments in cultured cells. Gene regulatory networks are best described as circuit diagrams showing cause and effect relationships between many signalling molecules within cells. They ultimately identify master regulators of gene expression represented by network ‘hubs’ from which numerous signals emanate.

We are combining novel methods developed in our group with existing published methods for analysing gene expression data and applying them to data in breast, skin and colon cancer to uncover potential targets for investigation in the laboratory. Moreover, we are combining clinical information such as patient history, survival record, tumor grade and patient age, with molecular data to improve the predictive power of our approach.