Systems Biology, Bioinformatics and Medicine Approaches to Cancer Progression Outcomes

Because of the complexity of carcinogenesis and tumour development, it is critical to understand the underlying organizing principles. In this chapter a possible approach is illustrated, starting with a description of breast cancer prognosis as a function of three powerful biological motifs derived from gene expression profiling. A proliferation metagene describing the transition from slow to fast proliferation leads to the most dramatic aggravation of prognosis. A second immune cell metagene represents an opponent of tumour evolution, whereby only fast-proliferating tumours that are not recognized and eliminated by immune cells can progress. In the absence of endocrine treatment, a third motif, the oestrogen receptor metagene, is of limited prognostic importance, although it is required to model the interactions between the proliferation and immune cell axes. The subsequent and critical step will be to model the gene array-derived biological motifs as a function of a manageable number of signalling pathways or signalling network constellations. The advantages of translating biological motifs into pathway signatures are the possibility of identification of pathologic pathways in individual tumours, and the perspective of selecting appropriate drugs. In recent years much progress has been achieved in the field of spatial-temporal tissue modelling. Spatial-temporal models simulating tissue regeneration or 3D tumour infiltration are available. However, the ambitious goal of fully linking spatial-temporal tissue development to single-cell decisions created by molecular models of signalling network constellations is yet to be achieved.