3MOONS - Project Summary

Cancer is a multifactorial disease with a striking heterogeneity due to genetic, epigenetic and transcriptional changes involving a myriad of genes and proteins. While these factors are relevant to clinical prognosis and medical treatment of patients, a system's approach is needed to unravel the complexities underlying intertwining carcinogenesis mechanisms. Given accurate experimental measurements, the presence at multiple scales of stochastic dynamics involved in gene regulation and proteinprotein interactions (PPI) requires that both the analysis of differential (cancer versus normal) conditions and the treatment of the associated uncertainty are taken at combined omicsscale levels. In particular, networks allow for the straightforward integration between molecular, genetic, clinical and topological features in a unifying context. Models can then be built from networkembedded measurable values to assess the variation significantly affecting the cellular mechanisms involved in cancer. By treating cancer as a systems disease, powerful computational instruments become available, and especially networkbased inference can drive the translation of systems biology to systems medicine by shifting the focus on the clinical impact