proteins and genes act in coordinated ways, and their relations are visualized as networks. Networks are more accurate descriptions of cancer regulatory mechanisms, in comparison to lists of oncogenes and tumor suppressors. To extract essential regulators (nodes) and connections (edges), interrogations of these networks are performed, e.g. cancer cells are subjected to different treatments. Interrogations force cancer cells to engage nodes and edges essential for maintaining cancer properties, i.e. drivers, and nonessential followers. The challenge is to discriminate which of the mechanisms drive tumorigenesis, and which are followers. Interrogation of cancer cells under variable g-forces is the treatment to which cancer cells are not normally exposed. Therefore, low (weightlessness) and high (acceleration) g-forces may trigger responses, which may differ in part of followers from responses on the Earth, but still engage carcinogenesis-essential drivers nodes and edges. Methodology: Experimental interrogation of human cancer cells to generate carcinogenesis-related regulatory networks was performed by using proteomics, cell biology, biochemistry, immunohistochemistry and bioinformatics tools. We used also reported datasets deposited in various databases. These networks were analyzed with algorithms to extract drivers of carcinogenesis. Results: Systemic analysis of human breast carcinogenesis has shown mechanisms of engagement of all known cancer hallmarks. Moreover, novel hallmarks have emerged, e.g. involvement of mechanisms of virus-cell interaction and RNA/miR processing. The breast cancer networks are rich, with >6,000 involved proteins and genes. The richness of the networks may explain many clinical observations, e.g. personalized response to treatments. Systemic analysis highlighted novel opportunities for treatment of cancer, by identifying key nodes of known and novel hallmark mechanisms. Systemic properties of the cancer network provides an opportunity to study compensatory mechanisms. These compensatory mechanisms frequently contribute to development of resistance to treatment. These mechanisms will be discussed. Cancer cells are not “wired” to function in weightlessness. The cells would have to adapt. This adaptation will include preserving mechanisms driving carcinogenesis, in addition to the space-only-related adaptation. Key carcinogenesis regulators in the space would be the same as on the Earth, while “passenger”-mechanisms would differ. Systems biology allows integration of a space- and the Earth-data, and would extract key regulators, and, subsequently lead to better diagnostic. Conclusion: Systemic analysis of carcinogenesis studies with different ways of interrogation delivered better diagnostic and novel modalities of treatment.
Bayesian Integrative Modeling of Genome-Scale Metabolic and Regulatory Networks