A current topic of interest in the biology of cancer is how cells respond dynamically to changes in their environment utilizing their cellular gene, RNA and protein networks. We aim to approach this question by investigating endogenous signal transduction and transcriptional regulatory networks of coding and non-coding RNA in yeast and cancer cells. The regulatory principles discovered in yeast will then be tested in healthy and cancerous mammalian tissue to test their generality. We aim to investigate the architecture and functioning of these networks by measuring the dynamics of protein and RNA levels in single cells. Our research methods include a combination of single-cell techniques such as flow cytometry, live cell time-lapse microscopy, fluorescent in-situ hybridization with single-molecule resolution at the RNA level (single-molecule RNA-FISH) in cells and tissue samples as well as single-molecule-based modeling. The main advantage to quantify single cells is to distinguish between different regulatory mechanisms, which cannot be observed in population-based experiments. Since our approach is general, it can lead to quantitative understanding of many genes, pathways or organisms and their malfunctioning in human cancers.