During cell progression from one state to another, such as transformation from benign to malignant conditions, cells undergo changes in gene regulation. To reveal state-dependent circuitries in human regulatory networks, we employed drafts of normal and malignant cell networks. Using these condition specific networks, gene profiles and annotated pathways we studied: a) the capacity to separate samples or cell states based on the collective expression of all the genes in each pathway rather than individual genes, b) the degree of regulatory network connectivity within and between pathways. Distinct cell types reveal notable differences in transcriptional activity in numerous pathways. On the other hand, in datasets from breast cancer patients with variable outcome the capacity of single pathway expression signatures to predict disease outcome is very limited, though this can be somewhat improved by combining multiple pathways. Remarkable connectivity between pathways on the transcriptional regulatory level revealed a non-modular network structure. Overall, network blueprints enable us to quantify the degree of interaction between condition specific co-regulated pathways. This can contribute to understanding deregulated processes associated with cancer.