Cancer is a complex disease that impacts a variety of processes resulting from dynamic alterations in highly connected cellular networks and microenvironments. While cellular networks can be quantified with high-throughput technologies to assess global activity, current technologies measure abundances of molecules that may not be translatable and do not capture dynamic events. Active transcription factors (TFs) are the downstream products of signaling pathways that are critical regulators of cellular processes and tissue development. This dissertation presents the development of cellular arrays for dynamic, large-scale quantification of TF activity as cells organize into tissue-like structures within 3D culture. TF-specific reporter constructs were delivered in parallel to a cellular array containing mammary epithelial cells cultured in the natural matrix, Matrigel, to form multi-cellular structures. Bioluminescence imaging provided a rapid, non-invasive and sensitive method to quantify reporter gene activity and was applied repeatedly on each sample to monitor dynamic activity. Many of the TFs investigated displayed dynamic activity, demonstrating the capability of the array to measure large-scale signaling events. The technology was further applied to exploring ErbB2 signaling in cancer. Cells expressing a mutant, inducible ErbB2 receptor were cultured in Matrigel and formed non-cancerous or cancerous structures contingent on ErbB2 activation, and ErbB2-activated cells showed different susceptibilities to trastuzumab, pertuzumab, and lapatinib. Arrays identified TFs that were differentially activated during structure development or following therapeutic treatment. Finally, while natural matrices can permit the formation of multi-cellular structures that are architecturally and functionally relevant, they are complex with a variety of signals and not readily controllable. In order to better understand the roles of the microenvironment in directing tissue development and cancer progression, a synthetic hydrogel (polyethylene glycol (PEG)) was employed to investigate how matrix-derived adhesion signals in a simplified system relate to tissue organization. Structures formed for both normal and cancerous cells, and the responses to adhesion peptides depended on cell genotype. Together, this dissertation presents work that will further our understanding of cancer progression and presents tools that could be employed to discover new targets for diagnosis or treatment.