A major goal of the field of systems biology is to translate genome-wide profiling data (e.g., mRNAs, miRNAs) into interpretable functional networks. However, employing a systems biology approach to better understand the complexities underlying drug resistance phenotypes in cancer continues to represent a significant challenge to the field. Previously, we derived two drug-resistant breast cancer sublines (tamoxifen- and fulvestrant-resistant cell lines) from the MCF7 breast cancer cell line and performed genome-wide mRNA and microRNA profiling to identify differential molecular pathways underlying acquired resistance to these important antiestrogens. In the current study, to further define molecular characteristics of acquired antiestrogen resistance we constructed an "integrative network". We combined joint miRNA-mRNA expression profiles, cancer contexts, miRNA-target mRNA relationships, and miRNA upstream regulators. In particular, to reduce the probability of false positive connections in the network, experimentally validated, rather than prediction-oriented, databases were utilized to obtain connectivity. Also, to improve biological interpretation, cancer contexts were incorporated into the network connectivity.