In this study, we investigate the ability of statistical co-expression networks to highlight and prioritize significant genes at four different breast cancer molecular subtypes, including Luminal A, Luminal B, HER2 and Triple Negative as well as at four different disease stages (I-IV) in terms of: (i) classification efficiency, (ii) gene subnetwork conservation, (iii) involved molecular mechanisms investigation and (iv) potential boost to drug repurposing pipelines. Here, ERBB2 is linked to breast carcinoma.