ARTICLE ABSTRACT
The complex yet interrelated connections between cancer metabolism, gene expression, and oncogenic driver genes have the potential to identify novel biomarkers and drug targets with prognostic and therapeutic value. Here we effectively integrated metabolomics and gene expression data from breast cancer mouse models through a novel unbiased correlation-based network analysis. This approach identified 35 metabolite and 34 gene hubs with the most network correlations. These hubs have prognostic value and are likely integral to tumor metabolism and breast cancer. The gene hub Aquaporin-7 (Aqp7), a water and glycerol channel, was identified as a novel regulator of breast cancer. AQP7 was prognostic of overall survival in patients with breast cancer. In mouse breast cancer models, reduced expression of Aqp7 caused reduced primary tumor burden and lung metastasis. Metabolomics and complex lipid profiling of cells and tumors with reduced Aqp7 revealed significantly altered lipid metabolism, glutathione metabolism, and urea/arginine metabolism compared with controls. These data identify AQP7 as a critical regulator of metabolic and signaling responses to environmental cellular stresses in breast cancer, highlighting AQP7 as a potential cancer-specific therapeutic vulnerability.
Aquaporin-7 is identified as a critical regulator of nutrient availability and signaling that responds to cellular stresses, making it an attractive therapeutic target in breast cancer.
