Multi-Omic Data Interpretation to Repurpose Subtype Specific Drug Candidates for Breast Cancer - Turanli, Beste; Karagoz, Kubra; Bidkhori, Gholamreza; Sinha, Raghu; Gatza, Michael L.; Uhlen, Mathias; Mardinoglu, Adil; Arga, Kazim Yalcin (Frontiers in Genetics, 2019)
Triple-negative breast cancer (TNBC), which is largely synonymous with the basal-like molecular subtype, is the 5th leading cause of cancer deaths for women in the USA. The overall prognosis for TNBC patients remains poor given that few treatment options exist, including no FDA approved targeted therapies, and standard-of-care treatment remains multi-agent chemotherapy. TNBC like other complex diseases is governed by the perturbations of the complex interaction networks, therefore, elucidating the underlying molecular mechanisms of this disease in the context of network principles has the potential to identify targets for drug development. Here, we presented an integrated “omics” approach based on the use of transcriptome and interactome data to identify dynamic/active protein-protein interaction networks in TNBC patients. We have identified three highly connected modules, EED, DHX9 and AURKA, which are highly activated in TNBC tumors compared to both normal tissues and other breast cancer subtypes. Based on functional analyses, we proposed that these modules are potential drivers of proliferation and, as such, should be considered as candidate molecular targets for drug development or drug repositioning in TNBC. Consistent with this argument, we repurposed steroids, anti-inflammatory agents, anti-infective agents, cardiovascular agents for patients with basal-like breast cancer. Finally, we have performed essential metabolite analysis on personalized genome-scale metabolic models and found that metabolites such as sphingosine-1-phosphate and cholesterol-sulfate have utmost important in TNBC tumor growth.