A Transcriptome- and Interactome-Based Analysis Identifies Repurposable Drugs for Human Breast Cancer Subtypes

Breast cancer (BC) is a heterogeneous and complex disease characterized by different subtypeswith distinct morphologies and clinical implications and for which new and effective treatment optionsare urgently demanded. The computational approaches recently developed for drug repurposingprovide a very promising opportunity to offer tools that efficiently screen potential novel medicalindications for various drugs that are already approved and used in clinical practice. Here, we startedwith disease-associated genes that were identified through a transcriptome-based analysis, which weused to predict potential repurposable drugs for various breast cancer subtypes by using an algorithmthat we developed for drug repurposing called SAveRUNNER. Our findings were also in silico validatedby performing a gene set enrichment analysis, which confirmed that most of the predicted repurposabledrugs may have a potential treatment effect against breast cancer pathophenotypes.