Background: The term triple-negative breast cancer (TNBC) is used to describe breast cancers without expression\nof estrogen receptor, progesterone receptor or HER2 amplification. To advance targeted treatment options for\nTNBC, it is critical that the subtypes within this classification be described in regard to their characteristic biology\nand gene expression. The Cancer Genome Atlas (TCGA) dataset provides not only clinical and mRNA expression\ndata but also expression data for microRNAs.\nResults: In this study, we applied the Lehmann classifier to TCGA-derived TNBC cases which also contained\nmicroRNA expression data and derived subtype-specific microRNA expression patterns. Subsequent analyses\nintegrated known and predicted microRNA-mRNA regulatory nodes as well as patient survival data to identify key\nnetworks. Notably, basal-like 1 (BL1) TNBCs were distinguished from basal-like 2 TNBCs through up-regulation of\nmembers of the miR-17-92 cluster of microRNAs and suppression of several known miR-17-92 targets including\ninositol polyphosphate 4-phosphatase type II, INPP4B.\nConclusions: These data demonstrate TNBC subtype-specific microRNA and target mRNA expression which may be\napplied to future biomarker and therapeutic development studies.
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