Triple-negative (TN) tumors are a subtype of breast cancer with aggressive behaviors and limited targeted therapies. Microarray studies were not concerned with interactions and functional relations of dysregulated transcripts. Here, we aimed to conduct integrative strategy to analyze gene and miRNA available microarray data as well as bioinformatic analyses to catch a more inclusive picture of pivotal dysregulated transcripts and their interactions in TN tumors. Several online datasets and offline bioinformatic tools were used to detect differentially expressed (DE) transcripts, both protein and nonprotein coding, in TN compared with non-TN tumors and their functional and molecular interactions. Sixteen upregulated and 58 downregulated genes with a log fold change higher or equal to | 2 | were identified, including nine transcription factors. Coexpression network revealed EN1 as a hub gene, moreover Kaplan-Meier plotter survival analysis indicated that it was an appropriate prognostic marker for TN patients with breast cancer. Functional annotation analysis of protein-protein interaction network showed FOXM1 as an upexpressed and ESR1 as a downexpressed hub genes are suitable targets as far as antitumor protein therapy is concerned in TN breast cancers. The consensus analysis of two microRNA datasets revealed seven DE miRNAs. The gene-transcriptional factor (TF)-miRNA network revealed mir-135b and mir-29b are the hub nodes and involved in feedback loops with GATA3. This study suggests that dysregulated TFs and miRNAs have pivotal roles in regulation of TN oncotranscriptomic profile and might become both biomarkers and therapeutic targets.
Keywords: bioinformatics analysis; differentially expressed gene; hub genes; miRNAs; microarray; triple-negative breast cancer.
© 2019 Wiley Periodicals, Inc.