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Updated: Jan 25, 2026
Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model
Published on: March 20, 2020
Integrative analyses of triple negative dysregulated transcripts compared with non-triple negative tumors and their
Farzaneh Darbeheshti1,2, Nima Rezaei3,4,5, Mahsa M Amoli6
1Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Abstract:
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.
Insights
Triple-negative breast cancer research identified key genes and microRNAs. These dysregulated factors, including transcription factors, show potential as biomarkers and therapeutic targets for aggressive tumors.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Triple-negative breast cancer (TNBC) is an aggressive subtype with limited targeted therapy options.
- Previous microarray studies often overlooked transcript interactions and functional relationships in TNBC.
- An integrative bioinformatics approach is needed for a comprehensive understanding of TNBC molecular landscape.
Purpose of the Study:
- To identify pivotal dysregulated transcripts and their interactions in TNBC using an integrative bioinformatics strategy.
- To analyze both protein-coding and non-coding RNA in TNBC compared to non-TNBC.
- To explore potential biomarkers and therapeutic targets within the TNBC molecular network.
Main Methods:
- Utilized publicly available microarray datasets and offline bioinformatics tools.
- Performed differential expression analysis to identify upregulated and downregulated genes and miRNAs.
- Constructed coexpression, protein-protein interaction, and gene-transcriptional factor-miRNA networks.
- Conducted Kaplan-Meier plotter survival analysis for prognostic marker identification.
Main Results:
- Identified 16 upregulated and 58 downregulated genes (log fold change ≥ |2|), including nine transcription factors.
- EN1 identified as a hub gene in coexpression network and a prognostic marker for TNBC patients.
- FOXM1 and ESR1 identified as hub genes in protein-protein interaction network, potential targets for protein therapy.
- Seven differentially expressed miRNAs identified; mir-135b and mir-29b highlighted as hub nodes in gene-TF-miRNA network, interacting with GATA3.
Conclusions:
- Dysregulated transcription factors (TFs) and microRNAs (miRNAs) play critical roles in regulating the TNBC oncotranscriptomic profile.
- Identified hub genes (EN1, FOXM1, ESR1) and miRNAs (mir-135b, mir-29b) represent potential biomarkers for TNBC diagnosis and prognosis.
- These molecular players offer promising avenues for developing novel therapeutic strategies against TNBC.
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