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  • Integrated Multi-Cohort Transcriptomic Analysis Identifies BST2 as a Candidate Immune-Associated Biomarker in Triple-Negative Breast Cancer

  • Salehe Amiri,1,* Babak Jahangiri,2 Elahe Asadollahi,3 Alireza Zomorodipour,4
    1. Department of Molecular Medicine, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran
    2. Department of Molecular Medicine, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran
    3. Department of Molecular Genetics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
    4. Department of Molecular Medicine, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran


  • Introduction: Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype characterized by the absence of estrogen receptor, progesterone receptor, and HER2 expression and is associated with limited targeted therapeutic options and high metastatic potential. Identification of robust molecular signatures associated with tumor progression and the immune microenvironment may facilitate the development of clinically relevant biomarkers and therapeutic hypotheses. Here, we performed an integrative multi-cohort transcriptomic analysis to identify reproducible molecular signatures and immune-associated pathways in TNBC, with particular emphasis on Bone Marrow Stromal Cell Antigen 2 (BST2).
  • Methods: Publicly available transcriptomic datasets comprising human TNBC and non-malignant breast tissue samples were obtained from the Gene Expression Omnibus (GEO), incorporating both RNA-seq and microarray platforms. Differentially expressed genes were identified across independent cohorts, and concordant expression patterns were investigated to identify robust TNBC-associated candidates. Protein–protein interaction networks were constructed using STRING and visualized in Cytoscape, with network topology assessed using CytoHubba. Functional characterization was performed using Gene Ontology and KEGG pathway enrichment through DAVID and Enrichr, complemented by Gene Set Enrichment Analysis (GSEA). BST2 expression and its clinical-stage associations were further evaluated using TCGA pan-cancer datasets, and relationships with selected immune-, chemokine-, and extracellular-matrix-associated genes were examined. In vitro expression of BST2 was additionally evaluated across five representative cancer cell lines, including the TNBC cell line MDA-MB-231.
  • Results: Integrative analysis across independent transcriptomic cohorts identified a reproducible TNBC-associated transcriptional signature enriched for immune and interferon-responsive genes. BST2 emerged as a highly connected component of an immune/interferon-associated network containing IFI27, IFI6, MX1, and OAS2. Functional enrichment analyses identified interferon-responsive and innate immune pathways, including IL-17-associated signaling, while GSEA demonstrated enrichment of proliferative programs, including E2F target and G2/M checkpoint pathways, together with interferon-α and interferon-γ response signatures. TCGA analyses further demonstrated persistent BST2 expression across TNBC clinical stages and positive associations with genes involved in extracellular-matrix remodeling, including MMP1 and MMP9, as well as chemokines such as CXCL10 and CXCL11. Among the five examined cancer cell lines, MDA-MB-231 exhibited the highest endogenous BST2 expression.
  • Conclusion: Across independent transcriptomic datasets, BST2 consistently associated with immune/interferon-responsive and tumor-associated transcriptional programs in TNBC. Its network connectivity and association with inflammatory, proliferative, chemokine, and extracellular-matrix-related signatures support BST2 as a candidate immune-associated biomarker and a potential subject for further mechanistic investigation. However, functional perturbation and independent clinical validation are required to determine whether BST2 has a tumor-cell-intrinsic regulatory role or predictive/prognostic utility and to establish its potential relevance to TNBC immunotherapy.
  • Keywords: Triple-Negative Breast Cancer, BST2, Bioinformatic analysis, Meta-Analysis, Immune response

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