Multi-omics single-cell dissection of malignant epithelial heterogeneity identifies GJB2 as an EMT-driving biomarker in triple-negative breast cancer

Tumor heterogeneity poses a major challenge to elucidating the mechanisms underlying tumor progression and metastasis. However, the cellular heterogeneity of triple-negative breast cancer (TNBC) remains incompletely understood. We performed an integrated analysis of publicly available single-cell RNA sequencing (scRNA-seq) datasets from TNBC to identify distinct malignant cell subtypes. Multiple analytical approaches were then applied to comprehensively characterize the metastasis-related subtype. Subsequently, we validated GJB2 as a biomarker of this subtype and confirmed its association with epithelial–mesenchymal transition (EMT) in TNBC cell lines. Based on six scRNA-seq datasets from GSE180286 and GSE161529, we constructed a comprehensive landscape of malignant-cell heterogeneity in TNBC and identified three malignant cell subtypes: an EMT-Subtype, a secretory-like subtype (Sec-like Subtype), and a metabolic subtype (Metab-Subtype). We further identified GJB2 as a marker of the EMT-Subtype. Enrichment analyses indicated that GJB2 was closely associated with the TGF-β signaling pathway, and this finding was further supported by in vitro functional assays. By classifying malignant TNBC cells into three subtypes, we identified GJB2 as a marker of the EMT-Subtype. Mechanistically, GJB2 may promote EMT through the TGF-β signaling pathway and therefore represent a potential therapeutic target in TNBC. Targeting the GJB2–TGF-β axis may provide a promising strategy for suppressing the highly metastatic behavior of TNBC.

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Publication Details

Journal
BMC Medical Genomics
Published
2026-04-27
DOI
https://doi.org/10.1186/s12920-026-02378-7
Primary Topic
Cancer Cells and Metastasis
Type
article
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article

Multi-omics single-cell dissection of malignant epithelial heterogeneity identifies GJB2 as an EMT-driving biomarker in triple-negative breast cancer

Shuyi Zhang, Zhou G, Hongjie Xu, Chengzhi Zhang et al.
BMC Medical Genomics
Cancer Cells and Metastasis
article

Multi-omics single-cell dissection of malignant epithelial heterogeneity identifies GJB2 as an EMT-driving biomarker in triple-negative breast cancer

Shuyi Zhang, Zhou G, Hongjie Xu, Chengzhi Zhang, Xinyi Zhang
article en

Abstract

Tumor heterogeneity poses a major challenge to elucidating the mechanisms underlying tumor progression and metastasis. However, the cellular heterogeneity of triple-negative breast cancer (TNBC) remains incompletely understood. We performed an integrated analysis of publicly available single-cell RNA sequencing (scRNA-seq) datasets from TNBC to identify distinct malignant cell subtypes. Multiple analytical approaches were then applied to comprehensively characterize the metastasis-related subtype. Subsequently, we validated GJB2 as a biomarker of this subtype and confirmed its association with epithelial–mesenchymal transition (EMT) in TNBC cell lines. Based on six scRNA-seq datasets from GSE180286 and GSE161529, we constructed a comprehensive landscape of malignant-cell heterogeneity in TNBC and identified three malignant cell subtypes: an EMT-Subtype, a secretory-like subtype (Sec-like Subtype), and a metabolic subtype (Metab-Subtype). We further identified GJB2 as a marker of the EMT-Subtype. Enrichment analyses indicated that GJB2 was closely associated with the TGF-β signaling pathway, and this finding was further supported by in vitro functional assays. By classifying malignant TNBC cells into three subtypes, we identified GJB2 as a marker of the EMT-Subtype. Mechanistically, GJB2 may promote EMT through the TGF-β signaling pathway and therefore represent a potential therapeutic target in TNBC. Targeting the GJB2–TGF-β axis may provide a promising strategy for suppressing the highly metastatic behavior of TNBC.

BMC Medical Genomics
Xuzhou Medical College (CN), Nantong University (CN), Yancheng First People's Hospital (CN), Yancheng Teachers University (CN), Yancheng Institute of Technology (CN)
Good health and well-being
Openalex Percentile: Top 7%
Cancer Cells and Metastasis
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