Evidence map›Paper›PMID 40627035›Full record

ArticleFunctional & integrative genomics2025

Immune-based molecular subtyping of triple-negative breast cancer via SNF-CC and functional validation of key immune-associated genes.

Pengwei Guo, Fengfei Yan, Hui Chang, Fuchun Li, Jinpeng Hu, Meizhe Liu, Aidong Li

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Article in Functional & integrative genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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7 authors.

Pengwei Guo *Department of Medical, Harbin North People's Hospital, Harbin, 150001, China.
Fengfei Yan *Department of Vascular Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, China.
Hui ChangDepartment of Oncology and Laparoscopy Surgery, The First Affiliated Hospital of Harbin Medical University, No. 23, Post Street, Nangang District, Harbin, 150001, Heilongjiang Province, China.
Fuchun LiDepartment of Oncology and Laparoscopy Surgery, The First Affiliated Hospital of Harbin Medical University, No. 23, Post Street, Nangang District, Harbin, 150001, Heilongjiang Province, China.
Jinpeng HuDepartment of Oncology and Laparoscopy Surgery, The First Affiliated Hospital of Harbin Medical University, No. 23, Post Street, Nangang District, Harbin, 150001, Heilongjiang Province, China.
Meizhe LiuDepartment of Oncology and Laparoscopy Surgery, The First Affiliated Hospital of Harbin Medical University, No. 23, Post Street, Nangang District, Harbin, 150001, Heilongjiang Province, China.
Aidong LiDepartment of Oncology and Laparoscopy Surgery, The First Affiliated Hospital of Harbin Medical University, No. 23, Post Street, Nangang District, Harbin, 150001, Heilongjiang Province, China. liaidong1964212@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) presents significant therapeutic challenges due to its aggressive nature and lack of targeted treatment options. Emerging evidence highlights the critical role of immune infiltration patterns in TNBC progression and prognosis, yet a comprehensive classification system integrating immune and transcriptomic features remains elusive. In this study, we employed the xCell algorithm to characterize immune infiltration across TNBC samples and utilized the Similarity Network Fusion and Consensus Clustering (SNF-CC) method to identify molecular subtypes. Our analysis revealed three distinct TNBC subtypes with marked heterogeneity in transcriptomic profiles and immune microenvironment composition. Subtype 1 exhibited high immune infiltration, while Subtype 3 demonstrated immunosuppressive characteristics. Functional enrichment analysis linked subtype-specific differentially expressed genes (DEGs) to pathways such as T-cell activation and cytokine signaling. Protein-protein interaction networks identified key hub genes (PTPRC, CD4, and UBE2C) showing elevated expression in TNBC tissues. Experimental validation in breast cancer cell lines confirmed that knockout of PTPRC, CD4, or UBE2C significantly impaired proliferation, migration, and invasion, while rescue experiments restored these oncogenic phenotypes. These findings establish an immune-based molecular subtyping framework for TNBC and uncover pivotal genes driving tumor progression. Our work provides novel insights into TNBC heterogeneity and identifies potential therapeutic targets for precision immunotherapy, advancing strategies to improve clinical outcomes in this recalcitrant malignancy.

Indexed as

Triple Negative Breast NeoplasmsCell Line, TumorCell ProliferationFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansProtein Interaction MapsTranscriptomeTumor MicroenvironmentUbiquitin-Conjugating EnzymesUbiquitin-Conjugating EnzymesCD4Immune infiltrationMolecular subtypingPTPRCTriple-negative breast cancerTumor microenvironmentUBE2C

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.