ArticleNPJ precision oncology2025
Quantitative proteomics analysis of triple-negative breast cancers.
Article in NPJ precision oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Macrophage-supported metabolic adaptation drives tumor survival under nutrient stress.Science advances · 2026Article
- Proteomic Biomarker Discovery in Breast Cancer: Advances, Challenges, and Translational Prospects.Journal of biochemical and molecular toxicology · 2026Review
- Multi-Omics Integration Identifies Ferroptosis-Related miRNA-mRNA Networks and Independent Prognostic miRNAs in Triple-Negative Breast Cancer.Journal of clinical practice and research · 2026Article
- Hijacking emergency granulopoiesis: Neutrophil ontogeny and reprogramming in cancer.Molecular oncology · 2026Review
- Focal hotspot and diffuse immune subtypes of tumor-infiltrating lymphocytes: AI-powered spatial clustering classification and its clinical relevance to HER2 expression in triple-negative breast cancer.Journal of translational medicine · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Triple-negative breast cancer (TNBC) accounts for approximately 15% of all Breast Cancer (BC) cases with poorer prognosis and clinical outcomes compared to other BC subtypes due to greater tumor heterogeneity and few therapeutically targetable oncogenic drivers. To reveal actionable pathways for anti-cancer treatment, we use a proteomic approach to quantitatively compare the abundances of 6306 proteins across 55 formalin-fixed and paraffin-embedded (FFPE) TNBC tumors. We identified four major TNBC clusters by unsupervised clustering analysis of protein abundances. Analyses of clinicopathological characteristics revealed associations between the proteomic profiles and clinical phenotypes exhibited by each subtype. We validate the findings by inferring immune and stromal cell type composition from genome-wide DNA methylation profiles. Finally, quantitative proteomics on TNBC cell lines was conducted to identify in vitro models for each subtype. Collectively, our data provide subtype-specific insights into molecular drivers, clinicopathological phenotypes, tumor microenvironment (TME) compositions, and potential pharmacologic vulnerabilities for further investigations.
Identifiers
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Registered trials
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