ArticleCancer cell international2023
Characterization of cancer-associated fibroblasts (CAFs) and development of a CAF-based risk model for triple-negative breast cancer.
Article in Cancer cell international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Cancer-associated fibroblasts secrete CSF3 to promote TNBC progression via enhancing PGM2L1-dependent glycolysis reprogramming.Cell death & disease · 2025Article
- Tumor Microenvironment Dynamics of Triple-Negative Breast Cancer Under Radiation Therapy.International journal of molecular sciences · 2025Review
- Effect of liraglutide on the dysglycemia, inflammation, and gut microbiota in prediabetic KKay mice.Frontiers in pharmacology · 2025Article
- The role of CAFs in therapeutic resistance in triple negative breast cancer: an emerging challenge.Frontiers in molecular biosciences · 2025Review
- GPR34 Stabilized by Deubiquitinase USP8 Suppresses Ferroptosis of ATC.Mediators of inflammation · 2025Article
- Cancer-associated fibroblasts affect breast cancer cell sensitivity to chemotherapeutic agents by regulating NRBP2.Toxicology research · 2024Article
- Evaluation of Targeted Alpha Therapy Using [International journal of molecular sciences · 2024Article
- Breast Cancer Stem Cells Upregulate IRF6 in Stromal Fibroblasts to Induce Stromagenesis.Cells · 2024Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Triple-negative breast Cancer (TNBC) is a highly malignant cancer with unclear pathogenesis. Within the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) vitally influence tumor onset and progression. Thus, this research aimed to identify distinct subgroups of CAF using single-cell and TNBC-related information from the GEO and TCGA databases, respectively. The primary aim was to establish a novel predictive model based on the CAF features and their clinical relevance. Moreover, the CAFs were analyzed for their immune characteristics, response to immunotherapy, and sensitivity to different drugs. The developed predictive model demonstrated significant effectiveness in determining the prognosis of patients with TNBC, TME, and the immune landscape of the tumor. Of note, the expression of GPR34 was significantly higher in TNBC tissues compared to that in other breast cancer (non-TNBC) tissues, indicating that GPR34 plays a crucial role in the onset and progression of TNBC. In summary, this research has yielded a novel predictive model for TNBC that holds promise for the accurate prediction of prognosis and response to immunotherapy in patients with TNBC.
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Registered trials
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