ArticleJournal of personalized medicine2023
An Angiogenesis-Related lncRNA Signature Is Associated with Prognosis and Tumor Immune Microenvironment in Breast Cancer.
Article in Journal of personalized medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 7 citations in OpenAlex.
- LCAL4-FUS cooperation switches on MMP13 and drives osteolytic bone metastasis in breast cancer.Oncogene · 2026Article
- LINC01614 favors breast cancer progression through the regulation of miR-217/FN1 and mediation in PI3K/AKT signal pathway.Translational cancer research · 2026Article
- Leveraging mitochondrial dynamics-related risk signatures to predict the prognosis and tumor microenvironment of lung adenocarcinoma.Discover oncology · 2026Article
- Expression graph network framework for biomarker discovery.Briefings in bioinformatics · 2025Article
- A lipid metabolism-related gene signature predicts prognosis after tamoxifen treatment in ER + breast cancer and reflects tumor microenvironment heterogeneity through single-cell analysis.BMC medical genomics · 2025Article
- Article
- A Model to Predict Prognosis of Renal Cell Clear Cell Carcinoma Based on 3 Angiogenesis-related Long Non-coding RNAs.Journal of Cancer · 2024Article
- Identification of cuproptosis-related gene SLC31A1 and upstream LncRNA-miRNA regulatory axis in breast cancer.Scientific reports · 2023Article
- The current advances of lncRNAs in breast cancer immunobiology research.Frontiers in immunology · 2023Review
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Angiogenesis is crucial in the development and progression of tumors. This study examined the relationship between angiogenesis-related lncRNAs (AR-lncRNAs) and breast cancer (BC) immunity and prognosis. We used univariate Cox regression analysis to obtain AR-lncRNAs closely related to BC prognosis. Cluster analysis of BC patients was performed using non-negative matrix factorization (NMF) analysis according to the expression of AR-lncRNAs that were prognostically relevant. An AR-lncRNA risk model (AR-lncM) was created using LASSO regression analysis to predict the prognosis and survival of BC patients. Subsequently, the effect of LINC01614 on cell migration and invasion was verified by Transwell and Western blot assays, and the CCK-8 assay detected its impact on cell sensitivity to tamoxifen. Finally, we obtained 17 AR-lncRNAs from the TCGA database that were closely associated with the prognosis of BC patients. Based on the expression of these AR-lncRNAs, BC patients were divided into five clusters using NMF analysis. Cluster 1 was found to have a better prognosis, higher expression of immune checkpoints, and higher levels of immune cell infiltration. Furthermore, an AR-LncM model was created using ten prognostic-related AR-lncRNAs. The model's risk predictive performance was validated using survival analysis, timeROC curves, and univariate and multivariate Cox analysis. The most interesting gene in the model, LINC01614, was found to regulate epithelial-mesenchymal transition (EMT) and tamoxifen sensitivity in BC cells, implying that LINC01614 could be a potential therapeutic target for BC patients.
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