ArticleBreast cancer (Dove Medical Press)2025
Telomere Maintenance-Related Genes are Essential for Prognosis in Breast Cancer.
Article in Breast cancer (Dove Medical Press), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Neuroimmune dysregulation and comorbidity mechanisms of major depressive disorder and migraine.BMC psychiatry · 2026Article
- Telomere Maintenance Characteristics Predict Prognosis and Therapeutic Response in Colorectal Cancer.Current topics in medicinal chemistry · 2026Article
- Spatial transcriptome and single-cell sequencing reveal the role of nucleotide metabolism in breast cancer progression and tumor microenvironment.Frontiers in oncology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Telomere maintenance mechanism significantly impacts the metastasis, progression, and survival of breast cancer (BC) patients. This study aimed to investigate the role of telomere maintenance-related genes (TMRGs) in BC prognosis and to construct a related prognostic model. Methods: Differentially expressed genes were identified from the TCGA-BC cohort, and functional enrichment analysis was conducted. TMRGs were sourced from the literature and intersected with DEGs. Candidate genes were selected using machine learning algorithms, including Lasso Cox, Random Forest, and XGBoost. Multivariate Cox regression analysis was conducted to construct a prognostic model and identify hub genes. Subsequent analyses included survival analysis, gene set enrichment analysis (GSEA), immune infiltration analysis, and drug sensitivity analysis of the hub genes. Finally, in vitro experiments were conducted to validate the expression of the hub genes. Results: A total of 1329 differentially expressed TMRGs were analyzed, with 128 significantly associated with overall survival. Machine learning identified 7 prognosis-related TMRGs: MECP2, PCMT1, PFKL, PTMA, TAGLN2, TRMT5, and XRCC4. These genes were used to construct a prognostic model, with MECP2, PCMT1, PFKL, TAGLN2, and XRCC4 as harmful factors, while PTMA and TRMT5 were protective. The model demonstrated a significant prognostic value (AUC: 0.81, 0.72, 0.69 for 1-, 3-, and 5-year, respectively). Survival analysis confirmed the prognostic relevance of these genes, and GSEA highlighted their roles in oxidative phosphorylation, glycolysis, and PI3K/AKT/mTOR signaling. Conclusion: The study identified 7 key TMRGs with significant prognostic value in BC. The constructed model effectively stratifies patient risk, providing a foundation for targeted therapies and personalized treatment strategies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.