ArticleDisease markers2022
Establishment and Analysis of an Individualized EMT-Related Gene Signature for the Prognosis of Breast Cancer in Female Patients.
Article in Disease markers, 2022. 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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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.
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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
9 citing papers in PubMed.
- P3H1 promotes malignant progression of esophageal squamous cell carcinoma (ESCC) and modulates the immune microenvironment.Journal of thoracic disease · 2025Article
- EMT and cancer: what clinicians should know.Nature reviews. Clinical oncology · 2025Review
- Pan-Cancer Analysis of P3H1 and Experimental Validation in Renal Clear Cell Carcinoma.Applied biochemistry and biotechnology · 2024Article
- Update on Epithelial-Mesenchymal Plasticity in Cancer Progression.Annual review of pathology · 2024Review
- Developing a prognosis and chemotherapy evaluating model for colon adenocarcinoma based on mitotic catastrophe-related genes.Scientific reports · 2024Article
- Development of a prognostic model based on different disulfidptosis related genes typing for kidney renal clear cell carcinoma.Frontiers in pharmacology · 2024Article
- An EMT-Related Gene Signature to Predict the Prognosis of Triple-Negative Breast Cancer.Advances in therapy · 2023Article
- Downregulation of MAL2 inhibits breast cancer progression through regulating β-catenin/c-Myc axis.Cancer cell international · 2023Article
- MCL1 Inhibition Overcomes the Aggressiveness Features of Triple-Negative Breast Cancer MDA-MB-231 Cells.International journal of molecular sciences · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The current high mortality rate of female breast cancer (BC) patients emphasizes the necessity of identifying powerful and reliable prognostic signatures in BC patients. Epithelial-mesenchymal transition (EMT) was reported to be associated with the development of BC. The purpose of this study was to identify prognostic biomarkers that predict overall survival (OS) in female BC patients by integrating data from TCGA database. Method: We first downloaded the dataset in TCGA and identified gene signatures by overlapping candidate genes. Differential analysis was performed to find differential EMT-related genes. Univariate regression analysis was then performed to identify candidate prognostic variables. We then developed a prognostic model by multivariate analysis to predict OS. Calibration curves, receiver operating characteristics (ROC) curves, Result: In this study, we identified and validated a prognostic model integrating age and six genes (CD44, P3H1, SDC1, COL4A1, TGF Conclusion: This study offered a robust predictive model for OS prediction in female BC patients and may provide a more accurate treatment strategy and personalized therapy in the future.
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Registered trials
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