ArticleFrontiers in genetics2020
Identification of EMT-Related Gene Signatures to Predict the Prognosis of Patients With Endometrial Cancer.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 42 citations in OpenAlex.
- Analysis and experimental validation of disulfidptosis related genes solute carrier family 3 member 2 (SLC3A2) in endometrial cancer.Cancer cell international · 2024Article
- Unraveling the Role of Bromodomain and Extra-Terminal Proteins in Human Uterine Leiomyosarcoma.Cells · 2024Article
- EMT-related gene risk model establishment for prognosis and drug treatment efficiency prediction in hepatocellular carcinoma.Scientific reports · 2023Article
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- An EMT-related genes signature as a prognostic biomarker for patients with endometrial cancer.BMC cancer · 2023Article
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- An epithelial-mesenchymal transition-related mRNA signature associated with the prognosis, immune infiltration and therapeutic response of colon adenocarcinoma.Pathology oncology research : POR · 2023Article
- Three RNA-binding protein signature as a novel biomarker to predict endometrial cancer prognosis.American journal of translational research · 2023Article
- Article
- Long non-coding RNA VPS9D1-AS1 enhances proliferation, invasion, and epithelial-mesenchymal transition in endometrial cancer via miR-377-3p/SGK1.The Kaohsiung journal of medical sciences · 2022Article
- Endothelial cell-specific molecule 1 (ESM1) promoted by transcription factor SPI1 acts as an oncogene to modulate the malignant phenotype of endometrial cancer.Open medicine (Warsaw, Poland) · 2022Article
- Epithelial-Mesenchymal Transition-Based Gene Signature and Distinct Molecular Subtypes for Predicting Clinical Outcomes in Breast Cancer.International journal of general medicine · 2022Article
- Identification of the prognostic value of a 2-gene signature of the WNT gene family in UCEC using bioinformatics and real-world data.Cancer cell international · 2021Article
- Bioengineering strategies to control epithelial-to-mesenchymal transition for studies of cardiac development and disease.APL bioengineering · 2021Review
- An EMT-Related Gene Signature for Predicting Response to Adjuvant Chemotherapy in Pancreatic Ductal Adenocarcinoma.Frontiers in cell and developmental biology · 2021Article
- Establishing a Prognostic Signature Based on Epithelial-Mesenchymal Transition-Related Genes for Endometrial Cancer Patients.Frontiers in immunology · 2021Article
- Identification of the Ferroptosis-Associated Gene Signature to Predict the Prognostic Status of Endometrial Carcinoma Patients.Computational and mathematical methods in medicine · 2021Article
- Identification of the EMT-Related Genes Signature for Predicting Occurrence and Progression in Thyroid Cancer.OncoTargets and therapy · 2021Article
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEndometrial cancer (EC) is one of the most common gynecological cancers. Epithelial-mesenchymal transition (EMT) is believed to be significantly associated with the malignant progression of tumors. However, there is no relevant study on the relationship between EMT-related gene (ERG) signatures and the prognosis of EC patients.
methodsWe extracted the mRNA expression profiles of 543 tumor and 23 normal tissues from The Cancer Genome Atlas database. Then, we selected differentially expressed ERGs (DEERGs) among these mRNAs. Next, univariate and multivariate Cox regression analyses were performed to select the ERGs with predictive ability for the prognosis of EC patients. In addition, risk score models were constructed based on the selected genes to predict patients' overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS). Finally, nomograms were constructed to estimate the OS and PFS of EC patients, and pan-cancer analysis was performed to further analyze the functions of a certain gene.
resultsSix OS-, ten PFS-, and five DFS-related ERGs were obtained. By constructing the prognostic risk score model, we found that the OS, PFS, and DFS of the high-risk group were notably poorer. Last, we found that AQP5 appeared in all three gene signatures, and through pan-cancer analysis, it was also found to play an important role in immunity in lower grade glioma (LGG), which may contribute to the poor prognosis of LGG patients.
conclusionsWe constructed ERG signatures to predict the prognosis of EC patients using bioinformatics methods. Our findings provide a thorough understanding of the effect of EMT in patients with EC and provide new targets and ideas for individualized treatment, which has important clinical significance.
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