Observational studyMedicine2025
A novel ferroptosis-related microRNAs signature for predicting prognosis in endometrial cancer: An observational study.
Observational study in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- MiR-124 alleviates cerebral ischemia-reperfusion injury by targeting SLC1A5 to inhibit neuronal ferroptosis.Iranian journal of basic medical sciences · 2026Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ferroptosis plays an important role in various cancer processes and is regulated by microRNAs. This study aimed to establish a prognostic model based on ferroptosis-related microRNAs (FermiRNAs) to predict the prognosis of endometrial cancer (EC). Tumor transcriptomes and corresponding clinical data of 544 EC patients were downloaded from the cancer genome atlas database, and the ferroptosis database (FerrDb) was used to identify ferroptosis-related genes (mRNAs). FermiRNAs in EC were selected based on their correlation with ferroptosis-related genes. Univariate and multivariate Cox regression analyses were conducted to construct a prognostic model based on the miRNA signature. EC patients were grouped into high- and low-risk categories based on the risk score of the prognostic model. Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the prognostic value of risk scores. A predictive nomogram was then established. Finally, we compared the proportion of infiltrating immune cells and the expression of potential immune checkpoints between the 2 groups to understand the tumor immune microenvironment associated with signature FermiRNAs. A prognostic model based on the 2 FermiRNAs (miR-4635 and miR-3131) was developed. Kaplan-Meier survival analysis indicated that patients with high-risk scores had worse overall survival (P < .001). ROC curves showed that the area under curve values of the prognostic model were 0.621, 0.712, and 0.696 for 1, 3, and 5 years, respectively, indicating good predictive ability. ROC curves also indicated that the prognostic model had a better capability to predict the prognosis of patients with EC than the other clinical factors. A predictive nomogram suggested that the risk model could offer independent prognostic evaluation with high accuracy. The tumor immune microenvironment, including infiltrating immune cells and immune checkpoints, showed several differences between patients with high- and low-risk scores. In an external validation cohort (213 EC patients from the clinical proteomic tumor analysis consortium dataset), 2 FermiRNAs were confirmed to be associated with EC prognosis in the same manner. A novel ferroptosis-related miRNA prognostic model is useful for predicting the prognosis of patients with EC.
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