ArticleFrontiers in oncology2022
A prognostic model and immune regulation analysis of uterine corpus endometrial carcinoma based on cellular senescence.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- COL1A1, ITGB1, THY1, and PDGFRA: key immune-related genes in uterine corpus endometrial carcinoma with prognostic and therapeutic implications.Hereditas · 2025Article
- Establishing and Validating an Innovative Focal Adhesion-Linked Gene Signature for Enhanced Prognostic Assessment in Endometrial Cancer.Reproductive sciences (Thousand Oaks, Calif.) · 2024Article
- Integrated machine learning identifies a cellular senescence-related prognostic model to improve outcomes in uterine corpus endometrial carcinoma.Frontiers in immunology · 2024Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study aimed to explore the clinical significance of cellular senescence in uterine corpus endometrial carcinoma (UCEC). Methods: Cluster analysis was performed on GEO data and TCGA data based on cellular senescence related genes, and then performed subtype analysis on differentially expressed genes between subtypes. The prognostic model was constructed using Lasso regression. Survival analysis, microenvironment analysis, immune analysis, mutation analysis, and drug susceptibility analysis were performed to evaluate the practical relevance. Ultimately, a clinical nomogram was constructed and cellular senescence-related genes expression was investigated by qRT-PCR. Results: We ultimately identified two subtypes. The prognostic model divides patients into high-risk and low-risk groups. There were notable discrepancies in prognosis, tumor microenvironment, immunity, and mutation between the two subtypes and groups. There was a notable connection between drug-sensitive and risk scores. The nomogram has good calibration with AUC values between 0.75-0.8. In addition, cellular senescence-related genes expression was investigated qRT-PCR. Conclusion: Our model and nomogram may effectively forecast patient prognosis and serve as a reference for patient management.
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Registered trials
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