ArticleOxidative medicine and cellular longevity2022
N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma.
Article in Oxidative medicine and cellular longevity, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Unravelling Multilayered RNA Modification Networks in Female Reproduction and Obstetric/Gynaecologic Disorders.Biomolecules · 2026Review
- Recent advances in characterizing the immune microenvironment and biomarkers of endometrial carcinoma.Frontiers in immunology · 2026Review
- The Analysis of ceRNA Networks and Tumor Microenvironment in Endometrial Cancer.Journal of Cancer · 2024Article
- RNA NCell communication and signaling : CCS · 2023Review
- Integrated single-cell and transcriptome sequencing analyses develops a metastasis-based risk score system for prognosis and immunotherapy response in uveal melanoma.Frontiers in pharmacology · 2023Article
- Construction of a ferroptosis scoring system and identification of LINC01572 as a novel ferroptosis suppressor in lung adenocarcinoma.Frontiers in pharmacology · 2022Article
- A novel melanoma prognostic model based on the ferroptosis-related long non-coding RNA.Frontiers in oncology · 2022Article
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8 authors at 2 institutions in 1 country.
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Abstract
Uterine corpus endometrial carcinoma (UCEC) is a malignant disease that, at present, has no well-characterised prognostic biomarker. In this study, two clusters were identified based on 28 N1-methyladenosine- (m1A-) related long noncoding RNAs (lncRNAs), of which cluster 1 was related to immune pathways according to the results of an enrichment analysis. We further observed better prognosis in patients with higher levels of immune cell infiltration, tumor mutation burden, microsatellite instability, and immune checkpoint gene expression. In addition, through Cox regression analysis and least absolute shrinkage and selection operator regression analysis, 10 m1A-related lncRNAs (mRLs) were employed to build a prognosis model. We found that people in higher risk categories had a poorer survival probability than those in lower risk. Low-risk samples were enriched with immune-related pathways, while the high-risk group was similar to the definition of the "immune desert" phenotype, which was associated with decreased immune infiltration, T cell failure, and decreased tumor mutation burden, while also being insensitive to immunotherapy and chemotherapy. This mRL-based model has the ability to accurately predict the prognosis of UCEC patients, and the mRLs could become promising therapeutic targets in enhancing the response of immunotherapy.
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