Cargando…
N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma
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 path...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9372539/ https://www.ncbi.nlm.nih.gov/pubmed/35965688 http://dx.doi.org/10.1155/2022/2754836 |
_version_ | 1784767407496101888 |
---|---|
author | Liu, Jinhui Geng, Rui Zhong, Zihang Zhang, Yixin Ni, Senmiao Liu, Wen Du, Mulong Bai, Jianling |
author_facet | Liu, Jinhui Geng, Rui Zhong, Zihang Zhang, Yixin Ni, Senmiao Liu, Wen Du, Mulong Bai, Jianling |
author_sort | Liu, Jinhui |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9372539 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-93725392022-08-13 N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma Liu, Jinhui Geng, Rui Zhong, Zihang Zhang, Yixin Ni, Senmiao Liu, Wen Du, Mulong Bai, Jianling Oxid Med Cell Longev Research Article 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. Hindawi 2022-07-31 /pmc/articles/PMC9372539/ /pubmed/35965688 http://dx.doi.org/10.1155/2022/2754836 Text en Copyright © 2022 Jinhui Liu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Liu, Jinhui Geng, Rui Zhong, Zihang Zhang, Yixin Ni, Senmiao Liu, Wen Du, Mulong Bai, Jianling N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma |
title | N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma |
title_full | N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma |
title_fullStr | N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma |
title_full_unstemmed | N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma |
title_short | N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma |
title_sort | n1-methyladenosine-related lncrnas are potential biomarkers for predicting prognosis and immune response in uterine corpus endometrial carcinoma |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9372539/ https://www.ncbi.nlm.nih.gov/pubmed/35965688 http://dx.doi.org/10.1155/2022/2754836 |
work_keys_str_mv | AT liujinhui n1methyladenosinerelatedlncrnasarepotentialbiomarkersforpredictingprognosisandimmuneresponseinuterinecorpusendometrialcarcinoma AT gengrui n1methyladenosinerelatedlncrnasarepotentialbiomarkersforpredictingprognosisandimmuneresponseinuterinecorpusendometrialcarcinoma AT zhongzihang n1methyladenosinerelatedlncrnasarepotentialbiomarkersforpredictingprognosisandimmuneresponseinuterinecorpusendometrialcarcinoma AT zhangyixin n1methyladenosinerelatedlncrnasarepotentialbiomarkersforpredictingprognosisandimmuneresponseinuterinecorpusendometrialcarcinoma AT nisenmiao n1methyladenosinerelatedlncrnasarepotentialbiomarkersforpredictingprognosisandimmuneresponseinuterinecorpusendometrialcarcinoma AT liuwen n1methyladenosinerelatedlncrnasarepotentialbiomarkersforpredictingprognosisandimmuneresponseinuterinecorpusendometrialcarcinoma AT dumulong n1methyladenosinerelatedlncrnasarepotentialbiomarkersforpredictingprognosisandimmuneresponseinuterinecorpusendometrialcarcinoma AT baijianling n1methyladenosinerelatedlncrnasarepotentialbiomarkersforpredictingprognosisandimmuneresponseinuterinecorpusendometrialcarcinoma |