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Necroptosis-Related miRNA Biomarkers for Predicting Overall Survival Outcomes for Endometrial Cancer

Endometrial cancer (EC) is the gynecological tumor with the highest incidence. In recent years, it has been proved that necroptosis is a method of cell death related to EC. However, the expression of necroptosis-related miRNA in EC and its correlation with prognosis still ill-defined. Use the Cancer...

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Autores principales: Song, Hualin, Li, Tianjie, Sheng, Jindong, Li, Dan, Liu, Xiangyu, Xiao, Huiting, Yu, Hu, Liu, Wenxin, Wang, Ke, Chen, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9198705/
https://www.ncbi.nlm.nih.gov/pubmed/35719379
http://dx.doi.org/10.3389/fgene.2022.828456
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author Song, Hualin
Li, Tianjie
Sheng, Jindong
Li, Dan
Liu, Xiangyu
Xiao, Huiting
Yu, Hu
Liu, Wenxin
Wang, Ke
Chen, Ying
author_facet Song, Hualin
Li, Tianjie
Sheng, Jindong
Li, Dan
Liu, Xiangyu
Xiao, Huiting
Yu, Hu
Liu, Wenxin
Wang, Ke
Chen, Ying
author_sort Song, Hualin
collection PubMed
description Endometrial cancer (EC) is the gynecological tumor with the highest incidence. In recent years, it has been proved that necroptosis is a method of cell death related to EC. However, the expression of necroptosis-related miRNA in EC and its correlation with prognosis still ill-defined. Use the Cancer Genome Atlas (TCGA) cohort to obtain prognostic data and related clinical data for ECs and normal endometrium tissues. In this study, we identified three necroptotic regulatory miRNAs that are necroptosis-related and survival-related miRNAs (DENSMs) between normal endometrium tissues and EC from 13 necroptosis-related miRNAs. The three DENSMs signature was built to develop prognostic model and classified all EC patients into a high or low risk group. EC patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (p = 0.0242), and the risk score was found to be an independent prognosis factor for predicting the OS of EC patients (p = 0.0254) in multivariate Cox regression. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed dephosphorylation, microtubule, protein serine/threonine kinase activity, PI3K-Akt signaling pathway and MAPK signaling pathway are closely related to it. In conclusion, the risk prediction model based on necroptosis-related miRNAs can effectively predict the prognosis of EC patients.
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spelling pubmed-91987052022-06-16 Necroptosis-Related miRNA Biomarkers for Predicting Overall Survival Outcomes for Endometrial Cancer Song, Hualin Li, Tianjie Sheng, Jindong Li, Dan Liu, Xiangyu Xiao, Huiting Yu, Hu Liu, Wenxin Wang, Ke Chen, Ying Front Genet Genetics Endometrial cancer (EC) is the gynecological tumor with the highest incidence. In recent years, it has been proved that necroptosis is a method of cell death related to EC. However, the expression of necroptosis-related miRNA in EC and its correlation with prognosis still ill-defined. Use the Cancer Genome Atlas (TCGA) cohort to obtain prognostic data and related clinical data for ECs and normal endometrium tissues. In this study, we identified three necroptotic regulatory miRNAs that are necroptosis-related and survival-related miRNAs (DENSMs) between normal endometrium tissues and EC from 13 necroptosis-related miRNAs. The three DENSMs signature was built to develop prognostic model and classified all EC patients into a high or low risk group. EC patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (p = 0.0242), and the risk score was found to be an independent prognosis factor for predicting the OS of EC patients (p = 0.0254) in multivariate Cox regression. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed dephosphorylation, microtubule, protein serine/threonine kinase activity, PI3K-Akt signaling pathway and MAPK signaling pathway are closely related to it. In conclusion, the risk prediction model based on necroptosis-related miRNAs can effectively predict the prognosis of EC patients. Frontiers Media S.A. 2022-05-27 /pmc/articles/PMC9198705/ /pubmed/35719379 http://dx.doi.org/10.3389/fgene.2022.828456 Text en Copyright © 2022 Song, Li, Sheng, Li, Liu, Xiao, Yu, Liu, Wang and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Song, Hualin
Li, Tianjie
Sheng, Jindong
Li, Dan
Liu, Xiangyu
Xiao, Huiting
Yu, Hu
Liu, Wenxin
Wang, Ke
Chen, Ying
Necroptosis-Related miRNA Biomarkers for Predicting Overall Survival Outcomes for Endometrial Cancer
title Necroptosis-Related miRNA Biomarkers for Predicting Overall Survival Outcomes for Endometrial Cancer
title_full Necroptosis-Related miRNA Biomarkers for Predicting Overall Survival Outcomes for Endometrial Cancer
title_fullStr Necroptosis-Related miRNA Biomarkers for Predicting Overall Survival Outcomes for Endometrial Cancer
title_full_unstemmed Necroptosis-Related miRNA Biomarkers for Predicting Overall Survival Outcomes for Endometrial Cancer
title_short Necroptosis-Related miRNA Biomarkers for Predicting Overall Survival Outcomes for Endometrial Cancer
title_sort necroptosis-related mirna biomarkers for predicting overall survival outcomes for endometrial cancer
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9198705/
https://www.ncbi.nlm.nih.gov/pubmed/35719379
http://dx.doi.org/10.3389/fgene.2022.828456
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