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The Cancer Genome Atlas (TCGA) based m6A methylation-related genes predict prognosis in rectosigmoid cancer

N6-methyladenosine (m6A) methylation plays an important role in the occurrence and development of tumors. This study aimed to explore the effects of m6A methylation regulatory genes on rectosigmoid cancer (RSC). RNA-seq data and related clinical information in The Cancer Genome Atlas database were a...

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Autores principales: Zhou, Wei, Lin, Junchao, Li, Zeng, Li, Min, Fan, Daiming, Hong, Liu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9794336/
https://www.ncbi.nlm.nih.gov/pubmed/36595765
http://dx.doi.org/10.1097/MD.0000000000032328
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author Zhou, Wei
Lin, Junchao
Li, Zeng
Li, Min
Fan, Daiming
Hong, Liu
author_facet Zhou, Wei
Lin, Junchao
Li, Zeng
Li, Min
Fan, Daiming
Hong, Liu
author_sort Zhou, Wei
collection PubMed
description N6-methyladenosine (m6A) methylation plays an important role in the occurrence and development of tumors. This study aimed to explore the effects of m6A methylation regulatory genes on rectosigmoid cancer (RSC). RNA-seq data and related clinical information in The Cancer Genome Atlas database were analyzed. The Wilcoxon test was used to analyze the different expression levels of m6A methylation regulatory genes between the tumor and normal samples. Least absolute shrinkage and selection operator Cox regression analysis was used to construct a risk prognosis model between the m6A methylation regulatory genes and RSC. The median risk score was used to classify RSC patients into high and low-risk groups. Kaplan–Meier survival analysis and receiver operating characteristic curves were used to evaluate the sensitivity and specificity of the prediction model. The expression of m6A methylation regulation genes was different between the tumor and normal samples, 6 genes were overexpressed in tumor and 2 genes were down-regulated. Four m6A methylation regulatory genes, YTHDF3, KIAA1429, ALKBH5 and METTL3, were screened by least absolute shrinkage and selection operator Cox regression analysis. The overall survival of high-risk group was significantly lower than that of low-risk group (P = 4.681 × 10(−4)). The area under the curve value in the receiver operating characteristic curve was 0.935, indicating that the prediction model was effective. Univariate and multivariate Cox regression were used to test the effectiveness of the model. m6A methylation regulators YTHDF3, KIAA1429, ALKBH5, and METTL3 can be used to construct predictive models to predict overall survival in different clinical subgroups of RSC patients.
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spelling pubmed-97943362022-12-28 The Cancer Genome Atlas (TCGA) based m6A methylation-related genes predict prognosis in rectosigmoid cancer Zhou, Wei Lin, Junchao Li, Zeng Li, Min Fan, Daiming Hong, Liu Medicine (Baltimore) 4500 N6-methyladenosine (m6A) methylation plays an important role in the occurrence and development of tumors. This study aimed to explore the effects of m6A methylation regulatory genes on rectosigmoid cancer (RSC). RNA-seq data and related clinical information in The Cancer Genome Atlas database were analyzed. The Wilcoxon test was used to analyze the different expression levels of m6A methylation regulatory genes between the tumor and normal samples. Least absolute shrinkage and selection operator Cox regression analysis was used to construct a risk prognosis model between the m6A methylation regulatory genes and RSC. The median risk score was used to classify RSC patients into high and low-risk groups. Kaplan–Meier survival analysis and receiver operating characteristic curves were used to evaluate the sensitivity and specificity of the prediction model. The expression of m6A methylation regulation genes was different between the tumor and normal samples, 6 genes were overexpressed in tumor and 2 genes were down-regulated. Four m6A methylation regulatory genes, YTHDF3, KIAA1429, ALKBH5 and METTL3, were screened by least absolute shrinkage and selection operator Cox regression analysis. The overall survival of high-risk group was significantly lower than that of low-risk group (P = 4.681 × 10(−4)). The area under the curve value in the receiver operating characteristic curve was 0.935, indicating that the prediction model was effective. Univariate and multivariate Cox regression were used to test the effectiveness of the model. m6A methylation regulators YTHDF3, KIAA1429, ALKBH5, and METTL3 can be used to construct predictive models to predict overall survival in different clinical subgroups of RSC patients. Lippincott Williams & Wilkins 2022-12-23 /pmc/articles/PMC9794336/ /pubmed/36595765 http://dx.doi.org/10.1097/MD.0000000000032328 Text en Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.
spellingShingle 4500
Zhou, Wei
Lin, Junchao
Li, Zeng
Li, Min
Fan, Daiming
Hong, Liu
The Cancer Genome Atlas (TCGA) based m6A methylation-related genes predict prognosis in rectosigmoid cancer
title The Cancer Genome Atlas (TCGA) based m6A methylation-related genes predict prognosis in rectosigmoid cancer
title_full The Cancer Genome Atlas (TCGA) based m6A methylation-related genes predict prognosis in rectosigmoid cancer
title_fullStr The Cancer Genome Atlas (TCGA) based m6A methylation-related genes predict prognosis in rectosigmoid cancer
title_full_unstemmed The Cancer Genome Atlas (TCGA) based m6A methylation-related genes predict prognosis in rectosigmoid cancer
title_short The Cancer Genome Atlas (TCGA) based m6A methylation-related genes predict prognosis in rectosigmoid cancer
title_sort cancer genome atlas (tcga) based m6a methylation-related genes predict prognosis in rectosigmoid cancer
topic 4500
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9794336/
https://www.ncbi.nlm.nih.gov/pubmed/36595765
http://dx.doi.org/10.1097/MD.0000000000032328
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