Construction and Comprehensive Analyses of a METTL5-Associated Prognostic Signature With Immune Implication in Lung Adenocarcinomas

For lung adenocarcinoma (LUAD), patients of different stages have strong heterogeneity, and their overall prognosis varies greatly. Thus, exploration of novel biomarkers to better clarify the characteristics of LUAD is urgent. Multi-omics information of LUAD patients were collected form TCGA. Three...

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Main Authors: Sijin Sun, Kailun Fei, Guochao Zhang, Juhong Wang, Yannan Yang, Wei Guo, Zhenlin Yang, Jie Wang, Qi Xue, Yibo Gao, Jie He
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-02-01
Series:Frontiers in Genetics
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2020.617174/full
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record_format Article
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language English
format Article
sources DOAJ
author Sijin Sun
Kailun Fei
Guochao Zhang
Juhong Wang
Yannan Yang
Wei Guo
Zhenlin Yang
Jie Wang
Qi Xue
Qi Xue
Yibo Gao
Yibo Gao
Jie He
Jie He
spellingShingle Sijin Sun
Kailun Fei
Guochao Zhang
Juhong Wang
Yannan Yang
Wei Guo
Zhenlin Yang
Jie Wang
Qi Xue
Qi Xue
Yibo Gao
Yibo Gao
Jie He
Jie He
Construction and Comprehensive Analyses of a METTL5-Associated Prognostic Signature With Immune Implication in Lung Adenocarcinomas
Frontiers in Genetics
rRNA methylation
prognosis
METTL5
machine learning
lung adenocarcinoma
author_facet Sijin Sun
Kailun Fei
Guochao Zhang
Juhong Wang
Yannan Yang
Wei Guo
Zhenlin Yang
Jie Wang
Qi Xue
Qi Xue
Yibo Gao
Yibo Gao
Jie He
Jie He
author_sort Sijin Sun
title Construction and Comprehensive Analyses of a METTL5-Associated Prognostic Signature With Immune Implication in Lung Adenocarcinomas
title_short Construction and Comprehensive Analyses of a METTL5-Associated Prognostic Signature With Immune Implication in Lung Adenocarcinomas
title_full Construction and Comprehensive Analyses of a METTL5-Associated Prognostic Signature With Immune Implication in Lung Adenocarcinomas
title_fullStr Construction and Comprehensive Analyses of a METTL5-Associated Prognostic Signature With Immune Implication in Lung Adenocarcinomas
title_full_unstemmed Construction and Comprehensive Analyses of a METTL5-Associated Prognostic Signature With Immune Implication in Lung Adenocarcinomas
title_sort construction and comprehensive analyses of a mettl5-associated prognostic signature with immune implication in lung adenocarcinomas
publisher Frontiers Media S.A.
series Frontiers in Genetics
issn 1664-8021
publishDate 2021-02-01
description For lung adenocarcinoma (LUAD), patients of different stages have strong heterogeneity, and their overall prognosis varies greatly. Thus, exploration of novel biomarkers to better clarify the characteristics of LUAD is urgent. Multi-omics information of LUAD patients were collected form TCGA. Three independent LUAD cohorts were obtained from gene expression omnibus (GEO). A multi-omics correlation analysis of METTL5 was performed in TCGA dataset. To build a METTL5-associated prognostic score (MAPS). Spathial and random forest methods were first applied for feature selection. Then, LASSO was implemented to develop the model in TCGA cohort. The prognostic value of MAPS was validated in three independent GEO datasets. Finally, functional annotation was conducted using gene set enrichment analysis (GSEA) and the abundances of infiltrated immune cells were estimated by ImmuCellAI algorithm. A total of 901 LUAD patients were included. The expression of METTL5 in LUAD was significantly higher than that in normal lung tissue. And high expression of METTL5 indicated poor prognosis in all different stages (P < 0.001, HR = 1.81). Five genes (RAC1, C11of24, METTL5, RCCD1, and SLC7A5) were used to construct MAPS and MAPS was significantly correlated with poor prognosis (P < 0.001, HR = 2.15). Furthermore, multivariate Cox regression analysis suggested MAPS as an independent prognostic factor. Functional enrichment revealed significant association between MAPS and several immune components and pathways. This study provides insights into the potential significance of METTL5 in LUAD and MAPS can serve as a promising biomarker for LUAD.
topic rRNA methylation
prognosis
METTL5
machine learning
lung adenocarcinoma
url https://www.frontiersin.org/articles/10.3389/fgene.2020.617174/full
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spelling doaj-dc0860b16e8b4e2499df8de6fc3b730f2021-02-19T07:10:16ZengFrontiers Media S.A.Frontiers in Genetics1664-80212021-02-011110.3389/fgene.2020.617174617174Construction and Comprehensive Analyses of a METTL5-Associated Prognostic Signature With Immune Implication in Lung AdenocarcinomasSijin Sun0Kailun Fei1Guochao Zhang2Juhong Wang3Yannan Yang4Wei Guo5Zhenlin Yang6Jie Wang7Qi Xue8Qi Xue9Yibo Gao10Yibo Gao11Jie He12Jie He13Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaState Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaState Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFor lung adenocarcinoma (LUAD), patients of different stages have strong heterogeneity, and their overall prognosis varies greatly. Thus, exploration of novel biomarkers to better clarify the characteristics of LUAD is urgent. Multi-omics information of LUAD patients were collected form TCGA. Three independent LUAD cohorts were obtained from gene expression omnibus (GEO). A multi-omics correlation analysis of METTL5 was performed in TCGA dataset. To build a METTL5-associated prognostic score (MAPS). Spathial and random forest methods were first applied for feature selection. Then, LASSO was implemented to develop the model in TCGA cohort. The prognostic value of MAPS was validated in three independent GEO datasets. Finally, functional annotation was conducted using gene set enrichment analysis (GSEA) and the abundances of infiltrated immune cells were estimated by ImmuCellAI algorithm. A total of 901 LUAD patients were included. The expression of METTL5 in LUAD was significantly higher than that in normal lung tissue. And high expression of METTL5 indicated poor prognosis in all different stages (P < 0.001, HR = 1.81). Five genes (RAC1, C11of24, METTL5, RCCD1, and SLC7A5) were used to construct MAPS and MAPS was significantly correlated with poor prognosis (P < 0.001, HR = 2.15). Furthermore, multivariate Cox regression analysis suggested MAPS as an independent prognostic factor. Functional enrichment revealed significant association between MAPS and several immune components and pathways. This study provides insights into the potential significance of METTL5 in LUAD and MAPS can serve as a promising biomarker for LUAD.https://www.frontiersin.org/articles/10.3389/fgene.2020.617174/fullrRNA methylationprognosisMETTL5machine learninglung adenocarcinoma