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METTL5相关的预后特征构建及其在肺腺癌中的免疫意义综合分析

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

作者信息

Sun Sijin, Fei Kailun, Zhang Guochao, Wang Juhong, Yang Yannan, Guo Wei, Yang Zhenlin, Wang Jie, Xue Qi, Gao Yibo, He Jie

机构信息

Department 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, China.

State 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, China.

出版信息

Front Genet. 2021 Feb 19;11:617174. doi: 10.3389/fgene.2020.617174. eCollection 2020.

DOI:10.3389/fgene.2020.617174
PMID:33679869
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7933593/
Abstract

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 was performed in TCGA dataset. To build a -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 in LUAD was significantly higher than that in normal lung tissue. And high expression of indicated poor prognosis in all different stages ( < 0.001, HR = 1.81). Five genes (, and ) were used to construct MAPS and MAPS was significantly correlated with poor prognosis ( < 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 in LUAD and MAPS can serve as a promising biomarker for LUAD.

摘要

对于肺腺癌(LUAD),不同阶段的患者具有很强的异质性,其总体预后差异很大。因此,迫切需要探索新的生物标志物以更好地阐明LUAD的特征。从TCGA收集了LUAD患者的多组学信息。从基因表达综合数据库(GEO)获得了三个独立的LUAD队列。在TCGA数据集中进行了多组学相关分析。为了构建一个与-相关的预后评分(MAPS)。首先应用空间和随机森林方法进行特征选择。然后,在TCGA队列中实施LASSO以开发模型。在三个独立的GEO数据集中验证了MAPS的预后价值。最后,使用基因集富集分析(GSEA)进行功能注释,并通过ImmuCellAI算法估计浸润免疫细胞的丰度。总共纳入了901例LUAD患者。LUAD中 的表达明显高于正常肺组织。并且 在所有不同阶段的高表达均表明预后不良(<0.001,HR = 1.81)。使用五个基因( 、 和 )构建MAPS,且MAPS与不良预后显著相关(<0.001,HR = 2.15)。此外,多变量Cox回归分析表明MAPS是一个独立的预后因素。功能富集揭示了MAPS与几种免疫成分和途径之间的显著关联。本研究提供了关于 在LUAD中的潜在意义的见解,并且MAPS可以作为LUAD的一个有前景的生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/7dd5f271bc7c/fgene-11-617174-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/b8426b392975/fgene-11-617174-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/7b5dc68be509/fgene-11-617174-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/c458e25167a8/fgene-11-617174-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/ea82012695e0/fgene-11-617174-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/189b41455759/fgene-11-617174-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/53d43488a5d9/fgene-11-617174-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/5443de6ab13d/fgene-11-617174-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/93e159a26db8/fgene-11-617174-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/7dd5f271bc7c/fgene-11-617174-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/b8426b392975/fgene-11-617174-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/7b5dc68be509/fgene-11-617174-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/c458e25167a8/fgene-11-617174-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/ea82012695e0/fgene-11-617174-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/189b41455759/fgene-11-617174-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/53d43488a5d9/fgene-11-617174-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/5443de6ab13d/fgene-11-617174-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/93e159a26db8/fgene-11-617174-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5ea/7933593/7dd5f271bc7c/fgene-11-617174-g009.jpg

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