中文版 | English
Title

Bioinformatics analysis based on DNA methylation data identified in lung adenocarcinoma subgroups with different immune characteristics and clinical outcomes

Author
Corresponding AuthorChen, Wenbiao
Publication Years
2023-04-01
DOI
Source Title
ISSN
2072-1439
EISSN
2077-6624
Volume15Issue:4
Abstract
["Background: DNA methylation can be used to predict clinical outcomes and improve the classification of tumors. The present study aimed to develop a new lung adenocarcinoma (LUAD) classification system according to the immune cell gene-related methylation sites and to reveal the survival outcomes, clinical characteristics, immune cell infiltration, stem cell characteristics, and genomic variations of each molecular subgroup.","Methods: The DNA methylation sites of LUAD samples collected from The Cancer Genome Atlas (TCGA) database were analyzed, and the prognosis-related differential methylation sites (DMS) were screened. Consistent clustering of the samples was conducted using ConsensusClusterPlus, and the classification results were verified by principal component analysis (PCA). The survival and clinical results, immune cell infiltration, stemness, DNA mutation, and copy number variation (CNV) of each molecular subgroup were analyzed.","Results: A total of 40 DMS were obtained by difference and univariate COX analyses, and the TCGA LUAD samples were divided into three subgroups: cluster 1 (C1), cluster 2 (C2), and cluster 3 (C3). Among these subgroups, the overall survival (OS) of C3 was significantly higher than that of C1 and C2. Compared with C1 and C3, C2 had the lowest innate immune cell and adaptive immune cell infiltration scores; the lowest stromal score, immune score, and iconic immune checkpoint expression; and the highest expression of index (mDNAsi), and tumor mutational burden (TMB).","Conclusions: In this study, we proposed a LUAD typing system based on DMS, which was closely related to the survival, clinical features, immune characteristics, and genomic variations of LUAD, and may contribute to the development of personalized therapy for new specific subtypes."]
Keywords
URL[Source Record]
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Language
English
SUSTech Authorship
Corresponding
Funding Project
Scientific Research Projects of Medical and Health Institutions of Longhua District, Shenzhen["2022011","2022105","2020096"] ; Basic and Applied Basic Research Fund of Guangdong Province[2021A1515110967]
WOS Research Area
Respiratory System
WOS Subject
Respiratory System
WOS Accession No
WOS:001044673700057
Publisher
Data Source
Web of Science
Citation statistics
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/583013
DepartmentShenzhen People's Hospital
Affiliation
1.Southern Med Univ, Peoples Hosp Longhua, Dept Resp Med, Shenzhen, Peoples R China
2.Jinan Univ, Guangdong Prov Engn Res Ctr Autoimmune Dis Precis, Southern Univ Sci & Technol,Clin Med Coll 2, Clin Med Res Ctr,Affiliated Hosp 1,Shenzhen Peopl, Shenzhen, Peoples R China
Corresponding Author AffilicationShenzhen People's Hospital
Recommended Citation
GB/T 7714
Yu, Ruilin,Huang, Xiaoming,Lin, Junqi,et al. Bioinformatics analysis based on DNA methylation data identified in lung adenocarcinoma subgroups with different immune characteristics and clinical outcomes[J]. JOURNAL OF THORACIC DISEASE,2023,15(4).
APA
Yu, Ruilin,Huang, Xiaoming,Lin, Junqi,Lin, Shaoming,Shen, Guanle,&Chen, Wenbiao.(2023).Bioinformatics analysis based on DNA methylation data identified in lung adenocarcinoma subgroups with different immune characteristics and clinical outcomes.JOURNAL OF THORACIC DISEASE,15(4).
MLA
Yu, Ruilin,et al."Bioinformatics analysis based on DNA methylation data identified in lung adenocarcinoma subgroups with different immune characteristics and clinical outcomes".JOURNAL OF THORACIC DISEASE 15.4(2023).
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