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pmid:34956315

Genomics and Prognosis Analysis of N6-Methyladenosine Regulators in Lung Adenocarcinoma.

Yanpin Ma · Huping Zhang

Frontiers in genetics · 2021 doi:10.3389/fgene.2021.746666

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Experiment

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Data

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Genomics and Prognosis Analysis of N6-Methyladenosine Regulators in Lung Adenocarcinoma.
doi
10.3389/fgene.2021.746666
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34956315
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[0]
Yanpin Ma
[1]
Huping Zhang
journal
Frontiers in genetics
year
2021
abstract
Objective: N6-methyladenosine (m6A) modification is involved in modulating various biological processes in human cancers. But the implication of m6A modification in lung adenocarcinoma (LUAD) is still unclear. Hence, this study conducted a comprehensive analysis of the expression and clinical implication of m6A regulators in LUAD. Methods: Consensus clustering analysis of 502 LUAD samples in the TCGA dataset was presented based on the expression profiles of 20 m6A regulators using ConsensusClusterPlus package. Overall survival (OS), activation of signaling pathways and tumor immunity (immune/stromal score, tumor purity, expression of HLA and immune checkpoints, and immune cell infiltration) were compared between m6A modification patterns. The m6A-related genes between patterns were identified and prognostic m6A-related genes were imported into LASSO-cox regression analysis. The m6A risk score was developed and its prognostic implication was evaluated and externally verified in the GSE30219 and GSE72094 dataset. Furthermore, a nomogram that contained independent prognostic indicators was established, followed by external verification. Results: Two m6A modification patterns were clustered across LUAD based on the expression similarity of the m6A regulators via consensus clustering analysis, with distinct OS, activation of signaling pathways and tumor immunity. Totally, 213 m6A-related genes that were identified by comparing two patterns were significantly related to LUAD prognosis. By LASSO method, we constructed the m6A risk score that was a reliable and independent prognostic factor for LUAD. Patients with low m6A risk score displayed a prominent survival advantage. After incorporating independent clinical features, we developed the prognostic nomogram that exhibited high predictive accuracy and the best clinical net benefit for OS. Conclusion: Collectively, our study may provide a clinically useful tool for precise prognostic management and optimization of immunotherapeutic strategies for LUAD patients.
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Candidate prognostic m6A-related DEGs were further screened with LASSO-Cox regression analysis (Figures 5A,B).
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sections[17] "Development of an m6A Risk Score for Lung Adenocarcinoma" paragraph 2
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Candidate prognostic m6A-related DEGs were further screened with LASSO-Cox regression analysis (Figures 5A,B).
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sections[23] "Data Availability Statement" paragraph 2
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The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
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The AUC values under one, three and 5-year OS were separately 0.663, 0.677 and 0.694 (Figure 6A).
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sections[18] "External Verification of the m6A Risk Score in Lung Adenocarcinoma Prognosis" paragraph 2
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The AUC values under one, three and 5-year OS were separately 0.663, 0.677 and 0.694 (Figure 6A).
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The AUC values under one, three and 5-year OS were separately 0.663, 0.677 and 0.694 (Figure 6A).
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sample_count
442
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null
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null
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15048
taxon
Homo sapiens
title
KRAS mutation-associated gene expression, p53 and STK11 mutations, proliferation and immune surveillance in lung adenocarcinoma
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2026-11-01T15:39:55Z
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[2]
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[3]
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partial
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method-1
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[0]
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time_to_event_with_censoring
evidence object · 3 fields
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Candidate prognostic m6A-related DEGs were further screened with LASSO-Cox regression analysis (Figures 5A,B).
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method-2
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group_comparison
specific
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Group comparison
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group_comparison_wilcoxon
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false
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two_or_more_groups_continuous
evidence object · 3 fields
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method-3
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evidence object · 3 fields
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net benefit
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capability object · 3 fields
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complete
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capability:computational_analysis
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[8]
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candidate
Automated Assays Laravel application and simulated adapters
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nothing:replicable_now
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R1
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cox_ph
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basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards.
capability object · 4 fields
tier
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capability_id
capability:computational_analysis
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owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
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[0]
GSE30219
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GSE72094
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[0]
GSE30219
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GSE72094
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[0]
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
basis
The paper names GSE30219, GSE72094 in Gene Expression Omnibus and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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cox_ph
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[1]
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[0]
data:geo:GSE30219
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partial
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extraction_review
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MiniMax-M3.1-Flash
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minimax
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minimax
read_at
2026-11-01T17:13:15Z
independence
single_reader
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verbatim
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verbatim
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5
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11731
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128
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extraction
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minimax
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not_run
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paper
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pmid:34956315
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source:pmid:34956315
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data:geo:GSE30219
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dataset
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GEO GSE30219
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classification
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pmid:34956315
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source:pmid:34956315
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PMID 34956315 full text
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data:geo:GSE30219
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dataset
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GEO GSE30219
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agent:corpus-assay-engine
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extraction
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agent:minimax-reader
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activity-resolve-GSE30219
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accession_resolution
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agent:corpus-assay-engine
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sha256:37669c7f22cdb110f520aee4053ff287fb1eb9d6b5d625e68d144513981d689a
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[2]
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[3]
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[4]
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[5]
method.reader_differs_from_extractor
[6]
review.human_critique
[7]
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[8]
review.machine_critique
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f2132e96ae6c7a4e
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cox_ph
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supported
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dsl_catalogue
f2132e96ae6c7a4e
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Candidate prognostic m6A-related DEGs were further screened with LASSO-Cox regression analysis (Figures 5A,B).
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34956315", "kind": "science-record", "revision": 4, "content_hash": "sha256:34aea85673a98bcddcf5d0dc69928f7ff1b8e31ea9c662e54e064a8eabfb0ac6", "created_at": "2026-11-01T17:36:40Z", "updated_at": "2026-11-01T22:05:27Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Genomics and Prognosis Analysis of N6-Methyladenosine Regulators in Lung Adenocarcinoma.", "doi": "10.3389/fgene.2021.746666", "pmid": "34956315", "authors": ["Yanpin Ma", "Huping Zhang"], "journal": "Frontiers in genetics", "year": 2021, "abstract": "Objective: N6-methyladenosine (m6A) modification is involved in modulating various biological processes in human cancers. But the implication of m6A modification in lung adenocarcinoma (LUAD) is still unclear. Hence, this study conducted a comprehensive analysis of the expression and clinical implication of m6A regulators in LUAD. Methods: Consensus clustering analysis of 502 LUAD samples in the TCGA dataset was presented based on the expression profiles of 20 m6A regulators using ConsensusClusterPlus package. Overall survival (OS), activation of signaling pathways and tumor immunity (immune/stromal score, tumor purity, expression of HLA and immune checkpoints, and immune cell infiltration) were compared between m6A modification patterns. The m6A-related genes between patterns were identified and prognostic m6A-related genes were imported into LASSO-cox regression analysis. The m6A risk score was developed and its prognostic implication was evaluated and externally verified in the GSE30219 and GSE72094 dataset. Furthermore, a nomogram that contained independent prognostic indicators was established, followed by external verification. Results: Two m6A modification patterns were clustered across LUAD based on the expression similarity of the m6A regulators via consensus clustering analysis, with distinct OS, activation of signaling pathways and tumor immunity. Totally, 213 m6A-related genes that were identified by comparing two patterns were significantly related to LUAD prognosis. By LASSO method, we constructed the m6A risk score that was a reliable and independent prognostic factor for LUAD. Patients with low m6A risk score displayed a prominent survival advantage. After incorporating independent clinical features, we developed the prognostic nomogram that exhibited high predictive accuracy and the best clinical net benefit for OS. 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