{"title":"Development of a Prognostic m6A-Related lncRNA Signature and Functional Validation of FAM83A-AS1 in Lung Adenocarcinoma.","authors":"Guojun Zhang, Cheng Liu, Yukun Wang","doi":"10.2147/OTT.S538953","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>This work aimed to identify m6A-related long non-coding RNAs (lncRNAs) associated with lung adenocarcinoma (LUAD) and evaluate their prognostic value and to examine the oncogenic actions of FAM83A-AS1 in LUAD.</p><p><strong>Methods: </strong>The m6A-related lncRNAs in LUAD were identified by correlating lncRNA expression profiles with known m6A regulators using TCGA RNA-seq data. Prognostic lncRNAs were selected through univariate and multivariate Cox regression analyses and integrated into a risk model termed m6ARLSig. The model's predictive performance was assessed using Kaplan-Meier survival analysis, ROC curves, and principal component analysis. Immune infiltration and therapeutic responses were evaluated using CIBERSORT and drug sensitivity prediction. In vitro assays were conducted in A549 and A549/DDP cell lines to assess the oncogenic and drug resistance roles of FAM83A-AS1.</p><p><strong>Results: </strong>We screened a set of m6A-related genes and identified a subset of m6A related-lncRNAs from TCGA through correlation analysis. Eight m6A-related lncRNAs were significantly associated with patient outcomes. AL606489.1 and COLCA1 functioned as independent adverse prognostic biomarkers, whereas six long non-coding RNAs served as independent favorable predictors of overall survival (OS). Eight lncRNAs were employed to develop a prognostic m6A-associated lncRNA signature (m6ARLSig). Based on personalized m6ARLSig levels, we computed a risk score for each individual and stratified the cohort into low-risk and high-risk categories. Survival analysis revealed a marked divergence in overall survival between the low- and high-risk cohorts, thereby substantiating the m6ARLSig's prognostic utility. In multivariate modeling, the m6ARLSig remained an independent predictor of prognosis. A nomogram incorporating m6ARLSig and clinicopathological parameters was constructed, providing a clinically adaptable tool for survival probability estimation. FAM83A-AS1 knockdown repressed A549 proliferation, invasion, migration, EMT, but increased apoptosis. Additionally, FAM83A-AS silence also attenuated cisplatin resistance of A549/DDP cells.</p><p><strong>Conclusion: </strong>Collectively, we identified a novel m6ARLSig with prognostic value in LUAD. The m6ARLSig showed associations with clinicopathological parameters, immune cell infiltration, and therapeutic responses. FAM831-AS1 may play oncogenic role in LUAD.</p>","PeriodicalId":19534,"journal":{"name":"OncoTargets and therapy","volume":"18 ","pages":"1107-1123"},"PeriodicalIF":2.8000,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12495916/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"OncoTargets and therapy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/OTT.S538953","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: This work aimed to identify m6A-related long non-coding RNAs (lncRNAs) associated with lung adenocarcinoma (LUAD) and evaluate their prognostic value and to examine the oncogenic actions of FAM83A-AS1 in LUAD.
Methods: The m6A-related lncRNAs in LUAD were identified by correlating lncRNA expression profiles with known m6A regulators using TCGA RNA-seq data. Prognostic lncRNAs were selected through univariate and multivariate Cox regression analyses and integrated into a risk model termed m6ARLSig. The model's predictive performance was assessed using Kaplan-Meier survival analysis, ROC curves, and principal component analysis. Immune infiltration and therapeutic responses were evaluated using CIBERSORT and drug sensitivity prediction. In vitro assays were conducted in A549 and A549/DDP cell lines to assess the oncogenic and drug resistance roles of FAM83A-AS1.
Results: We screened a set of m6A-related genes and identified a subset of m6A related-lncRNAs from TCGA through correlation analysis. Eight m6A-related lncRNAs were significantly associated with patient outcomes. AL606489.1 and COLCA1 functioned as independent adverse prognostic biomarkers, whereas six long non-coding RNAs served as independent favorable predictors of overall survival (OS). Eight lncRNAs were employed to develop a prognostic m6A-associated lncRNA signature (m6ARLSig). Based on personalized m6ARLSig levels, we computed a risk score for each individual and stratified the cohort into low-risk and high-risk categories. Survival analysis revealed a marked divergence in overall survival between the low- and high-risk cohorts, thereby substantiating the m6ARLSig's prognostic utility. In multivariate modeling, the m6ARLSig remained an independent predictor of prognosis. A nomogram incorporating m6ARLSig and clinicopathological parameters was constructed, providing a clinically adaptable tool for survival probability estimation. FAM83A-AS1 knockdown repressed A549 proliferation, invasion, migration, EMT, but increased apoptosis. Additionally, FAM83A-AS silence also attenuated cisplatin resistance of A549/DDP cells.
Conclusion: Collectively, we identified a novel m6ARLSig with prognostic value in LUAD. The m6ARLSig showed associations with clinicopathological parameters, immune cell infiltration, and therapeutic responses. FAM831-AS1 may play oncogenic role in LUAD.
期刊介绍：
OncoTargets and Therapy is an international, peer-reviewed journal focusing on molecular aspects of cancer research, that is, the molecular diagnosis of and targeted molecular or precision therapy for all types of cancer.
The journal is characterized by the rapid reporting of high-quality original research, basic science, reviews and evaluations, expert opinion and commentary that shed novel insight on a cancer or cancer subtype.
Specific topics covered by the journal include:
-Novel therapeutic targets and innovative agents
-Novel therapeutic regimens for improved benefit and/or decreased side effects
-Early stage clinical trials
Further considerations when submitting to OncoTargets and Therapy:
-Studies containing in vivo animal model data will be considered favorably.
-Tissue microarray analyses will not be considered except in cases where they are supported by comprehensive biological studies involving multiple cell lines.
-Biomarker association studies will be considered only when validated by comprehensive in vitro data and analysis of human tissue samples.
-Studies utilizing publicly available data (e.g. GWAS/TCGA/GEO etc.) should add to the body of knowledge about a specific disease or relevant phenotype and must be validated using the authors’ own data through replication in an independent sample set and functional follow-up.
-Bioinformatics studies must be validated using the authors’ own data through replication in an independent sample set and functional follow-up.
-Single nucleotide polymorphism (SNP) studies will not be considered.
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