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Article Abstract

Lung adenocarcinoma (LUAD) is the predominant pathological subtype of non-small cell lung cancer (NSCLC). The four primary forms of RNA adenosine modifications, N6-methyladenosine (mA), N1-methyladenosine (mA), alternative polyadenylation (APA) and adenosine-to-inosine (A-to-I) RNA editing, play a critical role in tumor progression. However, the clinical significance of RNA modification writer-related long non-coding RNAs (lncRNAs) in LUAD remains unclear. The Cancer Genome Atlas (TCGA) database was used to obtain transcriptomic and clinicopathological data. Univariate Cox regression analysis, consensus cluster analysis, and least absolute shrinkage and selection operator (LASSO) Cox regression were used to establish the molecular subtypes and prognostic signatures of LUAD based on the expression levels of lncRNAs. ESTIMATE, CIBERSORT, ssGSEA, and TIDE algorithms were used to investigate immune cell infiltration and immunotherapy. In addition, IC of chemotherapeutic agents were calculated for different risk subgroups using the "pRRophetic" R package. Finally, the expression of prognosis-associated lncRNAs in lung cancer tissues was verified using qPCR. A prognostic risk signature containing seven lncRNAs associated with four types of RNA modification writers was established. The high-risk group had a poorer prognosis and higher clinicopathological grade. Most immune checkpoint genes and immune cell infiltration differed significantly between the two risk groups. The high-risk group had a higher tumor mutation burden (TMB), lower TIDE score, and was more sensitive to immunotherapy. We developed an RNA modification writer-related seven-lncRNA signature prognostic model that was associated with prognosis, tumor microenvironment, and response to immunotherapy in LUAD patients. Among them, LINC01352, AC024075.1, AC005070.3, AL133445.2, AC005856.1, and LINC00968 were downregulated in LUAD, whereas AC092168.2 was upregulated. This model may be a valuable tool for personalized LUAD therapies.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11310873PMC
http://dx.doi.org/10.7150/jca.96755DOI Listing

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