Relationships of N6-Methyladenosine-Related Long Non-Coding RNAs With Tumor Immune Microenvironment and Clinical Prognosis in Lung Adenocarcinoma

Abstract

Background: Lung adenocarcinoma (LUAD) is the major subtype of lung cancer and is associated with very high mortality. Emerging studies have shown that N6-methyladenosine (m6A)-related long non-coding (lnc) RNAs play crucial roles in tumor prognosis and the tumor immune microenvironment (TME). We aimed to explore the expression patterns of different m6A-related lncRNAs concerning patient prognosis and construct an m6A-related lncRNA prognostic model for LUAD.Methods: The prognostic value of m6A-related lncRNAs was investigated in LUAD samples from The Cancer Genome Atlas (TCGA). Potential prognostic m6A-related lncRNAs were selected by Pearson’s correlation and univariate Cox regression analysis. Patients were divided into clusters using principal component analysis and the m6A-related lncRNA prognostic signature was calculated using least absolute shrinkage and selection operator (LASSO) Cox regression analysis.Results: Based on 91 prognostic m6A-related lncRNAs, we identified two m6A-related-lncRNA pattern clusters with different overall survival (OS) and different TMEs. We subsequently verified our findings multidimensionally by constructing a 13 m6A-related lncRNA prognostic signature (m6A-LPS) to calculate the risk score, which was robust in different subgroups. The receiver operating characteristic (ROC) curves and concordance index demonstrated that m6A-LPS harbored a promising ability to predict OS in TCGA data set and independent GSE11969 cohort. The risk score was also related to OS, TME, and clinical stage, and the risk score calculated by our model was also identified as independent prognostic predictive factors for LUAD patients after adjustment for age, smoking, gender, and stage. Enrichment analysis indicated that malignancy and drug resistance-associated pathways were more common in cluster2 (LUAD-unfavorable m6A-LPS). Furthermore, the results indicated that the signaling pathway enriched by the target gene of 13 m6A-related lncRNAs may be associated with metastasis and progression of cancer according to current studies.Conclusion: The current results indicated that different m6A-related-lncRNA patterns could affect OS and TME in patients with LUAD, and the prognostic signature based on 13 m6A-related lncRNAs may help to predict the prognosis in LUAD patients.

N6-methyladenosine (m6A) methyltransferase METTL3-mediated LINC00680 accelerates osteoarthritis through m6A/SIRT1 manner

“…Lately, studies have found that m 6 A modification could regulate the metabolism of lncRNAs [ 24 , 25 ]. For example, in non-small-cell lung cancer, MeRIP-Seq discovers that there was a m 6 A modification site in ABHD11-AS1 and METTL3 promotes the ABHD11-AS1 transcript stability to increase its expression [ 26 ].…”

N6-methyladenine- induced LINC00667 promoted breast cancer progression through m6A/KIAA1429 positive feedback loop

“…Compared to mRNAs, lncRNAs are also abundantly expressed in BC. The chemical internal modification on eukaryotic messenger RNAs dramatically changes the fate of RNAs [ 17 ]. In addition to this, the m 6 A modification on lncRNA also enriches the biological functions of lncRNAs in cancers.…”

N6-Methyladenosine-Related lncRNAs Are Novel Prognostic Markers and Predict the Immune Landscape in Acute Myeloid Leukemia

“…The PI3K/Akt/mTOR signaling pathway was found to be potentially affected by m6A regulators in most cancers such as gastrointestinal cancer ( Zhao Q. et al, 2020 ) and ovarian cancer ( Bi et al, 2021 ), which was consistent with our results. M6A modification of lncRNAs may affect the occurrence and development of tumors, lncRNAs may also target m6A regulators as competitive endogenous RNAs, affecting tumor invasive progression ( Xu F. et al, 2021 ; Zhao et al, 2021 ). Taken together, these findings implied potential correlation between m6A-modified lncRNAs and AML initiation or progression.…”

“…The expression and co-expression of m6A-related genes in AML were studied. Next, we calculated the correlation coefficient and p value between m6A-related genes and lncRNA profiles, and m6A-related lncRNAs were identified according to the standard of p < 0.05 in the correlation analysis as mentioned in previous studies ( Zhang P. et al, 2021 ; Zhao et al, 2021 ). Moreover, we incorporated the expression of m6A-related lncRNA in TCGA and the GEO database into model construction.…”