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Abstract Background FBXW7 m6A modification plays an important role in lung adenocarcinoma (LUAD) progression; however, the underlying mechanisms remain unclear. Methods The correlation between FBXW7 and various genes related to m6A modification was analyzed using The Cancer Genome Atlas database. The regulatory effects of METTL3 on FBXW7 mRNA m6A modification were examined in a cell model, and the underlying mechanism was determined by methylated RNA immunoprecipitation, RNA immunoprecipitation, luciferase reporter, and mutagenesis assays. In vitro experiments were performed to further explore the biological effects of METTL3-mediated FBXW7 m6A modification on LUAD development. Results Decreased FBXW7 expression was accompanied by downregulated METTL3 expression in human LUAD tissues and was associated with a worse prognosis for LUAD in The Cancer Genome Atlas database. m6A was highly enriched in METTL3-mediated FBXW7 transcripts, and increased m6A modification in the coding sequence region increased its translation. Functionally, METTL3 overexpression or knockdown affected the apoptosis and proliferation phenotype of LUAD cells by regulating FBXW7 m6A modification and expression. Furthermore, FBXW7 overexpression in METTL3-depleted cells partially restored LUAD cell suppression in vitro and in vivo. Conclusions Our findings reveal that METTL3 positively regulates FBXW7 expression and confirm the tumor-suppressive role of m6A-modified FBXW7, thus providing insight into its epigenetic regulatory mechanisms in LUAD initiation and development.

Abstract Background Lung adenocarcinoma (LUAD) remains a crucial factor endangering human health. Gene-based clinical predictions could be of great help for cancer intervention strategies. Here, we tried to build a gene-based survival score (SS) for LUAD via analyzing multiple transcriptional datasets. Methods We first acquired differentially expressed genes between tumors and normal tissues from intersections of four LUAD datasets. Next, survival-related genes were preliminarily unscrambled by univariate Cox regression and further filtrated by LASSO regression. Then, we applied PCA to establish a comprehensive SS based on survival-related genes. Subsequently, we applied four independent LUAD datasets to evaluate prognostic prediction of SS. Moreover, we explored associations between SS and clinicopathological features. Furthermore, we assessed independent predictive value of SS by multivariate Cox analysis and then built prognostic models based on clinical stage and SS. Finally, we performed pathway enrichments analysis and investigated immune checkpoints expression underlying SS in four datasets. Results We established a 13 gene-based SS, which could precisely predict OS and PFS of LUAD. Close relations were elicited between SS and canonical malignant indictors. Furthermore, SS could serve as an independent risk factor for OS and PFS. Besides, the predictive efficacies of prognostic models were also reasonable (C-indexes: OS, 0.7; PFS, 0.7). Finally, we demonstrated enhanced cell proliferation and immune escape might account for high clinical risk of SS. Conclusions We built a 13 gene-based SS for prognostic prediction of LUAD, which exhibited wide applicability and could contribute to LUAD management.