METTL3 promotes tumour development by decreasing APC expression mediated by APC mRNA N6-methyladenosine-dependent YTHDF binding

Wang, Wei; Shao, Fei; Yang, Xueying; Wang, Juhong; Zhu, Rongxuan; Yang, Yannan; Zhao, Guiqiu; Guo, Dong; Sun, Yingnan; Wang, Jie; Qin, Xue; Gao, Shugeng; Gao, Yibo; He, Jie; Lu, Zhimin

doi:10.1038/s41467-021-23501-5

Cited by 87 publications

(63 citation statements)

References 62 publications

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“…As such, our findings support the use of METTL3 as a biomarker of acral melanoma initiation. Previously, the critical role of METTL3 mainly reflected in the great impact on cell proliferation, growth, survival, invasion, and angiogenesis ( 39 – 42 ). However, the regulation mechanism of METTL3 through m 6 A modification is diverse and elusive.…”

Section: Discussionmentioning

confidence: 99%

m6A Methyltransferase METTL3 Promotes the Progression of Primary Acral Melanoma via Mediating TXNDC5 Methylation

et al. 2022

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m6A modification is one of the most important post-transcriptional modifications in RNA and plays an important role in promoting translation or decay of RNAs. The role of m6A modifications has been highlighted by increasing evidence in various cancers, which, however, is rarely explored in acral melanoma. Here, we demonstrated that m6A level was highly elevated in acral melanoma tissues, along with the expression of METTL3, one of the most important m6A methyltransferase. Besides, higher expression of METTL3 messenger RNA (mRNA) correlated with a higher stage in primary acral melanoma patients. Knockdown of METTL3 decreased global m6A level in melanoma cells. Furthermore, METTL3 knockdown suppressed the proliferation, migration, and invasion of melanoma cells. In METTL3 knockdown xenograft mouse models, we observed decreased volumes and weights of melanoma tissues. Mechanistically, we found that METTL3 regulates certain m6A-methylated transcripts, thioredoxin domain containing protein 5 (TXNDC5), with the confirmation of RNA-seq, MeRIP-seq, and Western blot. These data suggest that METTL3 may play a key role in the progression of acral melanoma, and targeting the m6A dependent-METTL3 signaling pathway may serve as a promising therapeutic strategy for management of patients of acral melanomas.

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Section: Discussionmentioning

confidence: 99%

m6A Methyltransferase METTL3 Promotes the Progression of Primary Acral Melanoma via Mediating TXNDC5 Methylation

et al. 2022

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“…Our results also suggest this function of KIAA1429 to promote metastasis and highly expressed in m 6 A-C1 desert phenotype, but its prediction of patient survival may require the combination of RBM15, RBM15B, IGF2BP3, and HNRNPA2B1, with co-occurrence between them. YTHDCs and YTHDFs containing YTH domain act as "readers" in post-translational RNA methylation modification, and YTHDFs enhance aerobic glycolysis by degrading mRNA to further promote tumor formation (Wang et al, 2021;Xia et al, 2021). Our study confirms that both YTHDF1/3 and YTHDC1/2 are highly expressed in metastatic melanoma, and of interest, the high expression of YTHDF1 in patients with metastatic melanoma is accompanied by an indication of a poorer prognosis, which suggests a new direction for deeper studies of molecules containing YTH domain.…”

Section: Discussionmentioning

confidence: 99%

Identification of m6A Regulator-Associated Methylation Modification Clusters and Immune Profiles in Melanoma

Han

et al. 2021

Front. Cell Dev. Biol.

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RNA N6-methyladenosine (m6A) modification in tumorigenesis and progression has been highlighted and discovered in recent years. However, the molecular and clinical implications of m6A modification in melanoma tumor microenvironment (TME) and immune infiltration remain largely unknown. Here, we utilized consensus molecular clustering with nonnegative matrix factorization based on the melanoma transcriptomic profiles of 23 m6A regulators to determine the m6A modification clusters and m6A-related gene signature. Three distinct m6A modification patterns (m6A-C1, C2, and C3), which are characterized by specific m6A regulator expression, survival outcomes, and biological pathways, were identified in more than 1,000 melanoma samples. The immune profile analyses showed that these three m6A modification subtypes were highly consistent with the three known immune phenotypes: immune-desert (C1), immune-excluded (C2), and immune-inflamed (C3). Tumor digital cytometry (CIBERSORT, ssGSEA) algorithm revealed an upregulated infiltration of CD8+ T cell and NK cell in m6A-C3 subtype. An m6A scoring scheme calculated by principal component of m6A signatures stratified melanoma patients into high- and low-m6sig score subgroups; a high score was significantly associated with prolonged survival and enhanced immune infiltration. Furthermore, fewer somatic copy number alternations (SCNA) and PD-L1 expression were found in patients with high m6Sig score. In addition, patients with high m6Sig score demonstrated marked immune responses and durable clinical benefits in two independent immunotherapy cohorts. Overall, this study indicated that m6A modification is involved in melanoma tumor microenvironment immune regulation and contributes to formation of tumor immunogenicity. Comprehensive evaluation of the m6A modification pattern of individual tumors will provide more insights into molecular mechanisms of TME characterization and promote more effective personalized biotherapy strategies.

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“…A total of 12 N6-methyladenosine (m6A) regulatory genes were selected ( ALKBH5, FTO, HNRNPC, METTL3, METTL14, RBM15, WTAP, YTHDC1, YTHDC2, YTHDF1, YTHDF2 , and ZC3H13 ) as classical regulators of m6A RNA methylation according to previously published studies ( Feng et al, 2021 ; Hou et al, 2021 ; Wang W. et al, 2021 ; Zheng B. et al, 2021 ). We systematically compared the mRNA expression levels of these regulatory genes base on RNA-seq transcriptome data and visualized the analysis results using boxplots.…”

Section: Methodsmentioning

confidence: 99%

Identification and Validation of the Pyroptosis-Related Molecular Subtypes of Lung Adenocarcinoma by Bioinformatics and Machine Learning

Liu

Zhao

et al. 2021

Front. Cell Dev. Biol.

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Lung cancer remains the leading cause of cancer death globally, with lung adenocarcinoma (LUAD) being its most prevalent subtype. Due to the heterogeneity of LUAD, patients given the same treatment regimen may have different responses and clinical outcomes. Therefore, identifying new subtypes of LUAD is important for predicting prognosis and providing personalized treatment for patients. Pyroptosis-related genes play an essential role in anticancer, but there is limited research investigating pyroptosis in LUAD. In this study, 33 pyroptosis gene expression profiles and clinical information were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. By bioinformatics and machine learning analyses, we identified novel subtypes of LUAD based on 10 pyroptosis-related genes and further validated them in the GEO dataset, with machine learning models performing up to an AUC of 1 for classifying in GEO. A web-based tool was established for clinicians to use our clustering model (http://www.aimedicallab.com/tool/aiml-subphe-luad.html). LUAD patients were clustered into 3 subtypes (A, B, and C), and survival analysis showed that B had the best survival outcome and C had the worst survival outcome. The relationships between pyroptosis gene expression and clinical characteristics were further analyzed in the three molecular subtypes. Immune profiling revealed significant differences in immune cell infiltration among the three molecular subtypes. GO enrichment and KEGG pathway analyses were performed based on the differential genes of the three subtypes, indicating that differentially expressed genes (DEGs) were involved in multiple cellular and biological functions, including RNA catabolic process, mRNA catabolic process, and pathways of neurodegeneration-multiple diseases. Finally, we developed an 8-gene prognostic model that accurately predicted 1-, 3-, and 5-year overall survival. In conclusion, pyroptosis-related genes may play a critical role in LUAD, and provide new insights into the underlying mechanisms of LUAD.

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METTL3 promotes tumour development by decreasing APC expression mediated by APC mRNA N6-methyladenosine-dependent YTHDF binding

Cited by 87 publications

References 62 publications

m6A Methyltransferase METTL3 Promotes the Progression of Primary Acral Melanoma via Mediating TXNDC5 Methylation

m6A Methyltransferase METTL3 Promotes the Progression of Primary Acral Melanoma via Mediating TXNDC5 Methylation

Identification of m6A Regulator-Associated Methylation Modification Clusters and Immune Profiles in Melanoma

Identification and Validation of the Pyroptosis-Related Molecular Subtypes of Lung Adenocarcinoma by Bioinformatics and Machine Learning

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