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METTL14 functions as an RNA methyltransferase involved in m6A modification, influencing mRNA biogenesis, decay, and translation processes. However, the specific mechanism by which METTL14 regulates glucose-6-phosphate dehydrogenase (G6PD) to promote the progression of lung adenocarcinoma (LUAD) is not well understood. Quantitative measurement and immunohistochemistry (IHC) analysis have demonstrated higher levels of m6A in LUAD tissues compared to adjacent normal tissues. Additionally, the expression of METTL14 was significantly increased in LUAD tissues. In LUAD cell lines, both METTL14 and m6A levels were elevated compared to normal human lung epithelial cells. Knockdown of METTL14 markedly reduced LUAD cell proliferation, migration, and invasion. Conversely, overexpression of METTL14, but not the mutant form, significantly enhanced these cellular processes in LUAD. In vivo studies using nude mice with subcutaneously transplanted LUAD cells demonstrated that stable METTL14 knockdown led to notably reduced tumor volume and weight, along with fewer Ki67-positive cells and lung metastatic sites. Importantly, METTL14 knockdown reduced glycolytic activity in LUAD cells. Through a combination of RNA sequencing and MeRIP-sequencing, we identified numerous altered genes and confirmed that IGF2BP2 enhances G6PD mRNA stability after METTL14-mediated m6A modification, thereby promoting tumor growth and metastasis. Moreover, LUAD patients with higher levels of G6PD had poorer overall survival (OS). In conclusion, our study indicates that METTL14 upregulates G6PD expression post-transcriptionally through an m6A-IGF2BP2-dependent mechanism, thereby stabilizing G6PD mRNA. These findings propose potential diagnostic biomarkers and effective targets for anti-metabolism therapy in LUAD.
METTL14 functions as an RNA methyltransferase involved in m6A modification, influencing mRNA biogenesis, decay, and translation processes. However, the specific mechanism by which METTL14 regulates glucose-6-phosphate dehydrogenase (G6PD) to promote the progression of lung adenocarcinoma (LUAD) is not well understood. Quantitative measurement and immunohistochemistry (IHC) analysis have demonstrated higher levels of m6A in LUAD tissues compared to adjacent normal tissues. Additionally, the expression of METTL14 was significantly increased in LUAD tissues. In LUAD cell lines, both METTL14 and m6A levels were elevated compared to normal human lung epithelial cells. Knockdown of METTL14 markedly reduced LUAD cell proliferation, migration, and invasion. Conversely, overexpression of METTL14, but not the mutant form, significantly enhanced these cellular processes in LUAD. In vivo studies using nude mice with subcutaneously transplanted LUAD cells demonstrated that stable METTL14 knockdown led to notably reduced tumor volume and weight, along with fewer Ki67-positive cells and lung metastatic sites. Importantly, METTL14 knockdown reduced glycolytic activity in LUAD cells. Through a combination of RNA sequencing and MeRIP-sequencing, we identified numerous altered genes and confirmed that IGF2BP2 enhances G6PD mRNA stability after METTL14-mediated m6A modification, thereby promoting tumor growth and metastasis. Moreover, LUAD patients with higher levels of G6PD had poorer overall survival (OS). In conclusion, our study indicates that METTL14 upregulates G6PD expression post-transcriptionally through an m6A-IGF2BP2-dependent mechanism, thereby stabilizing G6PD mRNA. These findings propose potential diagnostic biomarkers and effective targets for anti-metabolism therapy in LUAD.
Background Distant metastasis is the major cause of lung adenocarcinoma (LUAD)-associated mortality. However, molecular mechanisms involved in LUAD metastasis remain to be fully understood. While the role of long non-coding RNAs (lncRNAs) in cancer development, progression, and treatment resistance is being increasingly appreciated, the list of dysregulated lncRNAs that contribute to LUAD pathogenesis is also rapidly expanding. Methods Bioinformatics analysis was conducted to interrogate publicly available LUAD datasets. In situ hybridization and qRT-PCR assays were used to test lncRNA expression in human LUAD tissues and cell lines, respectively. Wound healing as well as transwell migration and invasion assays were employed to examine LUAD cell migration and invasion in vitro. LUAD metastasis was examined using mouse models in vivo. RNA pulldown and RNA immunoprecipitation were carried out to test RNA–protein associations. Cycloheximide-chase assays were performed to monitor protein turnover rates and Western blotting was employed to test protein expression. Results The expression of the lncRNA LINC01559 was commonly upregulated in LUADs, in particular, in those with distant metastasis. High LINC01559 expression was associated with poor outcome of LUAD patients and was potentially an independent prognostic factor. Knockdown of LINC01559 diminished the potential of LUAD cell migration and invasion in vitro and reduced the formation of LUAD metastatic lesions in vivo. Mechanistically, LINC01559 binds to vimentin and prevents its ubiquitination and proteasomal degradation, leading to promotion of LUAD cell migration, invasion, and metastasis. Conclusion LINC01559 plays an important role in LUAD metastasis through stabilizing vimentin. The expression of LINC01559 is potentially an independent prognostic factor of LUAD patients, and LINC01559 targeting may represent a novel avenue for the treatment of late-stage LUAD.
BackgroundSerous ovarian carcinoma (SOC) is considered the most lethal gynecological malignancy. The current lack of reliable prognostic biomarkers for SOC reduces the efficacy of predictive, preventive, and personalized medicine (PPPM/3PM) in patients with SOC, leading to unsatisfactory therapeutic outcomes. N6-methyladenosine (m6A) modification-associated long noncoding RNAs (lncRNAs) are effective predictors of SOC. In this study, an effective risk prediction model for SOC was constructed based on m6A modification-associated lncRNAs.MethodsTranscriptomic data and clinical information of patients with SOC were downloaded from The Cancer Genome Atlas. Candidate lncRNAs were identified using univariate and multivariate and least absolute shrinkage and selection operator-penalized Cox regression analyses. The molecular mechanisms of m6A effector-related lncRNAs were explored via Gene Ontology, pathway analysis, gene set enrichment analysis, and gene set variation analysis (GSVA). The extent of immune cell infiltration was assessed using various algorithms, including CIBERSORT, Microenvironment Cell Populations counter, xCell, European Prospective Investigation into Cancer and Nutrition, and GSVA. The calcPhenotype algorithm was used to predict responses to the drugs commonly used in ovarian carcinoma therapy. In vitro experiments, such as migration and invasion Transwell assays, wound healing assays, and dot blot assays, were conducted to elucidate the functional roles of candidate lncRNAs.ResultsSix m6A effector-related lncRNAs that were markedly associated with prognosis were used to establish an m6A effector-related lncRNA risk model (m6A-LRM) for SOC. Immune microenvironment analysis suggested that the high-risk group exhibited a proinflammatory state and displayed increased sensitivity to immunotherapy. A nomogram was constructed with the m6A effector-related lncRNAs to assess the prognostic value of the model. Sixteen drugs potentially targeting m6A effector-related lncRNAs were identified. Furthermore, we developed an online web application for clinicians and researchers (https://leley.shinyapps.io/OC_m6A_lnc/). Overexpression of the lncRNA RP11-508M8.1 promoted SOC cell migration and invasion. METTL3 is an upstream regulator of RP11-508M8.1. The preliminary regulatory axis METTL3/m6A/RP11-508M8.1/hsa-miR-1270/ARSD underlying SOC was identified via a combination of in vitro and bioinformatic analyses.ConclusionIn this study, we propose an innovative prognostic risk model and provide novel insights into the mechanism underlying the role of m6A-related lncRNAs in SOC. Incorporating the m6A-LRM into PPPM may help identify high-risk patients and personalize treatment as early as possible.
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