Elevated METTL9 is associated with peritoneal dissemination in human scirrhous gastric cancers

METTL Family in Healthy and Disease

Transcription, RNA splicing, RNA translation, and post-translational protein modification are fundamental processes of gene expression. Epigenetic modifications, such as DNA methylation, RNA modifications, and protein modifications, play a crucial role in regulating gene expression. The methyltransferase-like protein (METTL) family, a constituent of the 7-β-strand (7BS) methyltransferase subfamily, is broadly distributed across the cell nucleus, cytoplasm, and mitochondria. Members of the METTL family, through their S-adenosyl methionine (SAM) binding domain, can transfer methyl groups to DNA, RNA, or proteins, thereby impacting processes such as DNA replication, transcription, and mRNA translation, to participate in the maintenance of normal function or promote disease development. This review primarily examines the involvement of the METTL family in normal cell differentiation, the maintenance of mitochondrial function, and its association with tumor formation, the nervous system, and cardiovascular diseases. Notably, the METTL family is intricately linked to cellular translation, particularly in its regulation of translation factors. Members represent important molecules in disease development processes and are associated with patient immunity and tolerance to radiotherapy and chemotherapy. Moreover, future research directions could include the development of drugs or antibodies targeting its structural domains, and utilizing nanomaterials to carry miRNA corresponding to METTL family mRNA. Additionally, the precise mechanisms underlying the interactions between the METTL family and cellular translation factors remain to be clarified.

Identification of shared gene signatures and pathways for diagnosing osteoporosis with sarcopenia through integrated bioinformatics analysis and machine learning

BACKGROUND

Prior studies have suggested a potential relationship between osteoporosis and sarcopenia, both of which can present symptoms of compromised mobility. Additionally, fractures among the elderly are often considered a common outcome of both conditions. There is a strong correlation between fractures in the elderly population, decreased muscle mass, weakened muscle strength, heightened risk of falls, and diminished bone density. This study aimed to pinpoint crucial diagnostic candidate genes for osteoporosis patients with concomitant sarcopenia.

METHODS

Two osteoporosis datasets and one sarcopenia dataset were obtained from the Gene Expression Omnibus (GEO). Differential expression genes (DEGs) and module genes were identified using Limma and Weighted Gene Co-expression Network Analysis (WGCNA), followed by functional enrichment analysis, construction of protein-protein interaction (PPI) networks, and application of a machine learning algorithm (least absolute shrinkage and selection operator (LASSO) regression) to determine candidate hub genes for diagnosing osteoporosis combined with sarcopenia. Receiver operating characteristic (ROC) curves and column line plots were generated.

RESULTS

The merged osteoporosis dataset comprised 2067 DEGs, with 424 module genes filtered in sarcopenia. The intersection of DEGs between osteoporosis and sarcopenia module genes consisted of 60 genes, primarily enriched in viral infection. Through construction of the PPI network, 30 node genes were filtered, and after machine learning, 7 candidate hub genes were selected for column line plot construction and diagnostic value assessment. Both the column line plots and all 7 candidate hub genes exhibited high diagnostic value (area under the curve ranging from 1.00 to 0.93).

CONCLUSION

We identified 7 candidate hub genes (PDP1, ALS2CL, VLDLR, PLEKHA6, PPP1CB, MOSPD2, METTL9) and constructed column line plots for osteoporosis combined with sarcopenia. This study provides reference for potential peripheral blood diagnostic candidate genes for sarcopenia in osteoporosis patients.

METTL9-SLC7A11 axis promotes hepatocellular carcinoma progression through ferroptosis inhibition

Methytransferase-like proteins 9 (METTL9) has been characterized as an oncogene in several cancers, however, its role in hepatocellular carcinoma (HCC) remains unknown. Here, we investigated the function and molecular mechanism of METTL9 in HCC. We showed that METTL9 expression was elevated in HCC, and its high expression was associated with poor survival outcomes. Knockdown of METTL9 observed a significant inhibition of HCC cell viability, migration, and invasion both in vitro and in vivo. By contrast, METTL9 overexpression HCC cells obtained stronger abilities in cell proliferation and migration. Mechanistically, we discovered that METTL9 knockdown led to a reduction in the expression level of SLC7A11, a key suppressor of ferroptosis, in turn, promoted ferroptosis in HCC cells, impeding the progression of HCC. Moreover, we have proved that targeting METTL9 could significantly restrain the growth of HCC patient-derived xenograft (PDX). Our study established METTL9 as a critical role in promoting HCC development and provides a foundation for further investigation and potential therapeutic interventions targeting ferroptosis in HCC.

Comprehensive Analysis of METTLs (METTL1/13/18/21A/23/25/2A/2B/5/6/9) and Associated mRNA Risk Signature in Hepatocellular Carcinoma

Currently, 80%-90% of liver cancers are hepatocellular carcinomas (HCC). HCC patients develop insidiously and have an inferior prognosis. The methyltransferase-like (METTL) family principal members are strongly associated with epigenetic and tumor progression. The present study mainly analyzed the value of METTLs (METTL1/13/18/21A/23/25/2A/2B/5/6/9) and associated mRNA risk signature for HCC. METTLs expression is upregulated in HCC and is a poor prognostic factor in HCC. METTLs were upregulated in patients older than 60 and associated with grade. Except for METTL25, the remaining 10 genes were associated with the HCC stage, invasion depth (T). In addition, METTLs showed an overall alteration rate of 50%. Except for METTL13/2A/25/9, the expression of the other seven genes was significantly associated with overall survival, disease-specific survival, and progression-free survival. Multivariate studies have shown that METTL21A/6 can be an independent prognostic marker in HCC. A total of 664 mRNAs were selected based on Pearson correlation coefficient (R > 0.5), unsupervised consensus clustering, weighted coexpression network analysis, and univariate Cox analysis. These mRNAs were significantly associated with METTLs and were poor prognostic factors in HCC patients. The least absolute shrinkage and selection operator (lasso) was used to construct the best METTLs associated with mRNA risk signature. The mRNA risk signature was significantly associated with age, stage, and t grade. The mRNA high-risk group had higher TP53 and RB1 mutations. This study constructed a nomogram with the mRNA risk profile and clinicopathological features, which could better predict the OS of individuals with HCC. We also analyzed associations between METTLs and mRNA risk signatures in epithelial-mesenchymal transition, immune checkpoints, immune cell infiltration, tumor mutational burden, microsatellite instability, cancer stem cells, tumor pathways, and drug sensitivity. In addition, this study constructed a protein interaction network network including METTLs and mRNA risk signature genes related to tumor microenvironment remodeling based on single-cell sequencing. In conclusion, this study provides a theoretical basis for the mechanism, biomarker screening, and treatment of HCC.

SETD3 Methyltransferase Regulates PLK1 Expression to Promote In Situ Hepatic Carcinogenesis

Background

The development of a new strategy to overcome chemoresistance to hepatocellular carcinoma (HCC) treatment is a long-standing issue. We have previously found that upregulated SETD3 levels are closely correlated with HCC. This study aims to explore the mechanism underlying how upregulation of SETD3 promotes liver carcinogenesis.

Methods

RNA-Sequencing analysis was used to explore the correlation of SETD3 with regulatory targets. In vitro assays including cell proliferation and migration were performed to study the oncogenic roles of SETD3 and PLK1. Western blotting, immunohistochemical staining, and blood biochemical assays were performed to examine protein expression or pathological index in tumor tissues and mice liver tissues. Luciferase reporter system and chromatin immunoprecipitation assays were used to explore the mechanism.

Results

We revealed that SETD3 regulates gene expression in subgroups, including cell division, cell proliferation, and cell cycle, in hepatocellular tumor cells. We found that SETD3 upregulation is associated with elevated PLK1 level in both hepatic tumor cells and clinical liver tissues. We further showed that overexpression of SETD3 promoted tumor cell proliferation and migration, whereas inhibition of PLK1 activity attenuated these phenotypes caused by SETD3. By taking advantage of the Sleep Beauty transposase system, we confirmed that upregulated mouse Setd3 promoted hepatic carcinogenesis in situ, but knockdown of mouse Plk1 mitigated Setd3-promoted tumorigenesis in mice. Mechanistically, we showed that SETD3 could be recruited to the promoter of PLK1 gene to facilitate PLK1 transcription.

Conclusions

Our data demonstrate that elevated SETD3 may promote HCC by enhancing PLK1 expression, which suggests that SETD3 may act as a potential drug target combined with PLK1 inhibition to treat HCC.