Identification and verification of m7G-Related genes as biomarkers for prognosis of sarcoma

Abstract

Background: Increasing evidence indicates a crucial role for N7-methylguanosine (m7G) methylation modification in human disease development, particularly cancer, and aberrant m7G levels are closely associated with tumorigenesis and progression via regulation of the expression of multiple oncogenes and tumor suppressor genes. However, the role of m7G in sarcomas (SARC) has not been adequately evaluated.Materials and methods: Transcriptome and clinical data were gathered from the TCGA database for this study. Normal and SARC groups were compared for the expression of m7G-related genes (m7GRGs). The expression of m7GRGs was verified using real-time quantitative PCR (RT-qPCR) in SARC cell lines. Then, differentially expressed genes (DEGs) were identified between high and low m7GRGs expression groups in SARC samples, and GO enrichment and KEGG pathways were evaluated. Next, prognostic values of m7GRGs were evaluated by Cox regression analysis. Subsequently, a prognostic model was constructed using m7GRGs with good prognostic values by Lasso regression analysis. Besides, the relationships between prognostic m7GRGs and immune infiltration, clinical features, cuproptosis-related genes, and antitumor drugs were investigated in patients with SARC. Finally, a ceRNA regulatory network based on m7GRGs was constructed.Results: The expression of ten m7GRGs was higher in the SARC group than in the control group. DEGs across groups with high and low m7GRGs expression were enriched for adhesion sites and cGMP-PKG. Besides, we constructed a prognostic model that consists of EIF4A1, EIF4G3, NCBP1, and WDR4 m7GRGs for predicting the survival likelihood of sarcoma patients. And the elevated expression of these four prognostic m7GRGs was substantially associated with poor prognosis and elevated expression in SARC cell lines. Moreover, we discovered that these four m7GRGs expressions were negatively correlated with CD4+ T cell levels, dendritic cell level and tumor purity, and positively correlated with tumor mutational burden, microsatellite instability, drug sensitivity and cuproptosis-related genes in patients with sarcomas. Then, a triple regulatory network of mRNA, miRNA, and lncRNA was established.Conclusion: The current study identified EIF4A1, EIF4G3, NCBP1, and WDR4 as prognostic genes for SARC that are associated with m7G.These findings extend our knowledge of m7G methylation in SARC and may guide the development of innovative treatment options.

Correlation analysis of disulfidptosis-related gene signatures with clinical prognosis and immunotherapy response in sarcoma

“…Moreover, the authors elucidated that liquid biopsy based on DNA methylation can identify and monitor primary and metastatic malignant tumors while assessing tumor heterogeneity. Qin et al 66 demonstrated that m7G-related genes exhibit significantly upregulated expression in SARC and established an m7G-related prognostic model for predicting the survival rate of sarcoma patients. Presently, there exists a dearth of research investigating the association between DNA methylation and early diagnosis and prognosis in sarcoma patients, along with the potential of DNA methylation analysis to become a predictive indicator of sarcoma treatment efficacy.…”

Tumor-associated characteristics and immune dysregulation in nasopharyngeal carcinoma under the regulation of m7G-related tumor microenvironment cells

“…We speculate that EIF4A1 may regulate macrophages via the transcriptional regulation of CD68, thereby causing macrophage M1 polarization. The epigenetic regulation of EIF4A1 transcripts plays an oncogenic role [57], and the prognosis of patients with cancer is associated with EIF4A1 [58,59]. Currently, there is an increasing number of studies of EIF4A1 inhibitors for tumor treatment [55,60,61].…”

Identification and prediction of m7G-related Alzheimer’s disease subtypes: insights from immune infiltration and machine learning models

“…The gene expression profiles of the three datasets were normalized and processed using the "Perl" script and R package "limma." Subsequently, 22 m7G regulators were identified from previous publications (Luo et al, 2022;Li et al, 2023;Maimaiti et al, 2023;Qin et al, 2023).…”