ABSTRACT
Objective:The aim of this study was to determine the development and validation of a prognostic prediction model based on genes associated with N7 methylguanosine(m7G)RNA methylation modifications in breast cancer(BC)patients.Methods:We explored the expression patterns of 31 key m7G RNA methylation-related regulators in breast cancer tissues and their prognostic significance.First,we downloaded and analyzed the mRNA gene expression and clinical prognostic data from The Cancer Genome Atlas(TCGA)and Gene Expression Gene Expression(GEO)databases.The prognostic value of each m7G-related gene for survival was assessed by us-ing univariate Cox regression analysis.A prognostic risk model based on m7G methylation-regulat-ed genes was then constructed by applying the least absolute shrinkage and selection operator(LASSO)regression method.Patients were divided into high-risk and low-risk groups according to median risk scores,and the differences in overall survival(OS)between high-and low-risk groups were compared.Then,gene set enrichment analysis(GSEA)analysis was performed to elaborate the main mechanisms of action in the BC high-risk group.Finally,a prognostic nomogram based on m7G was constructed and validated in TCGA and GEO cohorts respectively.Results:A prognostic risk model based on seven m7G methylation-regulated genes was constructed.The overall survival(OS)was significantly lower in the high-risk group than in the low-risk group(P＜0.001).GSEA anal-ysis showed that the"cell cycle"was the most important pathways in the high-risk group.Using risk scores and clinical characteristics of the training set TCGA cohort,prognostic nomogram was constructed,and calibration curves and decision curve analysis(DCA)showed good concordance and predictive efficacy and were validated in the GEO cohort.Conclusion:The prognostic model based on m7G-related genes plays an important prognostic predictive role in breast cancer and can be used to guide the individualized treatment of breast cancer patients.
ABSTRACT
@#[摘 要] N7-甲基鸟苷（m7G）是表观遗传学调控过程中最常见的RNA修饰之一，在mRNA、核糖体RNA（rRNA）、转运RNA（tRNA）、miRNA等多种RNA分子的加工和代谢中起着重要作用，进而参与细胞增殖、分化、凋亡和迁移等多种功能。越来越多的证据表明，m7G甲基化修饰参与肿瘤的发生发展。异常的m7G甲基化修饰通过调控癌基因和抑制基因的表达促进或抑制多种肿瘤的进展，m7G甲基化修饰及其调控因子可能是肿瘤诊断和治疗的潜在靶点。本文就m7G甲基化修饰的最新研究进展、检测方法及其在肿瘤发生发展中作用的分子机制进行评述。
ABSTRACT
N7-methylguanosine (m7G) is a common post-transcriptional modification of RNA that plays an important role in RNA processing, metabolism and function and is mainly regulated by the methyltransferase 1 (METTL1) and WD repeat domain 4 (WDR4) complexes. Several studies have shown that the METTL1/WDR4 complex promotes or inhibits the progression of many tumours, including head and neck tumours, lung, liver, colon, bladder and esophageal squamous cancers, which are dependent on m7G methylation modification of tRNA or miRNA. Therefore, METTL1 and m7G modification can be used as biomarkers or potential intervention targets, providing a new direction for early diagnosis and treatment of tumors. This article will mainly discuss the mechanism and corresponding research progress of METTL1 in tumorigenesis through m7G.
ABSTRACT
OBJECTIVE@#To assess the value of m7G-lncRNAs in predicting the prognosis and microenvironment of colorectal cancer (CRC).@*METHODS@#We screened m7G-lncRNAs from TCGA to construct an m7G-lncRNAs risk model using multivariate Cox analysis, which was validated using ROC and C-index curves. Calibration and nomogram were used to predict the prognosis of CRC patients. Point-bar charts and K-M survival curves were used to assess the correlation of risk scores with the patients' clinical staging and prognosis. CIBERSORT and ESTIMATE were used to explore the association between the tumor microenvironment and immune cell infiltration in patients in high and low risk groups and the correlation of risk scores with microsatellite instability, stem cell index and immune checkpoint expression. A protein-protein interaction network was constructed, and the key targets regulated by m7G-lncRNAs were identified and validated in paired samples of CRC and adjacent tissues by immunoblotting.@*RESULTS@#We identified a total of 1722 m7G-lncRNAs from TCGA database, from which 12 lncRNAs were screened to construct the risk model. The AUCs of the risk model for predicting survival outcomes at 1, 3 and 5 years were 0.727, 0.747 and 0.794, respectively. The AUC of the nomogram for predicting prognosis was 0.794, and the predicted results were consistent with actual survival outcomes of the patients. The patients in the high-risk group showed more advanced tumor stages and a greater likelihood of high microsatellite instability than those in the low-risk group (P < 0.05). The tumor stemness index was negatively correlated with the risk score (r=-0.19; P=7.3e-05). Patients in the high-risk group had higher stromal cell scores (P=0.0028) and higher total scores (P=0.007) with lowered expressions of activated mast cells (r=-0.11; P=0.045) and resting CD4+ T cells (r=-0.14; P=0.01) and increased expressions of most immune checkpoints (P < 0.05). ATXN2 (P= 0.006) and G3BP1 (P=0.007) were identified as the key targets regulated by m7G-lncRNAs, and their expressions were both higher in CRC than in adjacent tissues.@*CONCLUSION@#The risk model based on 12 m7G-lncRNAs has important prognostic value for CRC and can reflect the microenvironment and the efficacy of immunotherapy in the patients.