Deng Kun, Li Jian-Xin, Yang Rui, Mou Zhi-Qiang, Yang Li, Yang Qing-Qiang
Department of General Surgery (Gastrointestinal Surgery), The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Department of General Surgery (Hepatobiliary Surgery), The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Transl Cancer Res. 2023 Jul 31;12(7):1836-1851. doi: 10.21037/tcr-22-2614. Epub 2023 Jul 28.
The role of N7-methyladenosine (m7G)-related genes in the progression and prognosis of gastric cancer (GC) remains unclear. This study aimed to explore prognostic biomarkers for GC based on m7G methylation regulators and to construct a prognostic risk model.
RNA sequencing profiles with corresponding clinicopathological information associated with GC of which the histological type was stomach adenocarcinoma (STAD) were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. A total of 29 m7G regulators were extracted from previous studies. According to the expression similarity of m7G regulators, the GC samples obtained from TCGA were further classified into 2 clusters demonstrating different overall survival (OS) rates and genetic heterogeneity, and the differentially expressed genes (DEGs) between these 2 clusters were defined as m7G-related genes. Univariate regression analysis and regression analysis were then used to obtain the prognostic m7G-related genes. The samples in TCGA and Genotype-Tissue Expression (GTEx) were used to verify the differential expression and prognostic value of these m7G-related genes contained in the prognostic model. Subsequently, the risk score was combined with other prognostic factors to develop a nomogram. The predictive ability of the nomogram was evaluated by the standard receiver operating characteristic (ROC) curve. Gene set enrichment analysis (GSEA) was used to identify activation pathways in both groups. Finally, the association between the prognostic model and the immune characteristics of GC were appraised.
A prognostic model consisting of 11 m7G-related genes was constructed. GC patients in the high-risk group were shown to have a poor prognosis and this result was further demonstrated in each group. The risk model can be applied for patients with different clinical features. The results of GSEA showed that cell adhesion, cell junction, and focal adhesion were highly enriched in the high-risk group. In addition, we found that the expression of programmed cell death ligand 1 (PD-L1) was significantly elevated in the low-risk group, whereas programmed cell death ligand 2 (PD-L2) and tumor necrosis factor receptor superfamily member 4 (TNFRSF4) were overexpressed in the high-risk group.
We successfully built and verified a m7G relevant prognostic model for predicting prognosis and providing a new train of thought for improving the treatment of GC.
N7-甲基腺苷（m7G）相关基因在胃癌（GC）进展和预后中的作用仍不清楚。本研究旨在探索基于m7G甲基化调节因子的GC预后生物标志物并构建预后风险模型。
分别从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）获取组织学类型为胃腺癌（STAD）的GC相关RNA测序图谱及相应临床病理信息。从既往研究中提取了总共29个m7G调节因子。根据m7G调节因子的表达相似性，将从TCGA获得的GC样本进一步分为2个簇，这两个簇显示出不同的总生存期（OS）率和基因异质性，将这2个簇之间的差异表达基因（DEG）定义为m7G相关基因。然后使用单因素回归分析和多因素回归分析来获得预后m7G相关基因。利用TCGA和基因型-组织表达（GTEx）中的样本验证预后模型中这些m7G相关基因的差异表达和预后价值。随后，将风险评分与其他预后因素相结合以制定列线图。通过标准受试者工作特征（ROC）曲线评估列线图的预测能力。采用基因集富集分析（GSEA）来识别两组中的激活途径。最后，评估预后模型与GC免疫特征之间的关联。
构建了一个由11个m7G相关基因组成的预后模型。高危组的GC患者显示预后不良，并且在每组中进一步得到证实。该风险模型可应用于具有不同临床特征的患者。GSEA结果表明，细胞黏附、细胞连接和黏着斑在高危组中高度富集。此外，我们发现程序性细胞死亡配体1（PD-L1）的表达在低危组中显著升高，而程序性细胞死亡配体2（PD-L2）和肿瘤坏死因子受体超家族成员4（TNFRSF4）在高危组中过表达。
我们成功构建并验证了一个m7G相关预后模型，用于预测预后并为改善GC治疗提供新思路。
