Wei Jianming, Gao Xibo, Li Zhufeng, Jia Yangpu, Li Chuan, Liu Jian
Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, China.
Department of Dermatology, Tianjin Children's Hospital, Tianjin, China.
Int J Med Sci. 2025 May 7;22(10):2533-2544. doi: 10.7150/ijms.107509. eCollection 2025.
Tumor differentiation grade was reported to be a prognostic factor in gastric cancer (GC). Here, we identify a novel tumor differentiation grade-related genes prognostic signature and provide new biomarkers using single-cell RNA sequencing (scRNA-seq) in GC. ScRNA-seq profiles of GC were analyzed by 'seurat' package. Tumor differentiation grade module was identified through a weighted gene co-expression network analysis (WGCNA). Hematoxylin and eosin (H&E) were performed to classify differentiation grade. The effects of tumor differentiation grade on prognosis were explored using the Kaplan-Meier. Tumor differentiation grade prognostic signature was constructed and validated in GC. Using GEO database, the scRNA-seq cell differentiation, clusters, and marker genes were identified in GC. Functional enrichment analysis revealed that common differentially expressed genes (DEGs) were mainly enriched in neutrophil process. Integrating clinical factors in GC, WGCNA analysis indicated that tumor differentiation grade module was the most significant. H&E and Kaplan-Meier analysis revealed that well-differentiated had a better prognosis in GC. Subsequently, tumor differentiation grade-related genes signature was established and validated (TNFAIP2, MAGEA3, CXCR4, COL1A1, FN1, VCAN, PXDN, COL5A1, MUC13 and RGS2). Cox regression analysis showed that age, TNM stage and the risk score were significantly associated with prognosis. And then, these genes could predict prognosis in GC. Finally, the hub gene COL5A1 was obviously correlated with B cells memory, dendritic cells activated, macrophages M0, macrophages M2, plasma cells, T cells follicular helper in GC. This study reveals a novel tumor differentiation grade-related genes signature, and COL5A1 represents a promising biomarker in GC.
肿瘤分化程度据报道是胃癌(GC)的一个预后因素。在此,我们鉴定了一种新的与肿瘤分化程度相关的基因预后特征,并利用胃癌的单细胞RNA测序(scRNA-seq)提供了新的生物标志物。通过“seurat”软件包分析胃癌的scRNA-seq图谱。通过加权基因共表达网络分析(WGCNA)确定肿瘤分化程度模块。进行苏木精和伊红(H&E)染色以分类分化程度。使用Kaplan-Meier法探讨肿瘤分化程度对预后的影响。构建并在胃癌中验证肿瘤分化程度预后特征。利用GEO数据库,在胃癌中鉴定scRNA-seq细胞分化、簇和标记基因。功能富集分析显示,常见的差异表达基因(DEG)主要富集于中性粒细胞过程。整合胃癌的临床因素,WGCNA分析表明肿瘤分化程度模块最为显著。H&E染色和Kaplan-Meier分析显示,高分化胃癌预后较好。随后,建立并验证了与肿瘤分化程度相关的基因特征(TNFAIP2、MAGEA3、CXCR4、COL1A1、FN1、VCAN、PXDN、COL5A1、MUC13和RGS2)。Cox回归分析表明,年龄、TNM分期和风险评分与预后显著相关。然后,这些基因可以预测胃癌的预后。最后,核心基因COL5A1与胃癌中的B细胞记忆、活化树突状细胞、M0巨噬细胞、M2巨噬细胞、浆细胞、滤泡辅助性T细胞明显相关。本研究揭示了一种新的与肿瘤分化程度相关的基因特征,COL5A1是胃癌中有前景的生物标志物。