Targeting Tumor Differentiation Grade-related Genes Prognostic Signature Including COL5A1 Based on Single-cell RNA-seq in Gastric Cancer.

Abstract

Background: 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. Methods: 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. Results: 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. Conclusions: This study reveals a novel tumor differentiation grade-related genes signature, and COL5A1 represents a promising biomarker in GC.