Cell differentiation trajectory predicts patient potential immunotherapy response and prognosis in gastric cancer

Abstract

The purpose of this study was to investigate the differentiation trajectory of gastric cancer (GC) cells and its clinical relevance and generate a prognostic risk scoring (RS) signature based on GC differentiation-related genes (GDRGs) to predict overall survival (OS). Integrated single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from GC samples were used for analysis. The cell differentiation trajectory analysis identified three subsets with distinct differentiation states, of which subsets I/II were involved in metabolic disorders, subset II were also associated with hypoxia tolerance, and subset III were related to immune-related pathways. GC samples were divided into three GDRG-based molecular subtypes, and it was found that molecular typing based on cell differentiation successfully predicted patient OS, clinicopathological features, immune infiltration status, and immune checkpoint gene expression. An eight-GDRG-based prognostic RS signature was generated, and the OS of the high-risk group was significantly worse than that of the low-risk group. By integrating the GDRG-based RS signature with prognostic clinicopathological characteristics, a clinicopathologic-genomic nomogram was constructed, and this nomogram yielded strong predictive performance and high accuracy. The study highlights the implication of GC cell differentiation for predicting patient clinical outcome and potential immunotherapy response and proposes a promising treatment direction for GC.