Abstract
Different subtypes of gastric cancer differentially respond to immune checkpoint inhibitors (ICI). This study aimed to investigate whether the Estimation of STromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm is related to the classification and prognosis of gastric cancer and to establish an ESTIMATE-based gene signature to predict the prognosis for patients. The immune/stromal scores of 388 gastric cancer patients from TCGA were used in this analysis. The upregulated differentially expressed genes (DEGs) in patients with high stromal/immune scores were identified. The immune-related hub DEGs were selected based on protein-protein interaction (PPI) analysis. The prognostic values of the hub DEGs were evaluated in the TCGA dataset and validated in the GSE15460 dataset using the Kaplan-Meier curves. A prognostic signature was built using the hub DEGs by Cox proportional hazards model, and the accuracy was assessed using receiver operating characteristic (ROC) analysis. Different subtypes of gastric cancer had significantly different immune/stromal scores. High stromal scores but not immune scores were significantly associated with short overall survivals of TCGA patients. Nine hub DEGs were identified in PPI analysisThe expression of these hub DEG negatively correlated with the overall survival in the TCGA cohort, which was validated in the GSE15460 cohort. A 9-gene prognostic signature was constructed. The risk factor of patients was calculated by this signature. High-risk patients had significantly shorter overall survival than low-risk patients. ROC analysis showed that the prognostic model accurately identified high-risk individuals within different time frames. We established an effective 9-gene-based risk signature to predict the prognosis of gastric cancer patients, providing guidance for prognostic stratification.
Highlights
Gastric cancer, with gastric adenocarcinoma comprising 95% of the total cases, ranks fifth for incidence and fourth for mortality worldwide (Sung et al, 2021)
The gene expression profiles of 388 patients with gastric adenocarcinoma were obtained from the the Cancer Genome Atlas (TCGA) database
We hypothesized that some factors in the tumor microenvironment (TME) contribute to the poor response of genomically stable (GS) subtype of gastric cancer to immune checkpoint inhibitors (ICI) therapy
Summary
With gastric adenocarcinoma comprising 95% of the total cases, ranks fifth for incidence and fourth for mortality worldwide (Sung et al, 2021). Curative gastrectomy with or without perioperative chemotherapy remains a standard treatment for gastric cancer. For unresectable or metastatic gastric cancer, chemotherapy using drugs such as platinum and taxol is a Prognostic Signature of Gastric Cancer standard treatment, with trastuzumab, a monoclonal antibody against human epidermal growth factor receptor 2 (HER2), as a first-line treatment for HER2-positive patients and ramucirumab, a monoclonal antibody against vascular endothelial growth factor receptor 2, as a second-line treatment for advanced disease (Bang et al, 2010; Sasako et al, 2011; Wagner et al, 2017). ICI monotherapy remains the third-line treatment for advanced, heavily pretreated gastric cancer due to its moderate efficacy in patients (Muro et al, 2016; Fuchs et al, 2018). It is necessary to investigate the mechanism underlying the limited efficacy of ICI in gastric cancer treatment
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