Immune checkpoints signature-based risk stratification for prognosis of patients with gastric cancer

Abstract

Until now, few researches have comprehensive explored the role of immune checkpoints (ICIs) and tumor microenvironment (TME) in gastric cancer (GC) patients based on the genomic data. RNA-sequence data and clinical information were obtained from The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) database, GSE84437 and GSE84433. Univariate Cox analysis identified 60 ICIs with prognostic values, and these genes were then subjected to NMF cluster analysis and the GC samples (n = 804) were classified into two distinct subtypes (Cluster 1: n = 583; Cluster 2: n = 221). The Kaplan-Meier curves for OS analysis indicated that C1 predicted a poorer prognosis. The C2 subtype illustrated a relatively better prognosis and characteristics of “hot tumors,” including high immune score, overexpression of immune checkpoint molecules, and enriched tumor-infiltrated immune cells, indicating that the NMF clustering in GC was robust and stable. Regarding the patient's heterogeneity, an ICI-score was constructed to quantify the ICI patterns in individual patients. Moreover, the study found that the low ICI-score group contained mostly MSI-low events, and the high ICI-score group contained predominantly MSI-high events. In addition, the ICI-score groups had good responsiveness to CTLA4 and PD-1 based on The Cancer Immunome Atlas (TCIA) database. Our research firstly constructed ICIs signature, as well as identified some hub genes in GC patients.