Abstract
Immune checkpoint inhibitor (ICI) therapy is an emerging and effective approach to the treatment of gastric cancer (GC). However, the low response rate of GC patients to ICI therapy is a major limitation of ICI therapy. We investigated the transcriptomic signature of immune genes in GC could provide a comprehensive understanding of the tumor microenvironment (TME) and identify a valuable biomarker to predict the response of GC patients receiving immunotherapy. We performed the weighted gene co-expression network analysis (WGCNA) to determine immune-related hub genes that differentially expressed in the GC dataset based on The Cancer Genome Atlas (TCGA). After that, univariate and multivariate Cox regression was performed to recognize prognostic genes associated with overall survival and to develop an immune-related gene prognostic index (IRGPI). Furthermore, we explored the possible correlation between IRGPI and immune cell infiltration and immunotherapy efficacy. Notably, IRGPI can predict the prognosis of GC patients, as well as the response to immunotherapy. IRGPI as an immune-related prognostic biomarker might bring some potential implications for immunotherapy strategies in GC.
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