Identification and validation of the prognostic value of cyclic GMP-AMP synthase-stimulator of interferon (cGAS-STING) related genes in gastric cancer

ABSTRACT

The cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway play a significant role in the production of inflammatory cytokines and type I interferons. This study aims to develop a cGAS-STING pathway-related genes (CSRs) prediction model to predict prognosis in gastric cancer (GC). In the present study, we used The Cancer Genome Atlas (TCGA), Gene Expression Omnibus databases (GEO), CIBERSORT and Tumor Immune Estimation Resource databases (TIMER). The risk model based on five hub genes (IFNB1, IFNA4, IL6, NFKB2, and TRIM25) was constructed to predict the overall survival (OS) of GC. Further univariate Cox regression (URC) and multivariate Cox regression (MCR) analyses revealed that this risk scoring model was an independent factor. The results were verified by GEO external validation set. Multiple immune pathways were assessed by Gene Set Enrichment Analysis (GSEA). TIMER analysis demonstrated that risk score strongly correlated with Macrophage, B cells and CD8 + T cells infiltration. In addition, through ‘CIBERSORT’ package, the higher levels of infiltration of T cell follicular assistance (P = 0.011), NK cells-activated (P = 0.034), and Dendritic cells resting (P = 0.033) exhibited in high-risk group. Kaplan–Meier (K-M) survival analysis illustrated T cells CD4 memory resting and T cells follicular helper infiltration correlated with overall survival (OS) of GC patients in TCGA and GEO databases. Altogether, the risk score model can be conveniently used to predict prognosis. The immunocyte infiltration analysis provided a novel horizon for monitoring the status of the GC immune microenvironment.

Abbreviations:TCGA: The Cancer Genome Atlas databases; GEO: Gene Expression Omnibus databases; GC: Gastric cancer; CSRs: cGAS-STING pathway-related genes; DECSRs: Differential expressed cGAS-STING pathway-related genes; PCSRs: Prognosis related cGAS-STING pathway genes; URC: Univariate Cox regression analyses; MCR: Multivariate Cox regression analyses GSEA: Gene set enrichment analysis; TIIC: Tumor-infiltrating immune cell.

KEYWORDS:

• Gastric cancer
• cGAS-STING pathway
• tumor immune
• prognostic model

Highlights

(1) A cGAS-STING pathway-related prognostic index to predict the prognosis of GC was constructed.

(2) The prognostic index is an independent index for GC prognosis.

(3) The prognostic index may affect immune-related biological processes and TIICs.

Acknowledgements

None.

Authors’ contributions

KY and CQ contributed to the conception and design of the study; JV collected data and wrote the manuscript; KY performed the data analysis and constructed the figures and tables; KY and JV reviewed and revised the manuscript and were involved in the conception of the study. Additionally, JV was responsible for the organization, revision, and submission of this manuscript. All authors read and approved the final manuscript.

Availability of data and materials

The datasets analyzed was acquired from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/) and GEO database (https://www.ncbi.nlm.nih.gov/geo/).

Disclosure statement

The authors declare that they have no competing interests.

Ethics approval and consent to participate

Not applicable.

Supplementary material

Supplemental data for this article can be accessed here

Additional information

Funding

The authors have no funding to report.