A novel adenosine signalling-based prognostic signature in gastric cancer and its association with cancer immune features and immunotherapy response.

Abstract

Reliable prognostic signatures that can reflect the intrinsic characteristics of gastric cancer (GC) are still rare. Here, we developed an adenosine-based prognostic signature and explored its association with the tumour immune in GC patients, aiming at confirming the prognostic value of adenosine-related genes and guiding the GC risk stratification and immunotherapeutic response prediction. We collected adenosine pathway-related genes from STRING websites and manual searching. We enrolled the The Cancer Genome Atlas cohort and four gene expression omnibus cohorts of GC for generating and validating the adenosine pathway-based signature using the Cox regression method. Gene expression in the signature was verified using polymerase chain reaction. We also performed gene set enrichment analysis, immune infiltration assessment and immunotherapy response prediction based on this signature. Our study resulted in a six-gene adenosine signature (GNAS, CXCR4, PPP1R1B, ADCY6, NT5E and NOS3) for risk stratification of GC prognosis, with the highest area under the receiver operating characteristic curve up to 0.767 for predicting 10-year overall survival (OS). In the training cohort, patients with signature-defined high risk had significantly poorer OS than those with low risk (p < .001). Multivariate analysis identified the signature as an independent prognostic factor (hazard ratio 2.863, 95% confidence interval [1.871-4.381], p < .001). These findings were confirmed in four independent cohorts. Expression detection showed that all signature genes were upregulated in both GC tissues and cell lines. Further analysis revealed that the signature-defined high-risk patients were characterised by immunosuppressive states and associated with a poor immunotherapy response. In conclusion, the adenosine pathway-based signature represents a promising risk stratification tool for GC in guiding individualised prognostication and immunotherapy.