An antigen processing and presentation signature for prognostic evaluation and immunotherapy selection in advanced gastric cancer - Wang, Ke-wei; Wang, Mei-dan; Li, Zi-xi; Hu, Ben-shun; Wu, Jun-jie; Yuan, Zheng-dong; Wu, Xiao-long; Yuan, Qin-fang; Yuan, Feng-lai (Frontiers in Immunology, 2022)
How antigen presentation-related genes affected the immunotherapy response and whether they could predict the clinical outcomes of the immune checkpoint inhibitor (ICI) in aGC remain largely unknown. This study proposed a new signature based on genes associated with antigen processing and presentation (APscore) to predict prognosis and response to ICIs in aGC patients. The APscore constructed by principal component analysis algorithms was an effective predictive biomarker of the response to ICIs in the Kim cohort and 467 aGC patient. The APscore also was a prognostic biomarker in 467 aGC patients. Inhibitory immunity, decreased tumor mutation burden (TMB) and low stromal scores were observed in the high APscore group while activation of immunity, increased TMB, and high stromal scores were observed in the low APscore group. Next, we evaluated the value of several hub genes in predicting the prognosis and response to ICIs in aGC patients, and verified them using immunogenic, transcriptomic, genomic, and multi-omics methods. Lastly, a predictive model built successfully discriminated patients with vs. without immunotherapy response and predicted the survival of aGC patients. The APscore was a new biomarker for identifying high-risk aGC patients and patients with responses to ICIs. Exploration of the APscore and hub genes in multi-omics GC data may guide treatment decisions.