Objective: Gastric cancer (GC) is a highly heterogeneous malignant carcinoma. This study aimed to conduct an exosome-based classification for assisting personalized therapy for GC. Methods: Based on the expression profiling of prognostic exosome-related genes, GC patients in The Cancer Genome Atlas (TCGA) cohort were classified using the unsupervised consensus clustering approach, and the reproducibility of this classification was confirmed in the GSE84437 cohort. An exosome-based gene signature was developed via Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. Immunological features, responses to immune checkpoint inhibitors, and genetic alterations were evaluated via computational methods. Results: Two exosome-relevant phenotypes (A and B) were clustered, and this classification was independent of immune subtypes and TCGA subtypes. Exosome-relevant phenotype B had a poorer prognosis and an inflamed tumor microenvironment (TME) relative to phenotype A. Patients with phenotype B presented higher responses to the anti-CTLA4 inhibitor. Moreover, phenotype B occurred at a higher frequency of genetic mutation than phenotype A. The exosome-based gene signature (GPX3, RGS2, MATN3, SLC7A2, and SNCG) could independently and accurately predict GC prognosis, which was linked to stromal activation and immunosuppression. Conclusion: Our findings offer a conceptual frame to further comprehend the roles of exosomes in immune escape mechanisms and genomic alterations of GC. More work is required to evaluate the reference value of exosome-relevant phenotypes for designing immunotherapeutic regimens.
Keywords: exosomes; gastric cancer; immune escape; immunotherapy; tumor microenvironment.
Copyright © 2022 Lin, Huang, Cai, Chen, Feng, Gao, Zheng, Fan, Qiu, Zhuang and Feng.