Identification and Validation of a Tumour Microenvironment-Based Immune Molecular Subgroups for Gastric Cancer: Immunotherapeutic Implications

Abstract

Background: Immunotherapy could trigger durable response in advanced gastric cancer, but it only benefits a minority of patients. Aims: To propose a robust molecular classification of gastric cancer microenvironment to identify ideal candidates for tailoring effective immunotherapy. Methods: A training cohort of 375 gastric cancer samples with RNAsequencing data were analysed. We virtually microdissected tumour, stromal, and immune cell gene expression patterns employing a nonnegative matrix factorization algorithm. These expression patterns were annotated using immune- and stromal-related gene signatures. Validation of immunogenomic classification was performed across six microarray datasets of 1,406 samples. Results: We found approximately half of gastric cancer samples to have higher immune cell infiltrates, PD-L1 expression, markers of cytolytic activity, and fewer copy number aberrations (all P < 0.05). We termed this group of tumours the Immune Class, which incorporated two components, namely Immune Activation and Immunosuppressive Subtype, according to immunosuppressive or activated microenvironment. Immune Activation Subtype was associated with improved survival in multivariate survival analysis and shared similar genomic characteristics with responders of anti-PD-1 therapy. Immunosuppressive Subtype featured high immune infiltration, stromal enrichment, and transforming growth factor (TGF)-β signalling pathway activation, which might be suitable for antiPD-L1 and anti-TGF-β combined therapy. Conclusions: We proposed and independently validated three reproducible immune molecular subtypes of gastric cancer, which may provide implications for patient selection of immunotherapy. Funding Statement: This work was supported by grants from the Incubating Program for Clinical Research and Innovation of Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University (Grant No. PYMDT-001), Science and Technology Commission of Shanghai Municipality (Grant No. 16441906903), Three-year action plan for Shin Kang of Shanghai (16CR4005A). Declaration of Interests: The authors declare no potential conflicts of interest. Ethics Approval Statement: Not required.