A Signature-Based Classification of Gastric Cancer That Stratifies Tumor Immunity and Predicts Responses to PD-1 Inhibitors.

Abstract

Gastric cancer is a leading cause of cancer-related deaths with considerable heterogeneity among patients. Appropriate classifications are essential for prognosis prediction and individualized treatment. Although immunotherapy showed potential efficacy in a portion of patients with gastric cancer, few studies have tried to classify gastric cancer specifically based on immune signatures. In this study, we established a 3-subtype cluster with low (CLIM), medium (CMIM), and high (CHIM) enrichment of immune signatures based on immunogenomic profiling. We validated the classification in multiple independent datasets. The CHIM subtype exhibited a relatively better prognosis and showed features of "hot tumors", including low tumor purity, high stromal components, overexpression of immune checkpoint molecules, and enriched tumor-infiltrated immune cells (activated T cells and macrophages). In addition, CHIM tumors were also characterized by frequent ARID1A mutation, rare TP53 mutation, hypermethylation status, and altered protein expression (HER2, β-catenin, Cyclin E1, PREX1, LCK, PD-L1, Transglutaminase, and cleaved Caspase 7). By Gene Set Variation Analysis, "TGFβ signaling pathway" and "GAP junction" were enriched in CLIM tumors and inversely correlated with CD8+ and CD4+ T cell infiltration. Of note, the CHIM patients showed a higher response rate to immunotherapy (44.4% vs. 11.1% and 16.7%) and a more prolonged progression-free survival (4.83 vs. 1.86 and 2.75 months) than CMIM and CLIM patients in a microsatellite-independent manner. In conclusion, the new immune signature-based subtypes have potential therapeutic and prognostic implications for gastric cancer management, especially immunotherapy.

• Authors: Song Li, Jing Gao, Qian Xu, Xue Zhang, Miao Huang, Xin Dai, Kai Huang, Lian Liu
• Journal: Frontiers in immunology (Front Immunol) Vol. 12 Pg. 693314 ( 2021) ISSN: 1664-3224 [Electronic] Switzerland
• PMID: 34177954 (Publication Type: Journal Article, Meta-Analysis, Research Support, Non-U.S. Gov't, Validation Study)
• Copyright: Copyright © 2021 Li, Gao, Xu, Zhang, Huang, Dai, Huang and Liu.

Chemical References

• Biomarkers, Tumor
• Immune Checkpoint Inhibitors
• PDCD1 protein, human
• Programmed Cell Death 1 Receptor

Topics

• Biomarkers, Tumor (genetics)
• Clinical Decision-Making
• Databases, Genetic
• Feasibility Studies
• Gene Expression Profiling
• Gene Regulatory Networks
• Humans
• Immune Checkpoint Inhibitors (therapeutic use)
• Lymphocytes, Tumor-Infiltrating (immunology)
• Predictive Value of Tests
• Programmed Cell Death 1 Receptor (antagonists & inhibitors, genetics)
• Protein Interaction Maps
• Retrospective Studies
• Stomach Neoplasms (drug therapy, genetics, immunology, mortality)
• Transcriptome
• Treatment Outcome
• Tumor Microenvironment (immunology)