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A tumor microenvironment-based classification of gastric cancer for more effective diagnosis and treatment.

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Surgical oncology 📖 저널 OA 11.2% 2021: 0/4 OA 2022: 0/1 OA 2023: 0/1 OA 2024: 0/4 OA 2025: 2/33 OA 2026: 10/55 OA 2021~2026 2025 Vol.63() p. 102298
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Dima SO, Sorop A, Kitahara S, Setia N, Chivu-Economescu M, Matei L

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With approximately one million diagnosed cases and over 700,000 deaths recorded annually, gastric cancer (GC) is the third most common cause of cancer-related deaths worldwide.

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APA Dima SO, Sorop A, et al. (2025). A tumor microenvironment-based classification of gastric cancer for more effective diagnosis and treatment.. Surgical oncology, 63, 102298. https://doi.org/10.1016/j.suronc.2025.102298
MLA Dima SO, et al.. "A tumor microenvironment-based classification of gastric cancer for more effective diagnosis and treatment.." Surgical oncology, vol. 63, 2025, pp. 102298.
PMID 41033926 ↗

Abstract

With approximately one million diagnosed cases and over 700,000 deaths recorded annually, gastric cancer (GC) is the third most common cause of cancer-related deaths worldwide. GC is a heterogeneous tumor. Thus, optimal management requires biomarkers of prognosis, treatment selection, and treatment response. The Cancer Genome Atlas program sub-classified GC into molecular subtypes, providing a framework for treatment personalization using traditional chemotherapies or biologics. We hypothesized that integrating immunohistochemistry markers, tumor gene expression profiles, and serum cytokines would define biologically distinct subtypes of gastric cancer and associate with overall survival independently of clinicopathologic factors and provide incremental prognostic value beyond existing classifications. Here, we report a comprehensive study of GC vascular and immune markers associated with tumor microenvironment (TME) based on stage and molecular subtypes, and their correlation with outcomes. Using tissues and blood circulating biomarkers and a molecular classification, we identified tumor archetypes, which show that the TME evolves with the disease stage and is a determinant of prognosis. Moreover, our TME-based subtyping strategy allowed the identification of archetype-specific prognostic biomarkers such as CDH1-mutant GC and circulating IL-6 that provided information beyond and independent of TMN staging, MSI status, and consensus molecular subtyping. The results show that integrating molecular subtyping with TME-specific biomarkers could contribute to improved patient prognostication and may provide a basis for treatment stratification, including for contemporary anti-angiogenesis and immunotherapy approaches.

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