ArticleFrontiers in cell and developmental biology2026
Therapeutic vulnerability shaped by the microenvironment: multi-omics and AI biomarkers for precision surgical planning in gastrointestinal tumors.
Article in Frontiers in cell and developmental biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
- Spatial immune ecology of immunotherapy resistance in gastric and gastroesophageal junction adenocarcinoma.Frontiers in oncology · 2026Review
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Abstract
Background: Therapeutic vulnerability in gastric cancer is profoundly influenced by the tumor microenvironment (TME), yet reliable and clinically actionable preoperative indicators remain insufficient. Methods: We developed and validated an artificial intelligence-driven multi-omics TME score (DLRS/TMEscore) by integrating CT-derived imaging features with transcriptomic, immunohistochemical, and molecular profiling. The score was evaluated for its associations with survival outcomes, benefit from adjuvant chemotherapy, and response to anti-PD-1 therapy. Results: The DLRS/TMEscore reproducibly stratified disease-free and overall survival across independent cohorts. Patients in the low-risk subgroup derived substantial benefit from adjuvant chemotherapy, whereas those in the high-risk subgroup demonstrated attenuated benefit. Among individuals receiving immunotherapy, the score enriched objective responders and predicted more durable clinical outcomes, outperforming established biomarkers including PD-L1 combined positive score (CPS) and microsatellite instability (MSI). In addition, DLRS/TMEscore correlated with multiple surgical parameters, such as operative complexity, resection margin status, nodal involvement, and postoperative recovery, indicating relevance in perioperative risk assessment. Conclusion: This AI-enabled multi-omics framework offers a robust and interpretable approach for characterizing microenvironment-defined therapeutic vulnerability, supporting preoperative risk stratification and individualized systemic treatment strategies in gastric cancer.
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