Related Experiment Video
Updated: May 30, 2025

Elastic Staining on Paraffin-embedded Slides of pT3N0M0 Gastric Cancer Tissue
Published on: May 1, 2019
Tumor-Stroma Ratio is a Critical Indicator of Peritoneal Metastasis in Gastric Cancer
Lin Zhong1, Hongyun Huang2, Dong Hou1
1Department of Gastrointestinal Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, 510120, People's Republic of China.
Objective:
This study aims to investigate the correlation between the tumor-stroma ratio (TSR) and peritoneal metastasis (PM) in gastric cancer (GC) and constructs a diagnostic model based on preoperative examination data.
Methods:
To determine the feasibility of obtaining TSR in GC patients through preoperative examinations, the consistency of TSR between endoscopic biopsy tissues and postoperative histopathological tissues was evaluated. Additionally, the correlation between TSR and PM in GC was analyzed using Gene Expression Omnibus (GEO) datasets. To validate TSR's clinical potential in diagnosing PM, 640 GC patients from two medical centers were enrolled. A training cohort of 330 patients evaluated TSR and synchronous PM correlation, and a validation cohort of 310 patients was used. An additional cohort of 510 patients was established to investigate TSR and metachronous PM. A diagnostic model based on preoperative data was developed and a nomogram constructed.
Results:
The TSR shows good consistency between endoscopic biopsy tissues and postoperative histopathological tissues. A significant correlation between TSR and PM was observed. The TSR-based model, combined with CA125, CA724 and Borrmann type, exhibited strong diagnostic effectiveness and considerable predictive efficacy, with an Area Under the Curve (AUC) of 0.85 in the training cohort, 0.73 in the external validation cohort, and 0.72 in the metachronous PM cohort.
Conclusion:
The TSR emerges as a crucial marker for PM in GC, with the developed model, based on TSR and preoperative examination data, demonstrating substantial diagnostic and predictive capabilities.

