Galectin-1 and peritoneal fibrosis: a novel predictor for peritoneal metastasis in gastric cancer

Current indicators lack the precision required to accurately predict the PM(peritoneal metastasis) of gastric cancer (GC). The accurate prediction of GC with PM and the implementation of targeted therapeutic strategies hold substantial clinical significance. This study aimed to evaluate the prognostic value of galectin-1 expression and peritoneal fibrosis in predicting PM in GC patients. Immunohistochemical and Masson's trichrome staining were conducted on GC tissues and peritoneal tissues from 125 patients who underwent radical gastrectomy. The correlations among galectin-1 expression in GC tissues, peritoneal fibrosis, and PM were analyzed. Univariate and multivariate regression analyses were performed, incorporating clinicopathological parameters, to assess predictors of PM of GC. Both univariate and multivariate analyses revealed significant correlations among pathological Tumor (pT) stage, galectin-1 expression, peritoneal fibrosis, and PM. Patients with pathological pT3-4 stage GC, who had high galectin-1 expression and who were positive for peritoneal fibrosis had a greater risk of PM after pairwise superposition. This study represents the first to systematically elucidate that galectin-1 expression in GC tissues and peritoneal fibrosis are independent predictors of the risk of PM in patients with GC. These two indicators coordinate with pT stage, and the combination of these two indicators increases their predictive accuracy.

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Publication Details

Journal
BMC Gastroenterology
Published
2026-02-14
DOI
https://doi.org/10.1186/s12876-026-04682-z
Primary Topic
Galectins and Cancer Biology
Type
article
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article

Galectin-1 and peritoneal fibrosis: a novel predictor for peritoneal metastasis in gastric cancer

Guiyuan Liu, Zhiyi Cheng, Xiaolan You, Qingzhu Ding et al.
BMC Gastroenterology
Galectins and Cancer Biology
article

Galectin-1 and peritoneal fibrosis: a novel predictor for peritoneal metastasis in gastric cancer

Guiyuan Liu, Zhiyi Cheng, Xiaolan You, Qingzhu Ding, Hao Wang, Chuanjiang Huang, Chungen Xing
article en

Abstract

Current indicators lack the precision required to accurately predict the PM(peritoneal metastasis) of gastric cancer (GC). The accurate prediction of GC with PM and the implementation of targeted therapeutic strategies hold substantial clinical significance. This study aimed to evaluate the prognostic value of galectin-1 expression and peritoneal fibrosis in predicting PM in GC patients. Immunohistochemical and Masson's trichrome staining were conducted on GC tissues and peritoneal tissues from 125 patients who underwent radical gastrectomy. The correlations among galectin-1 expression in GC tissues, peritoneal fibrosis, and PM were analyzed. Univariate and multivariate regression analyses were performed, incorporating clinicopathological parameters, to assess predictors of PM of GC. Both univariate and multivariate analyses revealed significant correlations among pathological Tumor (pT) stage, galectin-1 expression, peritoneal fibrosis, and PM. Patients with pathological pT3-4 stage GC, who had high galectin-1 expression and who were positive for peritoneal fibrosis had a greater risk of PM after pairwise superposition. This study represents the first to systematically elucidate that galectin-1 expression in GC tissues and peritoneal fibrosis are independent predictors of the risk of PM in patients with GC. These two indicators coordinate with pT stage, and the combination of these two indicators increases their predictive accuracy.

BMC GastroenterologyVol. 26(1)
Nantong University (CN), Soochow University (CN), The Affiliated Taizhou People's Hospital of Nanjing Medical University (CN), Second Affiliated Hospital of Soochow University (CN)
Good health and well-being
Openalex Percentile: Top 54%
Galectins and Cancer Biology
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Galectin-1 and peritoneal fibrosis: a novel predictor for peritoneal metastasis in gastric cancer — Guiyuan Liu, Zhiyi Cheng, et al. · BMC Gastroenterology (2026) | TGRS Research Map | TGRS