Evidence map›Paper›PMID 40667557›Full record

ArticleAmerican journal of cancer research2025

Correlation and predictive modeling of serum exosomal miRNAs and serological biomarkers for lymph node metastasis in gastric cancer.

Quandong Li, Fang Nie, Dezhi Huang, Yongping Lin, Junjie Wan

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Article in American journal of cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Quandong LiNational Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Shenzhen 518116, China.
Fang NieChengdu Second People's Hospital Chengdu 610017, Sichuan, China.
Dezhi HuangNational Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Shenzhen 518116, China.
Yongping LinNational Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Shenzhen 518116, China.
Junjie WanNational Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Shenzhen 518116, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the predictive potential of serum exosomal microRNAs (miRNAs) and traditional serological biomarkers for lymph node metastasis in gastric cancer and to assess their applicability in clinical practice.

methodsThis retrospective study included 845 gastric cancer patients treated between January 2020 and December 2023, as the training cohort. Patients were stratified into lymph node-positive (n = 231) and lymph node-negative (n = 614) groups based on postoperative pathological evaluation. Serum exosomal miRNAs and conventional serological biomarkers were quantified and compared between groups. Multivariate logistic regression analysis was conducted to identify independent predictors. Model performance was validated using an independent test cohort comprising 277 patients (74 lymph node-positive, 203 lymph node-negative).

resultsPatients with lymph node metastasis exhibited significantly elevated expression of miR-21, miR-20a, miR-27a, and miR-106a. Serological markers that were significantly higher in the lymph node positive group included carbohydrate antigen 724, carcinoembryonic antigen, hepatocyte growth factor, vascular endothelial growth factor, interleukin-6, and circulating cell-free DNA (all P < 0.05). A combined predictive model integrating both miRNA and serological data demonstrated strong diagnostic performance, with an area under the curve of 0.816 in the training cohort and 0.817 in the validation cohort.

conclusionSerum exosomal miRNAs and serological biomarkers are significantly associated with lymph node metastasis in gastric cancer.

Indexed as

cancer prognosisGastric cancerlymph node metastasisprediction modelserological biomarkersserum exosome miRNA

Identifiers

PMID40667557
PMCPMC12256415

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