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

OBJECTIVE

To 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.

METHODS

This 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).

RESULTS

Patients 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.

CONCLUSION

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