miR-1287-5p as a Biomarker for Predicting Lymph Node Metastasis in Gastric Cancer Patients

Area of Science:

• Oncology
• Genetics
• Biostatistics

Background:

• Gastric cancer (GC) is a significant global health concern.
• Lymph node metastasis (LNM) is a critical prognostic factor in GC.
• Accurate prediction of LNM is essential for guiding treatment decisions.

Purpose of the Study:

• To develop and validate a predictive model for lymph node metastasis (LNM) in gastric cancer (GC) patients.
• To identify novel biomarkers for LNM prediction in GC.
• To construct a nomogram for clinical application in GC management.

Main Methods:

• Utilized data from the TCGA database and the Second Hospital of Hebei Medical University.
• Employed logistic regression to identify risk factors for LNM in GC.
• Developed a nomogram incorporating independent predictors of LNM.
• Assessed model performance using Area Under the Curve (AUC) and calibration curves.

Main Results:

• Race, histologic grade, advanced pathologic stage (T3 or higher), and miR-1287-5p were independently associated with LNM in GC.
• The constructed nomogram demonstrated good predictive performance with C-index values of 0.847 (training) and 0.755 (supportive cohort).
• miR-1287-5p emerged as a novel predictor for LNM in GC patients.

Conclusions:

• A robust nomogram model for predicting LNM in GC patients was successfully established.
• The nomogram, incorporating miR-1287-5p, offers a valuable tool for assessing LNM risk in GC.
• This study highlights the potential of miR-1287-5p as a biomarker for GC metastasis.