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This is a Quantitative Study study.

October 9, 2025Open Access

Machine Learning-Driven Discovery of Biomarkers in Gastric Cancer: A Focus on DPT, FBP2, ADH7, INHBA, and GPR155

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Comprehensive bioinformatics approach reveals five potential biomarkers in gastric cancer, suggesting new diagnostic avenues.

Five genes—DPT, FBP2, ADH7, INHBA, and GPR155—are identified as potential biomarkers for gastric cancer using data-driven methods.
A support vector machine showed superior performance, with clear contributions from identified biomarkers enhancing predictive accuracy.
Analysis techniques like LASSO and SHAP clarified the functional roles of these biomarkers in gastric cancer pathology.
Identified proteins may provide critical insights into immune cell behavior and patient prognosis, enhancing treatment strategies.

Zhao et al. (2025) studied this question.

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