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Published: 2026-03-31
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DOI: https://doi.org/10.52852/tcncyh.v200i3.4871
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Vol. 200 No. 3 (2026)
Section
Các bài báo
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Anh, N. T., Chi, D. T. K., Thảo, L. T. T., Diệu, Đỗ M. X., & Minh, Q. T. (2026). Evaluation of circulating hsa-miR-1203 as a diagnostic biomarker for prostate cancer using machine learning approaches. Journal of Medical Research, 200(3), 311-321. https://doi.org/10.52852/tcncyh.v200i3.4871

Evaluation of circulating hsa-miR-1203 as a diagnostic biomarker for prostate cancer using machine learning approaches

Nguyen Tu Anh, Duong Thi Kim Chi, Le Thi Thanh Thao, Do Mai Xuan Dieu, Quang Trong Minh

Main Article Content

Abstract

Prostate cancer is one of the most common malignancies among men, and the identification of reliable circulating biomarkers remains essential for improving diagnostic accuracy. This study aimed to evaluate the diagnostic potential of circulating hsa-miR-1203 in distinguishing prostate cancer patients from non-cancer controls using machine learning models. MicroRNA expression data were obtained from the GSE211692 dataset in the Gene Expression Omnibus, comprising 1,027 prostate cancer serum samples and 5,893 non-cancer samples. After preprocessing and log2 transformation, the dataset was divided into training (70%) and internal testing (30%) sets using stratified sampling. hsa-miR-1203 expression was significantly decreased in prostate cancer samples (log2FC = -3.77; p < 0.001). Four classification algorithms, including Extra Trees, Support Vector Machine (RBF kernel), AdaBoost, and Gaussian Naive Bayes, demonstrated excellent discriminative performance on the testing set, with area under the ROC curve (AUC) values approaching 0.98. These findings suggest that circulating hsa-miR-1203 may serve as a promising non-invasive biomarker to support prostate cancer diagnosis.

Article Details

Keywords

Prostate cancer, microRNA, hsa-miR-1203, machine learning, circulating biomarker, diagnosis

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