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Machine learning and experimental analyses identified miRNA expression models associated with metastatic osteosarcoma.
- Source :
-
Biochimica et biophysica acta. Molecular basis of disease [Biochim Biophys Acta Mol Basis Dis] 2024 Oct; Vol. 1870 (7), pp. 167357. Date of Electronic Publication: 2024 Jul 20. - Publication Year :
- 2024
-
Abstract
- Osteosarcoma (OS), as the most common primary bone cancer, has a high invasiveness and metastatic potential, therefore, it has a poor prognosis. This study identified early diagnostic biomarkers using miRNA expression profiles associated with osteosarcoma metastasis. In the first step, we used RNA-seq and online microarray data from osteosarcoma tissues and cell lines to identify differentially expressed miRNAs. Then, using seven feature selection algorithms for ranking, the first-ranked miRNAs were selected as input for five machine learning systems. Using network analysis and machine learning algorithms, we developed new diagnostic models that successfully differentiated metastatic osteosarcoma from non-metastatic samples based on newly discovered miRNA signatures. The results showed that miR-34c-3p and miR-154-3p act as the most promising models in the diagnosis of metastatic osteosarcoma. Validation for this model by RT-qPCR in benign tissue and osteosarcoma biopsies confirmed the lower expression of miR-34c-3p and miR-154-3p in OS samples. In addition, a direct correlation between miR-34c-3p expression, miR-154-3p expression and tumor grade was discovered. The combined values of miR-34c-3p and miR-154-3p showed 90 % diagnostic power (AUC = 0.90) for osteosarcoma samples and 85 % (AUC = 0.85) for metastatic osteosarcoma. Adhesion junction and focal adhesion pathways, as well as epithelial-to-mesenchymal transition (EMT) GO terms, were identified as the most significant KEGG and GO terms for the top miRNAs. The findings of this study highlight the potential use of novel miRNA expression signatures for early detection of metastatic osteosarcoma. These findings may help in determining therapeutic approaches with a quantitative and faster method of metastasis detection and also be used in the development of targeted molecular therapy for this aggressive cancer. Further research is needed to confirm the clinical utility of miR-34c-3p and miR-154-3p as diagnostic biomarkers for metastatic osteosarcoma.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 Elsevier B.V. All rights reserved.)
- Subjects :
- Humans
Biomarkers, Tumor genetics
Biomarkers, Tumor metabolism
Neoplasm Metastasis
Cell Line, Tumor
Male
Female
Gene Expression Profiling
Epithelial-Mesenchymal Transition genetics
Osteosarcoma genetics
Osteosarcoma pathology
Osteosarcoma metabolism
MicroRNAs genetics
MicroRNAs metabolism
Machine Learning
Bone Neoplasms genetics
Bone Neoplasms pathology
Bone Neoplasms metabolism
Gene Expression Regulation, Neoplastic
Subjects
Details
- Language :
- English
- ISSN :
- 1879-260X
- Volume :
- 1870
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- Biochimica et biophysica acta. Molecular basis of disease
- Publication Type :
- Academic Journal
- Accession number :
- 39033966
- Full Text :
- https://doi.org/10.1016/j.bbadis.2024.167357