Machine learning and experimental analyses identified miRNA expression models associated with metastatic osteosarcoma

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dc.authorscopusidAli Zarrabi / 23483174100
dc.authorwosidAli Zarrabi / U-2602-2019
dc.contributor.authorAbedi, Samira
dc.contributor.authorBehmanesh, Ali
dc.contributor.authorMazhar, Farid Najd
dc.contributor.authorBagherifard, Abolfazl
dc.contributor.authorSami, Sam Hajialiloo
dc.contributor.authorHeidari, Negar
dc.contributor.authorHossein-Khannazer, Nikoo
dc.contributor.authorNamazifard, Saina
dc.contributor.authorArki, Mandana Kazem
dc.contributor.authorShams, Roshanak
dc.contributor.authorZarrabi, Ali
dc.contributor.authorVosough, Massoud
dc.date.accessioned2025-04-18T10:33:40Z
dc.date.available2025-04-18T10:33:40Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Biyomedikal Mühendisliği Bölümü
dc.description.abstractOsteosarcoma (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.
dc.description.sponsorshipBone and Joint Reconstruction Research Center, Department of Orthopedics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
dc.identifier.citationAbedi, S., Behmanesh, A., Mazhar, F. N., Bagherifard, A., Sami, S. H., Heidari, N., ... & Vosough, M. (2024). Machine learning and experimental analyses identified miRNA expression models associated with metastatic osteosarcoma. Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease, 1870(7), 167357.
dc.identifier.doi10.1016/j.bbadis.2024.167357
dc.identifier.endpage19
dc.identifier.issn0925-4439
dc.identifier.issn1879-260X
dc.identifier.issue7
dc.identifier.pmid39033966
dc.identifier.scopus2-s2.0-85199348291
dc.identifier.scopusqualityQ1
dc.identifier.startpage1
dc.identifier.urihttp://dx.doi.org/10.1016/j.bbadis.2024.167357
dc.identifier.urihttps://hdl.handle.net/20.500.12713/7126
dc.identifier.volume1870
dc.identifier.wosWOS:001280256600001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorZarrabi, Ali
dc.institutionauthoridAli Zarrabi / 0000-0003-0391-1769
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofBiochimica et biophysica acta molecular basis of disease
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectMetastatic Osteosarcoma
dc.subjectEarly Biomarkers
dc.subjectMachine Learning Algorithms
dc.subjectDifferentially Expressed miRNAs
dc.titleMachine learning and experimental analyses identified miRNA expression models associated with metastatic osteosarcoma
dc.typeArticle

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