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miR-486-3p, miR-139-5p, and miR-21 as Biomarkers for the Detection of Oral Tongue Squamous Cell Carcinoma.
Chen, Zujian; Yu, Tianwei; Cabay, Robert J; Jin, Yi; Mahjabeen, Ishrat; Luan, Xianghong; Huang, Lei; Dai, Yang; Zhou, Xiaofeng.
Afiliación
  • Chen Z; Center for Molecular Biology of Oral Diseases, Department of Periodontics, College of Dentistry, University of Illinois at Chicago, Chicago, IL, USA.
  • Yu T; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
  • Cabay RJ; Department of Pathology, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA.
  • Jin Y; Center for Molecular Biology of Oral Diseases, Department of Periodontics, College of Dentistry, University of Illinois at Chicago, Chicago, IL, USA.
  • Mahjabeen I; Center for Molecular Biology of Oral Diseases, Department of Periodontics, College of Dentistry, University of Illinois at Chicago, Chicago, IL, USA.
  • Luan X; Department of Biosciences, COMSATS Institute of Information and Technology, Islamabad, Pakistan.
  • Huang L; Department of Oral Biology, College of Dentistry, University of Illinois at Chicago, Chicago, IL, USA.
  • Dai Y; Department of Bioengineering, College of Engineering, University of Illinois at Chicago, Chicago, IL, USA.
  • Zhou X; Department of Bioengineering, College of Engineering, University of Illinois at Chicago, Chicago, IL, USA.
Biomark Cancer ; 9: 1179299X1700900001, 2017.
Article en En | MEDLINE | ID: mdl-35237086
Oral tongue squamous cell carcinoma (TSCC) is a complex disease with extensive genetic and epigenetic defects, including microRNA deregulation. The aims of the present study were to test the feasibility of performing the microRNA profiling analysis on archived TSCC specimens and to assess the potential diagnostic utility of the identified microRNA biomarkers for the detection of TSCC. TaqMan array-based microRNA profiling analysis was performed on 10 archived TSCC samples and their matching normal tissues. A panel of 12 differentially expressed microRNAs was identified. Eight of these differentially expressed microRNAs were validated in an independent sample set. A random forest (RF) classification model was built with miR-486-3p, miR-139-5p, and miR-21, and it was able to detect TSCC with a sensitivity of 100% and a specificity of 86.7% (overall error rate = 6.7%). As such, this study demonstrated the utility of the archived clinical specimens for microRNA biomarker discovery. The feasibility of using microRNA biomarkers (miR-486-3p, miR-139-5p, and miR-21) for the detection of TSCC was confirmed.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Biomark Cancer Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
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XML
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Biomark Cancer Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos