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Author Notes:

CORRESPONDENCE: xfzhou@uic.edu

Conceived and designed the experiments: RJC, YJ, XL, YD, XZ.

Performed experiments: ZC, YJ, IM. Analyzed the data: TY, LH, YD, XZ.

Wrote the first draft of the manuscript: TY, RJC, YD, XZ.

Contributed to the writing of the manuscript: ZC, YJ, IM, XL, LH.

Agree with manuscript results and conclusions: ZC, TY, RJC, YJ, IM, XL, LH, YD, XZ.

Made critical revisions and approved final version: TY, RJC, YD.

All authors reviewed and approved of the final manuscript.

The authors confirm that the funder had no influence over the study design, content of the article, or selection of this journal.

Authors disclose no potential conflicts of interest.

Subjects:

Research Funding:

This research was made possible, in part, by NIH PHS grants (CA139596 and CA171436) and the Lilly USA Research Award in Cancer Prevention and Early Detection funded by Lilly USA, LLC and awarded by Prevent Cancer Foundation to XZ. YJ is supported by a T32 training grant (DE018381) from NIH/NIDCR.

IM is supported by a scholarship under the International Research Support Initiative Program from Higher Education Commission of Pakistan.

Keywords:

  • biomarker
  • formalin-fixed paraffin-embedded
  • miR-139-5p
  • miR-21
  • miR-486-3p
  • microRNA
  • tongue squamous cell carcinoma

miR-486-3p, miR-139-5p, and miR-21 as Biomarkers for the Detection of Oral Tongue Squamous Cell Carcinoma.

Tools:

Journal Title:

Biomarkers in Cancer

Volume:

Volume 9

Publisher:

, Pages 1-8

Type of Work:

Article | Final Publisher PDF

Abstract:

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.

Copyright information:

© 2017 the author(s), publisher and licensee Libertas Academica Ltd.

This is an Open Access work distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License (http://creativecommons.org/licenses/by-nc/3.0/).

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