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miR-486-3p, miR-139-5p, and miR-21 as Biomarkers for the Detection of Oral Tongue Squamous Cell Carcinoma
Zujian Chen1, Tianwei Yu2, Robert J Cabay3
1Center for Molecular Biology of Oral Diseases, Department of Periodontics, College of Dentistry, University of Illinois at Chicago, Chicago, IL, USA.
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.
Insights
This study explored microRNA biomarkers for oral tongue squamous cell carcinoma (TSCC) detection using archived samples. A panel of three microRNAs (miR-486-3p, miR-139-5p, and miR-21) showed high accuracy in identifying TSCC.
Area of Science:
- Oncology
- Genetics
- Molecular Biology
Background:
- Oral tongue squamous cell carcinoma (TSCC) is characterized by genetic and epigenetic alterations, including dysregulated microRNAs.
- MicroRNA deregulation plays a role in the pathogenesis of TSCC.
Purpose of the Study:
- To evaluate the feasibility of microRNA profiling on archived TSCC specimens.
- To assess the diagnostic potential of microRNA biomarkers for TSCC detection.
Main Methods:
- MicroRNA profiling was conducted on 10 archived TSCC samples and adjacent normal tissues using TaqMan arrays.
- Differential expression analysis identified 12 microRNAs, with 8 validated in an independent set.
- A random forest classification model was developed using specific microRNAs.
Main Results:
- A panel of 12 differentially expressed microRNAs was identified between TSCC and normal tissues.
- A random forest model utilizing miR-486-3p, miR-139-5p, and miR-21 achieved 100% sensitivity and 86.7% specificity for TSCC detection.
- The overall error rate for the classification model was 6.7%.
Conclusions:
- Archived clinical specimens are suitable for microRNA biomarker discovery in TSCC.
- MicroRNA biomarkers, specifically miR-486-3p, miR-139-5p, and miR-21, demonstrate feasibility for TSCC detection.
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