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| Status |
Public on Oct 07, 2014 |
| Title |
A two miRNA classifier differentiates follicular thyroid carcinomas from follicular thyroid adenomas |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by array
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| Summary |
The inherent diagnostic limitations of thyroid fine needle aspiration (FNA), especially in the “indeterminate” category, can be partially overcome by molecular analyses. We aimed at the identification of miRNAs that could be used to improve the discrimination of indeterminate FNAs. miRNA expression profiling was performed for 17 follicular carcinomas (FTCs) and 8 follicular adenomas (FAs). The microarray results underwent cross-comparison using three additional microarray data sets. Candidate miRNAs were validated by qPCR in an independent set of 32 FTCs and 46 FAs. Sixty-eight differentially expressed miRNAs were identified. Thirteen miRNAs could be confirmed by cross comparison. A two-miRNA-classifier was established improving the diagnostic applicability and resulted in a sensitivity of 82% and a specificity of 49%. We present a classifier that has the potential to be successfully evaluated in cytology material for its capability to discriminate (mutation negative) indeterminate cytologies and thereby improving the pre-surgical diagnostics of thyroid nodules.
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| Overall design |
miRNA expression profiling was performed for 17 follicular carcinomas (FTCs) and 8 follicular adenomas (FAs). All samples are independent, coming from different patients.
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| Contributor(s) |
Stokowy T, Eszlinger M, Paschke R |
| Citation missing |
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| |
| Submission date |
Oct 03, 2014 |
| Last update date |
Feb 18, 2019 |
| Contact name |
Tomasz Stokowy |
| E-mail(s) |
tomasz.stokowy@uib.no
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| Organization name |
University of Bergen
|
| Department |
IT Division
|
| Lab |
Scientific Computing
|
| Street address |
Nygardsgaten 5
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| City |
Bergen |
| ZIP/Postal code |
5020 |
| Country |
Norway |
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| Platforms (1) |
| GPL8179 |
Illumina Human v2 MicroRNA expression beadchip |
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| Samples (25)
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| Relations |
| BioProject |
PRJNA263179 |
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