Title |
Association of MicroRNA Expression and BRAFV600E Mutation with Recurrence of Thyroid Cancer / |
Authors |
Pamedytyte, Daina ; Simanaviciene, Vaida ; Dauksiene, Dalia ; Leipute, Enrika ; Zvirbliene, Aurelija ; Sarauskas, Valdas ; Dauksa, Albertas ; Verkauskiene, Rasa ; Zilaitiene, Birute |
DOI |
10.3390/biom10040625 |
Full Text |
|
Is Part of |
Biomolecules.. Basel : MDPI. 2020, vol. 10, no. 4, p. 1-17.. ISSN 2218-273X |
Keywords [eng] |
BRAFV600E mutation ; biomarkers ; papillary thyroid carcinoma (PTC) ; miRNA ; recurrence |
Abstract [eng] |
Many miRNAs and cancer-related mutations have been proposed as promising molecular markers of papillary thyroid carcinoma (PTC). However, there are limited data on the correlation between miRNA expression, BRAFV600E mutation, and PTC recurrence. Therefore, to evaluate the potential of BRAFV600E mutation and five selected miRNAs (-146b, -222, -21, -221, -181b) in predicting PTC recurrence, these molecular markers were analyzed in 400 formalin-fixed, paraffin-embedded PTC tissue specimens. The expression levels of miRNAs were measured using qRT-PCR. It was demonstrated that expression levels of all analyzed miRNAs are significantly higher in recurrent PTC than in non-recurrent PTC (p < 0.05). Moreover, higher expression levels of miR-146b, miR-222, miR-21, and miR-221 were associated with other clinicopathologic features of PTC, such as tumor size and lymph node metastases at initial surgery (p < 0.05). No significant differences in the frequency of BRAFV600E mutation in recurrent PTC and non-recurrent PTC were determined. Our results suggest that miRNA expression profile differs in PTC that is prone to recurrence when compared to PTC that does not reoccur after the initial surgery while BRAFV600E mutation frequency does not reflect the PTC recurrence status. However, the prognostic value of the analyzed miRNAs is rather limited in individual cases as the pattern of miRNA expression is highly overlapping between recurrent and non-recurrent PTC. |
Published |
Basel : MDPI |
Type |
Journal article |
Language |
English |
Publication date |
2020 |
CC license |
|