OBJECTIVES: Papillary thyroid cancer (PTC) is the most common subtype of thyroid cancer, which accounts for 80-90% of all thyroid cancer cases. Though the pathological mechanism hasn't been fully understood, it is reported that both environmental and genetic factor may contribute to the PTC susceptibility. MicroRNAs (miRNAs) are small non-coding RNA molecules which function as the suppressors to participate in a variety of biological processes. Accumulating evidence suggests that polymorphisms of miRNAs were associated with the tumorigenesis of various cancers, including PTC. In this article, we focus on the association between four common microRNA polymorphisms (miR-146a, miR-608, miR-933, and miR-149) and PTC risk in a Han Chinese population. METHODS: In this case-control study, we recruited 1,398 participants in total, including 369 PTC patients, 278 patients with thyroid benign nodules (BN) and 751 normal controls. The miRNAs polymorphisms were genotyped and analyzed by using MALDI-TOF mass spectrometry. The odd ratios and their 95% confidence interval (95% CI) were calculated to evaluate the association between miRNAs polymorphisms and PTC risk. Furthermore, a meta-analysis based on previous studies was conducted to comprehensively assess the diagnostic performance of miR-146a in the PTC diagnosis. RESULTS: The miR-146a polymorphisms were shown to be significantly correlated with elevated risk of PTC under the heterozygous, homozygous, dominant and allelic models by comparing the genotype distribution between PTC cases and healthy controls, as well as between PTC cases and BN cases. However, the result of meta-analysis showed no significant association between miR-146a polymorphisms and PTC risk. CONCLUSIONS: Our study indicated that the miR-146a polymorphism was significantly associated with PTC risk. In contrast, meta-analysis revealed no evidence of association between miR-146a variants and PTC risk. Further studies are required to elucidate the role of miR-146a in the etiology of PTC.
OBJECTIVES:Papillary thyroid cancer (PTC) is the most common subtype of thyroid cancer, which accounts for 80-90% of all thyroid cancer cases. Though the pathological mechanism hasn't been fully understood, it is reported that both environmental and genetic factor may contribute to the PTC susceptibility. MicroRNAs (miRNAs) are small non-coding RNA molecules which function as the suppressors to participate in a variety of biological processes. Accumulating evidence suggests that polymorphisms of miRNAs were associated with the tumorigenesis of various cancers, including PTC. In this article, we focus on the association between four common microRNA polymorphisms (miR-146a, miR-608, miR-933, and miR-149) and PTC risk in a Han Chinese population. METHODS: In this case-control study, we recruited 1,398 participants in total, including 369 PTC patients, 278 patients with thyroid benign nodules (BN) and 751 normal controls. The miRNAs polymorphisms were genotyped and analyzed by using MALDI-TOF mass spectrometry. The odd ratios and their 95% confidence interval (95% CI) were calculated to evaluate the association between miRNAs polymorphisms and PTC risk. Furthermore, a meta-analysis based on previous studies was conducted to comprehensively assess the diagnostic performance of miR-146a in the PTC diagnosis. RESULTS: The miR-146a polymorphisms were shown to be significantly correlated with elevated risk of PTC under the heterozygous, homozygous, dominant and allelic models by comparing the genotype distribution between PTC cases and healthy controls, as well as between PTC cases and BN cases. However, the result of meta-analysis showed no significant association between miR-146a polymorphisms and PTC risk. CONCLUSIONS: Our study indicated that the miR-146a polymorphism was significantly associated with PTC risk. In contrast, meta-analysis revealed no evidence of association between miR-146a variants and PTC risk. Further studies are required to elucidate the role of miR-146a in the etiology of PTC.
Authors: Jacques Ferlay; Isabelle Soerjomataram; Rajesh Dikshit; Sultan Eser; Colin Mathers; Marise Rebelo; Donald Maxwell Parkin; David Forman; Freddie Bray Journal: Int J Cancer Date: 2014-10-09 Impact factor: 7.396
Authors: Angela M Liu; Zhi Xu; Felix H Shek; Kwong-Fai Wong; Nikki P Lee; Ronnie T Poon; Jinfei Chen; John M Luk Journal: PLoS One Date: 2014-01-23 Impact factor: 3.240
Authors: T P McVeigh; R J Mulligan; U M McVeigh; P W Owens; N Miller; M Bell; F Sebag; C Guerin; D S Quill; J B Weidhaas; M J Kerin; A J Lowery Journal: Endocr Connect Date: 2017-09-12 Impact factor: 3.335