Background: This study explores the association between growth arrest-specific 5 (GAS5) rs145204276, nuclear paraspeckle assembly transcript 1 (NEAT1) rs512715, and Maternally Expressed 3 (MEG3) rs4081134 polymorphisms and their impact on susceptibility to papillary thyroid carcinoma (PTC), considering differential expression of long noncoding RNAs (lncRNAs) in PTC.
Methods: A case-control study involving 125 papillary thyroid carcinoma (PTC) patients and 125 controls was conducted. Genotyping of polymorphisms was performed using tetra-primer amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) and PCR-restriction fragment length polymorphism (PCR-RFLP) methods.
Results: No significant association was found between the two groups regarding genotypes and allelic frequencies of GAS-5 145204276 and MEG3 rs4081134 polymorphisms. Genetic models also showed the same results. Regarding NEAT1 rs512715, The PTC group had more GC genotypes and over-dominant models of NEAT1 rs512715 than controls, while controls showed a higher frequency of recessive models.
Conclusion: GAS5 rs145204276 and MEG3 rs4081134 polymorphisms showed no significant association with papillary thyroid carcinoma (PTC) risk. In contrast, NEAT1 rs512715 exhibited a significant impact on PTC development.
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http://dx.doi.org/10.61186/rbmb.12.3.487 | DOI Listing |
Rep Biochem Mol Biol
October 2023
Department of Clinical Biochemistry, School of Medicine, Zahedan University of Medical Sciences, Zahedan, Iran.
Background: This study explores the association between growth arrest-specific 5 (GAS5) rs145204276, nuclear paraspeckle assembly transcript 1 (NEAT1) rs512715, and Maternally Expressed 3 (MEG3) rs4081134 polymorphisms and their impact on susceptibility to papillary thyroid carcinoma (PTC), considering differential expression of long noncoding RNAs (lncRNAs) in PTC.
Methods: A case-control study involving 125 papillary thyroid carcinoma (PTC) patients and 125 controls was conducted. Genotyping of polymorphisms was performed using tetra-primer amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) and PCR-restriction fragment length polymorphism (PCR-RFLP) methods.
Infect Drug Resist
May 2022
The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, People's Republic of China.
Background: Recent studies have shown that abnormal expression of lncRNA NEAT1 is associated with the progression of pulmonary tuberculosis (PTB). The aim of our study was to analyze the relationship between single nucleotide polymorphisms (SNPs) of gene and susceptibility to PTB.
Methods: Four SNPs (rs2239895, rs3741384, rs3825071, rs512715) in gene were genotyped in 479 patients with PTB and 476 controls by improved multiple ligase detection reaction (iMLDR) in a Chinese population.
Pathol Res Pract
December 2019
Department of Epidemiology, School of Public Health, China Medical University, Shenyang 110122, PR China; Key Laboratory of Cancer Etiology and Intervention, University of Liaoning Province, Shenyang 110122, PR China. Electronic address:
Background: Long non-coding RNA Nuclear Paraspeckle Assembly Transcript 1 (NEAT1) is a novel lncRNA localized specifically to nuclear paraspeckles. The study analyses the association between NEAT1 genetic polymorphisms and the susceptibility of lung cancer in a Chinese Northeast Population.
Methods: The NEAT1 rs512715 and rs2239895 genetic polymorphisms were genotyped in 462 lung cancer cases and 559 controls by a Real-Time Polymerase Chain Reaction (PCR) with the TaqMan discrimination assay.
Oncotarget
May 2017
Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), Ministry of Education, School of Life Sciences, Northwest University, Xi'an, Shaanxi 710069, China.
We explored the correlation between single nucleotide polymorphisms (SNPs) and susceptibility to cervical cancer (CC) in a Xinjiang Uygur population. Ten SNPs in eight miRNA-regulated genes were selected for analysis. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using unconditional logistic regression analysis.
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