Association between gene polymorphism rs11614913 in microRNA196a2, with Non-small cell lung cancer risk in the population of southern Iran

• Main Authors: Parvin Pishva, Mohammad Tahmaseb, Abbass Ghaderi
• Format: Article
• Language: English
• Published: Kharazmi University 2016-06-01
• Series: یافته‌های نوین در علوم زیستی
• Subjects: micro RNA; non-small cell lung cancer; SNP
• Online Access: http://nbr.khu.ac.ir/browse.php?a_code=A-10-35-1&slc_lang=en&sid=1

Lung cancer is the most common cause of death worldwide and result in 1.4 million deaths per year. Lung cancer is the fifth most common cancer in Iran, with rates of 4.7 to 9.2 per 100 thousand populations. Despite the low incidence, survival is not promising. Identification of biological markers and their application in diagnosis of cancer could lead to early diagnosis and therefore longer survival rate in patients. In this study, we evaluated the association of SNP rs11614913 in mir-196a2 with risk of non-small cell lung cancer (NSCLC) in population of southern Iran. SNP rs11614913 in miR-196a2 was assayed in 95 lung cancer patients and 100 controls. Polymorphism was determined by RFLP-PCR. The PCR product was digested with TaaI (5’ ACN^GT) which generated two bands (187bp and 196bp) in TT, three bands (187bp, 196bp and 383bp) in TC and one bandn(383bp) in CC individuals. Analysis of electrophoretic pattern of digestion products revealed that the frequencies of C allele for SNP rs11614913 miR-196a2 were 0.695 in patients and 0.76 in controls. As a result, the genotype frequencies of TT, TC and CC were 0.074, 0.463 and 0.463 in patients and 0.06, 0.36 and 0.58 in controls. The statistical analysis indicates the presence of Hardy-Weinberg equilibrium between the two alleles of the gene in the population studied (p>0.05). Based on the results in this study, no significant association between SNP rs11614913 and susceptibility to NSCLC was found. However, male participants who possess TC/TT genotypes showed high risk for NSCLC compared to those possessed CC genotypes (recessive genetic model).