RESUMO
BACKGROUND: microRNAs (miRNAs) are small, noncoding RNA molecules, functioning either as oncogenes or tumor suppressor genes. SNPs in miRNAs might modify the expression of genes associated with miRNAs, enhancing susceptibility to breast cancer. Both miRNA-146a (rs2910164) and miRNA-196a (rs11614913) are identified and significantly associated with breast cancer risk in several ethnicities, but remains unexplored in Khyber Pakhtunkhwa population of Pakistan. METHODS: This study was aimed to check the relation of selected SNPs with breast cancer risk. The research cohort included 100 breast cancer patients and 100 healthy controls. All the participants were subjected for DNA extraction followed by T-ARMS PCR and gel electrophoresis. RESULTS: The results revealed a strong association between risk allele (G) of miRNA-146a and increased risk of breast cancer (OR = 2.04, P = 0.0006). Similarly, heterozygous and mutant genotypes also indicated high risk and significant association with breast cancer risk (CG; OR = 0.51, 9 P = 0.0001) (GG; OR = 3.76, P = 0.04). However, risk allele (T) of miRNA-196a (rs11614913) failed to exhibit significant association with breast cancer risk (OR = 0.92 P = 0.68). Similarly, the heterozygous and mutant genotype did not show significant association with breast cancer risk (CT; OR = 0.52, P = 0.125 (TT; OR = 0.88, P = 0.84). Furthermore, miRNA-146a (rs2910164) and miRNA-196a (rs11614913) polymorphisms exhibited non-significant associations with family history (P = 0.34, P = 0.77), PR status (P = 0.310, P = 0.397), ER status (P = 0.992, P = 0.981), nodal status (P = 0.86, P = 0.90), and menstrual status (P = 0.97, P = 0.09). Notably, miRNA-196a showed a significant association with the metastasis group (P = 0.010) and cancer stages (P = 0.047). CONCLUSIONS: In conclusion, this study highlights the association of miRNA-146a (rs2910164) polymorphism with breast cancer risk but suggested non-significant association of miRNA-196a (rs11614913) with breast cancer risk. However, these findings need to be confirmed through larger data set for more accurate result.
