Document Type : Research Articles
Department of Microbiology, College of Medicine, Imam Abdulrahman Bin Faisal University (IAU), Dammam, Saudi Arabia.
Department of Pathology, College of Medicine, Imam Abdulrahman Bin Faisal University (IAU), Dammam, Saudi Arabia.
Breast Division, Department of Surgery, College of Medicine, Imam Abdulrahman Bin Faisal University (IAU), Dammam, Saudi Arabia.
Background: Genetic mutations and polymorphisms play an important role in the transformation of primary cells to malignant cells as it may lead to disturbance of vital pathways regulating cell cycle, DNA damage repair, and apoptosis. In this study, we genotyped single nucleotide polymorphisms (SNPs) which were predicted to affect certain pathways and to increase the risk of breast cancer. Methods: The study included 81 Saudi breast cancer patients and 100 matching healthy controls from the Eastern Province in Saudi Arabia. The following SNPs (rs3168891, rs2899849, rs2230394, rs2229714) were then genotyped by TaqMan genotyping assay and the allele and genotype distribution was compared. Results: The minor allele frequency of the following SNPs (rs3168891, rs2899849, rs2230394, rs2229714) was T=0.17, A=0.28, A=0.22, and G=0.16 respectively. The G allele of the SNP rs3168891 was significantly associated with increased breast cancer risk (P = 0.00001) while the T allele of the same locus was associated with reduced risk of breast cancer in both heterozygous and homozygous states. The T allele of SNP rs2229714 which is located in the RPS6KA1 gene was also significantly associated with the increased risk of breast cancer. However, the rs2899849 SNP located in the Integrin beta-1 (ITGB1) gene was not associated with the increased risk of breast cancer in our study population. Haplotype analysis revealed the presence of three risk haplotypes that increases the risk of breast cancer (TGGT, TGTA, GATA). Conclusion: We showed that three, previously untested, SNPs are associated with increased risk of breast cancer in our population. This may be added to the list of factors involved in breast cancer risk assessment studies. The benefit and the utility of the in-silico prediction of disease risk factors and their genetic association had been demonstrated in this study, yet the predicted risk alleles have to be tested in clinical studies.