Detection of Breast Cancer Related Gene Polymorphisms By a New Modified PCR-RAPD-PCR Technique
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Abstract
Breast cancer is one of the most aggressive cancers with high estimated mortality worldwide; many studies around the world have involved polymorphisms in drug resistance genes, tumor suppressor genes, estrogen receptor genes, and regulatory genes related to the development and prognosis of breast cancers. It is worth noting that this study was the first to include these genes as PCR templates to determine the relationship between their polymorphisms and breast cancer incidence using RAPD of amplified genes. The study was designed first to evaluate the association of ABCG2 , ABCB1 and BRCA1 gene polymorphisms in addition to miRNA-152 and ER-a using the RAPD technique with breast cancer incidence in women in Maysan, Province and then to employ those genes in the future as biomarkers in breast cancer prediction and diagnosis. This study included 100 patients with breast cancer and 30 healthy control women, and then all samples were amplified by conventional PCR with specific F and R primers for ABCG2 , ABCB1 , BRCA1 , ER-α , and miRNA-152 genes. Then, the best PCR product (20) was chosen as the template for the RAPD technique. The results revealed that all RAPD primers showed polymorphisms with higher values in patient samples, and revealed several mutations in patient samples. Our study proved the relationship between genetic polymorphisms of breast cancer related genes and a higher incidence of cancer. The results of the statistical analysis by using Chi-square showed that there were no significant differences in the types of bands of the ABCG2 , ABCB1 , BRCA1 between the patient sample and the control sample, at the probability level of P >0.05, and significant differences in the types of bands of the ER- α , and mi-RNA 152 between the patient sample and the control sample, at the probability level of P <0.05. The current study recommends employing these results for future prediction and diagnosis of breast cancers.
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