Association between polymorphisms of XRCC1, p53 and MDR1 genes, the expression of their protein products and prognostic significance in human breast cancer.

Abstract

SummaryBackgroundThis study aimed to examine the relationship between XRCC1, p53 and MDR1 protein, along with polymorphisms of their genes and their prognostic values in breast cancer. The following clinical and pathological parameters were evaluated: histopathological type of tumor, grade, stage, Her2/neu expression, ER, PR positivity and involvement of regional lymph nodes.Material/MethodsExpression of proteins was determined in 39 samples of breast cancer by immunohistochemistry. Nucleotide polymorphisms were analyzed by PCR-RFLP. For statistical analysis, chi-square test (Yates), Fisher’s exact test, and correlation test were used to analyze the data.ResultsThe highest protein expression was immunohistochemically found in MDR1 protein, with 54% of samples testing positive. In addition, the evaluation of MDR1 expression revealed higher positive immunoreactivity in lobular (LIC) and other types of tumor in comparison to ductal (DIC) type. The expression of p53 and XRCC1 protein was equal, but lower compared to MDR1, both testing positive in 36% of all tissue samples. Comparison of XRCC1 protein and histopathological type of tumor revealed that DIC and LIC types were mostly XRCC1-negative, while other types, papillary and mucinous were more likely to be XRCC1-positive. Interestingly, when evaluating LIC samples separately, a negative correlation between the Her2/neu and expression of XRCC1 was detected. Apparently, all Her2/neu-positive samples were XRCC1-negative (6/86%). The correlation test indicated a negative correlation between Her2/neu-positive samples and XRCC1-negative specimens (r=1, p<0.05). Statistical analysis did not reveal a correlation of p53 expression with clinical and pathological parameters. Similarly, no statistically significant difference was found between the tested polymorphisms and protein expression.ConclusionsWe did not find statistically significant correlation between tested polymorphisms and their protein expression.

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