The A-kinase anchoring proteins correlation with disease free survival in breast cancer

Abstract

Background: Researchers are always trying to find specific markers which express specifically in cancer. These specific markers help to diagnose and treat cancer without affecting normal tissues. Cancer-testis antigens are among the new promising biomarkers, especially for targeted therapy. These markers are specially expressed in testis. Various studies have been reported individual expression of these proteins in some tumor tissues. Since testis is an immune privilege organ, abnormal expression of the above mentioned genes raises immune response and the serum antibody against them (CT antigene) can be detected as a marker of cancer. However, understanding their differential role in normal and cancer tissues may introduce them as new candidates of cancer biomarkers. The aim of this study was to evaluate AKAP3 gene expression in breast cancer and its correlation with clinicopathologic features of the disease. Methods: This study is a case-control study conducted at the Brest Cancer Research Center (BCRC)- Iran, between October 2014 to May 2016. AKAP3 gene expression was investigated with real-time PCR in breast samples including: 74 tumors, 73 normal adjacents and 15 normal tissues. On the other hand the correlation between gene expression, clinicopathologic features of the tumors and treatment regimen were evaluated. Results: Statistical analysis showed a significant correlation between lack of AKAP3 expression, tumor size (P=0.01) and stage (P=0.04). The association between poor prognosis and the absence of AKAP3 expression in normal adjacent tissues were observed. Kaplan Meier plot showed a significant better disease free survival in the normal adjacent patients group that are expressed AKAP3. Conclusion: It was observed that the better free survival in the normal adjacent group is because of the different AKAP3 expression, not treatment variations between two patient groups. As a result, AKAP3 can be a suitable candidate biomarker for breast cancer patients. Also, the study of gene expression in normal tissue of patients may be used to predict response to therapy