| dc.description.abstract | Breast cancer is a heterogeneous disease, which is the most common malignancy in women. The incidence and mortality
rates of breast cancer indicate that it is the leading cause of cancer-related with deaths. circRNAs operate as part of com peting endogenous RNAs (ceRNAs) mechanisms, which play critical roles in the diferent biological processes of breast
cancer such as proliferation, migration, and apoptosis. The goal of the present study is to identify the potential predictive
biomarker for breast cancer diagnosis in the circRNA network by in vitro and in silico analyzes. 40 miRNAs were obtained
from the miRWalk database and their combinatorial target genes (potential ceRNAs) were identifed with ComiR. We stated
that the cancer-specifc circRNA genes in MCF-7 cells using the cancer-specifc circRNA (CSDC) database, and obtained
the ones showing potential ceRNA activity in our previous analysis among them. Identifed genes with remarkable expres sion diferences between BCa and normal breast tissue were determined by the GEPIA database. Moreover, the Spearman
correlation test in the GEPIA database was used for the statistical analysis of the relationship between DCAF7 and SOGA1,
SOGA1 and AVL 9, DCAF7 and AVL 9 gene pairs. And also, DCAF7, SOGA1, and AVL9 gene expression levels were
detected in MCF-7 and MCF-10A cells by RT-qPCR method. DCAF7, SOGA1, and AVL9 gene were signifcantly more
expressed to BCa tissue and MCF-7 cells than normal breast tissue and MCF-10 A cells. And also, DCAF7 and SOGA1,
SOGA1 and AVL9, DCAF7 and AVL9 genes pairs were found to be signifcantly correlated with BCa. These genes may be
considered as potential predictive biomarkers to discriminate BCa patients from healthy persons. Our preliminary results
can supply a new perspective for in vitro and vivo studies in the future. | tr |
