Abstract
Breast cancer is the most prevailing disease among women. It actually develops from breast tissue and has heterogeneous and complex nature that constitutes multiple tumor quiddities. These features are associated with different histological forms, distinctive biological characteristics, and clinical patterns. The predisposition of breast cancer has been attributed to a number of genetic factors, associated with the worst outcomes. Unfortunately, their behavior with relevance to clinical significance remained poorly understood. So, there is a need to further explore the nature of the disease at the transcriptome level. The focus of this study was to explore the influence of Krüppel-like factor 3 (KLF3), tumor protein D52 (TPD52), microRNA 124 (miR-124), and protein kinase C epsilon (PKCε) expression on breast cancer. Moreover, this study was also aimed at predicting the tertiary structure of KLF3 protein. Expression of genes was analyzed through real-time PCR using the delta cycle threshold method, and statistical significance was calculated by two-way ANOVA in Graphpad Prism. For the construction of a 3D model, various bioinformatics software programs, Swiss Model and UCSF Chimera, were employed. The expression of KLF3, miR-124, and PKCε genes was decreased (fold change: 0.076443, 0.06969, and 0.011597, respectively). However, there was 2-fold increased expression of TPD52 with p value < 0.001 relative to control. Tertiary structure of KLF3 exhibited 80.72% structure conservation with its template KLF4 and was 95.06% structurally favored by a Ramachandran plot. These genes might be predictors of stage, metastasis, receptor, and treatment status and used as new biomarkers for breast cancer diagnosis. However, extensive investigations at the tissue level and in in vivo are required to further strengthen their role as a potential biomarker for prognosis of breast cancer.
Highlights
Breast cancer is a malignancy that originates from breast tissue
The RNA samples isolated from the blood of breast cancer patients were analyzed by qPCR for the expression of tumor protein D52 (TPD52), Krüppel-like factor 3 (KLF3), miR-124, and PKCε
The dysregulated expression pattern of all these genes is significantly coupled with disease progression
Summary
Breast cancer is a malignancy that originates from breast tissue. It is presumed that breast cancer results from the accumulation of several genetic aberrations, resulting in inactivation of tumor suppressor genes and activation of protooncogenes. Current evidences from literature indicate that approximately 10-20% of cases are due to a germline mutation in a gene that leads to increased predisposition for breast cancer [2, 3] while 15-20% of breast cancer incidences are familial [4]. Other than germ line genes, dysregulation in several other genes encoding tumor suppressor proteins, transcription regulators, microRNAs, kinases, and phosphatases has led to breast cancer [5, 6]. Genome-wide studies of human cancer have shown that Receptor Tyrosine Kinase (RTK) and G Protein-Coupled Receptor (GPCR) are the major receptors that regulate the effector protein [7, 8]. Phosphoinositide 3-kinases (PI3K) and Kras via channeling signal transduction from various
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