Evaluation of the Expression Level of Some Coding and Non-coding Genes in Breast Cancer Samples Based on Bioinformatics and Laboratory Studies

Breast cancer (BC) is the leading cause of cancer-associated mortality in women worldwide. However, the molecular mechanism underlying the process is still unclear. In this regard, bioinformatics studies play a decisive role in facilitating the path of biological investigations and can ultimately lead to the identification of better molecular candidates for further study.

Due to the abnormal expression of many coding and non-coding genes in all types of cancers and their relationship with various mechanisms of carcinogenesis, this study aimed at evaluating the expression levels of certain coding and non-coding genes involved in BC based on bioinformatics findings and laboratory investigations.

Gene expression dataset, module extraction, functional enrichment analysis, protein-protein interaction network construction, and RT-qPCR were performed based on bioinformatics methods and laboratory investigations. Additionally, the promoter region mutations of these genes were investigated, using sequencing of extracted DNAs from formalin-fixed paraffin-embedded (FFPE) tumor tissues.

A module was selected as a candidate for further investigation. Estrogen receptor 1 (ESR1) and forkhead box A1 (FOXA1) showed the highest degrees in the PPI network with 9 and 7 links, respectively. Furthermore, the expression levels of the FOXA1 gene, RNA component of mitochondrial RNA processing endoribonuclease (RMRP), and nuclear enriched abundant transcript 1 (NEAT1) were significantly upregulated in the tumor group compared to the control group (in order, P = 0.044, P = 0.014, and P = 0.0004). The tumors of patients with positive metastasis displayed significantly higher levels of NEAT1 and RMRP expression compared to those of negative metastasis samples (P < 0.05). Moreover, the expression level of RMRP dramatically decreased in HER2-positive patients compared to negative samples (P = 0.011). Finally, no mutations were observed in the promoter sequencing of positive metastasis samples compared to normal samples.

The upregulation levels of all three examined genes may correlate with BC progression. Therefore, they could potentially be used as biomarkers for detecting BC development.