A comprehensive analysis of notch signaling genes in breast cancer: Expression pattern and prognostic significance

Abstract

The most recurrent type of cancer among women is breast cancer which is an intricate disease with high intertumoral and intratumoral heterogeneity. Such variability is a key factor in the failure of current treatments and the emergence of resistance. It is crucial to develop novel therapeutic options to enhance the prognosis for breast cancer patients due to the limitations of current therapy and the unavoidable formation of acquired drug resistance (chemo and endocrine) as well as radio resistance. Poor clinical results in the treatment of breast cancer, that is resistance are associated with deregulated Notch signalling within the breast tumor and its tumor microenvironment (TME). In this research, a bioinformatics approach was used to check the expression pattern, the role, as well as the prognostic and diagnostic significance of the deregulated Notch-related genes in BC patients. The various bioinformatic tools include; UCSC XENA, GEPIA 2, UALCAN, bc Genexminer, KM Plotter, ENRICHR, STRING and Cytoscape. The study demonstrates that highly dysregulated genes (NOTCH4, CCND1, JAG1, DLL1, MAML2, and EGFR) can be used as biomarkers to identify breast cancer patients with poor prognosis and as potential targets for therapeutic intervention. The study found that 6 genes—NOTCH4, CCND1, JAG1, DLL1, MAML2, and EGFR—out of 22 tested genes showed a significant log2 fold change. Our study revealed that Luminal Breast Cancer patients display a high expression of the CCND1 gene in comparison to its expression in normal. The results of our study also depicted that the patients with elevated levels of NOTCH-related gene expression displayed better relapse-free survival with p < 0.05. Moreover, we analysed the deregulated notch genes that play an important role in various cellular and molecular processes. The study shows that these highly deregulated screened genes could be utilized as the Biomarkers that help to reveal poor prognosis and could act as targets for treating BC. However, the identification of these dysregulated genes involved in notch signallibng through insilico approach is not sufficient.