Expression Pattern and Prognostic Significance of Chemokines in Breast cancer: An Integrated Bioinformatics Analysis.

Background: Breast cancer (BC), one of the most prevalent malignancies, is the second major cause of mortality from cancer among women worldwide. Even though substantial progress has been made in breast cancer treatment, metastasis still accounts for the majority of the deaths. The tumor microenvironment (TME) comprising stromal and non-stromal components is central to tumor growth and development and is partly regulated by chemokines. Chemokines regulate immune cell trafficking, the development of stroma and play a key role in inflammation, a cancer hallmark.
Methods: In the present study, we used a bioinformatics approach to identify highly deregulated chemokines in BC patients. We performed expression analysis, survival analysis, gene ontology analysis, KEGG analysis, and protein-protein interaction network analysis of the deregulated chemokines using Gepia2, UALCAN, Kaplan-Meier Plotter, DAVID, and STRING tools.
Results: We identified >2-fold change (FC) increase in CXCL9/10/11/13 and >-2 FC decrease in CCL14/21/28, CXCL2/12 CX3CL1. Also, increased expression of CCL14, CCL21, CXCL13, CXCL9, CXCL12 correlated with better overall survival (OS) of BC patients.
Conclusions: Our results strongly indicate that chemokines may have potential biomarker characteristics, and the constructed PPI network contributed to an in-depth understanding of the chemokine networks. The deregulated chemokines may prove to be therapeutic targets for the effective management of BC.
(Copyright © 2022. Published by Elsevier Inc.)