Identification of significant hub genes and pathways associated with metastatic breast cancer and tolerogenic dendritic cell via bioinformatics analysis
Kirstie Wong Chee Ching , Noor Fatmawati Mokhtar , Gee Jun Tye
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引用次数: 0
Abstract
Metastatic breast cancer (MBC) is an advanced-stage breast cancer associated with more than 90 % of cancer-related deaths. Immunosuppressive properties of tolerogenic dendritic cells (tolDCs) in tumour immune microenvironment (TIME) may be a risk factor for the rapid progression to MBC. However, the exact connections between the two are unknown. The aim of the current study is to uncover gene signatures and key pathways associated with MBC and tolDCs via an integrated bioinformatics approach. Gene expression profiles of MBC and tolDCs were retrieved from Gene Expression Omnibus (GEO) to identify common differentially expressed genes (DEGs). From DGE analysis, 529 upregulated common DEGs and 367 downregulated common DEGs had been identified. In enrichment analysis, common DEGs enriched in GO terms of defense response to virus and KEGG pathway of transcriptional misregulation in cancer were reported to be significantly associated with MBC and tolDCs. From the constructed PPI networks, 23 hub genes were identified, although only 5 genes were significant; 3 upregulated (ISG15, OAS2 and RSAD2) and 2 downregulated (eEF2 and PPARG) as they were found to be significantly correlated and had the same expression trend as predicted in validation analysis of overall survival (OS) analysis, expression levels, immune infiltration analysis and immunohistochemistry (IHC) analysis. These 5 hub genes can now be exploited in developing novel therapeutic interventions and as diagnostic biomarkers for enhancing the clinical outcomes of MBC patients.
期刊介绍:
Computers in Biology and Medicine is an international forum for sharing groundbreaking advancements in the use of computers in bioscience and medicine. This journal serves as a medium for communicating essential research, instruction, ideas, and information regarding the rapidly evolving field of computer applications in these domains. By encouraging the exchange of knowledge, we aim to facilitate progress and innovation in the utilization of computers in biology and medicine.