A Systems Biology Approach Provides Deeper Insights into Differentially Expressed Genes in Taxane-Anthracycline Chemoresistant and Non-Resistant Breast Cancers

Asian Pacific Journal of Cancer Prevention : APJCP
Shamim SarhadiNosratollah Zarghami

Abstract

Objective: To date, numerous studies have been conducted to search for reasons for chemoresistance and differences in survival rates of patients receiving chemotherapy. We have sought to identify differentially expressed genes (DEGs) between predicted chemotherapy resistance and sensitive phenotypes by a network as well as gene enrichment approach. Methods: Functional modules were explored with network analysis of DEGs in predicted neoadjuvant taxane-anthracycline resistance versus sensitive cases in the GSE25066 dataset, including 508 samples. A linear model was created by limma package in R to establish DEGs. Results: A gene set related to phagocytic vesicle membrane was found to be up-regulated in chemoresistance samples. Also, we found GO_CYTOKINE_ACTIVITY and GO_GROWTH_FACTOR BINDING to be up-regulated gene sets with the chemoresistance phenotype. Growth factors and cytokines are two groups of agents that induce the immune system to recruit APCs and promote tolerogenic phagocytosis. Some hub nodes like S100A8 were found to be important in the chemoresistant tumor cell network with associated high rank genes in GSEA. Conclusions: Functional gene sets and hub nodes could be considered as potential treatment targets. Moreover...Continue Reading

Software Mentioned

Enrich R
STRING
Enrichr
InSilicoDB
Limma
NetworkAnalyst
R
GeneCards
GSEA
Ipathway

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