WGCNA-based identification of potential targets and pathways in response to treatment in locally advanced breast cancer patients

Abstract

Abstract Locally advanced breast cancer patients have a poor prognosis; however, the relationship between potential targets and the response to treatment is still unclear. The gene expression profiles of breast cancer patients with stages from IIB to IIIC were downloaded from The Cancer Genome Atlas. We applied weighted gene co-expression network analysis and differentially expressed gene analysis to identify the primary genes involved in treatment response. The disease-free survival between low- and high-expression groups was analyzed using Kaplan–Meier analysis. Gene set enrichment analysis was applied to identify hub genes-related pathways. Additionally, the CIBERSORT algorithm was employed to evaluate the correlation between the hub gene expression and immune cell types. A total of 16 genes were identified to be related to radiotherapy response, and low expression of SVOPL, EDAR, GSTA1, and ABCA13 was associated with poor overall survival and progression-free survival in breast cancer cases. Correlation analysis revealed that the four genes negatively related to some specific immune cell types. The four genes were downregulated in H group compared with the L group. Four hub genes associated with the immune cell infiltration of breast cancer were identified; these genes might be used as a promising biomarker to test the treatment in breast cancer patients.