Expression characterization of the guanylate-binding protein gene family in breast cancer and its association with the immune microenvironment.

Background: Considering the complexity of prognostic assessment in breast cancer (BRCA) and the potential role of guanylate-binding protein (GBP) genes in immune regulation, the present research was designed to construct a prognostic model using GBP-related genes and to explore the mechanism of their role in BRCA. Methods: Using RNA sequencing data of BRCA from public databases, GBP gene scores of BRCA samples were computed by single-sample GSEA (ssGSEA). The gene modules associated with the scores were identified by weighted gene co-expression network analysis (WCGNA). Subsequently, differentially expressed genes (DEGs) between BRCA samples and paraneoplastic samples were screened by the "limma" package and intersected with the modular genes. Key prognostic genes were further compressed by least absolute shrinkage and selection operator (LASSO), univariate and multivariate stepwise regression analyses were used to develop a risk model. Next, differences in the biological characteristics and immune infiltration between different risk groups were explored. Particularly, CCK-8, wound healing and transwell test were performed to examine the biological role of Results: Low GBP scores in BRCA patients were significantly linked to a poorer overall survival. Two gene modules were closely and positively correlated with GBP scores, and their module genes were enriched in immune-related pathways. Subsequently, four key genes ( Conclusion: This study constructed a prognostic model for BRCA based on GBP-related genes. The model was closely related to the immune microenvironment, contributing to the prognostic assessment and individualized treatment guidance in the management of BRCA.