Expression characterization of the guanylate-binding protein gene family in breast cancer and its association with the immune microenvironment
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View abstract on PubMed
Summary
This summary is machine-generated.This study developed a prognostic model for breast cancer (BRCA) using guanylate-binding protein (GBP) genes. The model predicts patient survival and immune microenvironment status, aiding in personalized treatment strategies for BRCA.
Area Of Science
- Oncology
- Immunology
- Genetics
Background
- Breast cancer (BRCA) prognosis is complex.
- Guanylate-binding protein (GBP) genes may influence immune regulation in BRCA.
Purpose Of The Study
- To develop a prognostic model for BRCA utilizing GBP-related genes.
- To investigate the role of GBP genes in BRCA's underlying mechanisms.
Main Methods
- RNA sequencing data and gene expression profiles from public databases were analyzed.
- Weighted gene co-expression network analysis (WCGNA) and LASSO regression identified key prognostic genes.
- Differential gene expression and immune cell infiltration were assessed between risk groups.
Main Results
- A prognostic model comprising PSME2, DACT2, PIGR, and STX11 demonstrated strong diagnostic performance.
- Lower GBP gene scores correlated with poorer overall survival and altered immune cell infiltration.
- DACT2 overexpression suppressed BRCA cell survival, migration, and invasion in vitro.
Conclusions
- A novel prognostic model for BRCA based on GBP-related genes was established.
- This model is linked to the tumor immune microenvironment, offering insights for prognostic assessment.
- The findings support individualized treatment guidance for breast cancer management.
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