Identification of prognostic biomarkers for breast cancer brain metastases based on the bioinformatics analysis

• DOI: 10.1016/j.bbrep.2022.101203
• Publication Date: 2022-01-10T23:17:01Z
• Authors: Zhuoyi Wu; Jinghai Wan; Jiawei Wang; Xiaoli Meng; Haipeng Qian
• Keywords: Identification; Brain cancer

The prognosis of breast cancer (BC) patients who develop into brain metastases (BMs) is very poor. Thus, it great significance to explore the etiology BMs in BC and identify key genes involved this process improve survival with BMs. gene expression data clinical information were downloaded from TCGA GEO database. Differentially expressed (DEGs) TCGA-BRCA GSE12276 overlapped find differentially metastatic (DEMGs). protein-protein interaction (PPI) network DEMGs was constructed via STRING ClusterProfiler R package applied perform ontology (GO) enrichment analysis DEMGs. univariate Cox regression Kaplan-Meier (K-M) curves plotted screen associated overall recurrence survival, which identified as BC. immune infiltration expressions checkpoints for relapses other analyzed respectively. correlations among differently infiltrated cells or calculated. set (GSEA) each conducted investigate potential mechanisms Moreover, CTD database used predict drug-gene genes. A total 154 DEGs at M0 M1 667 relapses. By overlapping these DEGs, 17 identified, enriched cell proliferation related biological processes molecular functions. revealed that CXCL9 GPR171 closely analyses checkpoint showed there a significant difference microenvironment between GSEA indicated may regulate immune-related pathways. Our study underlying These findings provide promising approach treatments