Breast cancer is the most common cancer in women, and in advanced stages, it often metastasizes to the brain. However, research on the biological mechanisms of breast cancer brain metastasis and potential therapeutic targets are limited. Differential gene expression analysis (DEGs) for the datasets GSE43837 and GSE125989 from the GEO database was performed using online analysis tools such as GEO2R and Sangerbox. Further investigation related to SULF1 was conducted using online databases such as Kaplan-Meier Plotter and cBioPortal. Thus, expression levels, variations, associations with HER2, biological processes, and pathways involving SULF1 could be analyzed using UALCAN, cBioPortal, GEPIA2, and LinkedOmics databases. Moreover, the sensitivity of SULF1 to existing drugs was explored using drug databases such as RNAactDrug and CADSP. High expression of SULF1 was associated with poor prognosis in advanced breast cancer brain metastasis and was positively correlated with the expression of HER2. In the metastatic breast cancer population, SULF1 ranked top among the 16 DEGs with the highest mutation rate, reaching 11%, primarily due to amplification. KEGG and GSEA analyses revealed that the genes co-expressed with SULF1 were positively enriched in the 'ECM-receptor interaction' gene set and negatively enriched in the 'Ribosome' gene set. Currently, docetaxel and vinorelbine can act as treatment options if the expression of SULF1 is high. This study, through bioinformatics analysis, unveiled SULF1 as a potential target for treating breast cancer brain metastasis (BM).
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