This study aimed to differentiate phyllodes tumors from fibroadenomas by identifying biomarkers through bioinformatics. Gene expression datasets from the GEO database were analyzed, focusing on differential expression and epithelial-mesenchymal transition (EMT)-related genes between breast fibro-ma and phyllodes tumors. A total of 209 upregulated and 254 downregulated differentially expressed genes (DEGs) were identified. Intersection with 1142 EMT genes yielded 42 EMT-DEGs. Enrichment analysis linked these genes to epithelial cell proliferation, stem cell differentiation, and activities involving collagen-containing extracellular matrices, translation, repressor activity, and mRNA post-transcriptional regulation. Hub genes were identified using Weighted Gene Co-expression Network Analysis (WGCNA), Random Forest, and Lasso regression. The genes CCL19 and CCR6 emerged as potential biomarkers and demonstrated strong internal discriminative ability between fibroadenoma and phyllodes tumor samples, with Receiver Operating Characteristic (ROC) values of 0.962 and 0.915, respectively, in the GSE78071 dataset. The combined model showed favorable internal discrimination, with a mean absolute error of 0.006. Validation with six fresh tissue specimens confirmed higher expression of CCL19 and CCR6 in fibroadenomas compared to phyllodes tumors. Further analysis revealed their roles in chemokine signaling, cytokine interactions, and signaling pathways. CCL19 and CCR6 were identified as diagnostic biomarkers for distinguishing breast fibroadenomas from phyllodes tumors.
Gao et al. (Thu,) studied this question.