From circRNA-miRNA-immune-related mRNAs axes to potential therapeutic targets via multi-algorithmic mining of immune regulatory networks in breast cancer

Breast cancer is the most common malignant tumor in women worldwide, and its high heterogeneity and complex immune mechanisms pose challenges for treatment. CircRNAs, as miRNA sponges, can regulate gene expression, but the role of the circRNA-miRNA-immune-related mRNA regulatory axis in breast cancer remains unclear. This study aimed to construct a regulatory network of circRNA-miRNA-immune-related mRNA in breast cancer, explore its immune regulatory mechanisms, and screen potential therapeutic targets. Transcriptome data of breast cancer were obtained from public databases to screen DEmRNAs, DEmiRNAs, and DEcircRNAs. Immune-related DEmRNAs were identified by combining with the ImmPort database. Biological functions were analyzed through functional enrichment. A ceRNA regulatory network was constructed. Key immune-related DEmRNA were screened by integrating LASSO, SVM-RFE, and RF algorithms, and their associations with immune cell infiltration and potential targeted drugs were analyzed. In addition, expression verification was also performed based on external datasets. A total of 36 immune-related DEmRNAs were identified, and a ceRNA network was constructed. The KEGG functional enrichment results showed that Cytokine-cytokine receptor interaction, PI3K-Akt signaling pathway, and MAPK signaling pathway were significantly enriched. GSEA analysis revealed that the KEGG_BASE_EXCISION_REPAIR, KEGG_SPLICEOSOME, and KEGG_HOMOLOGOUS_RECOMBINATION were abnormally enriched in the breast cancer group. Five key immune-related DEmRNAs were screened out. The ceRNA sub-network corresponding to key immune-related DEmRNAs was extracted from the ceRNA network. Multiple circRNA-miRNA-mRNA regulatory axes were identified in this ceRNA sub-network, such as hsa_circ_0001861/hsa_circ_0000264-hsa-miR-296-5p-INHBA, hsa_circ_0001204-hsa-miR-654-5p-MIF, hsa_circ_0000367/hsa_circ_0000417-hsa-miR-331-3p-IGF1, hsa_circ_0001085-hsa-miR-362-3p-FGF2, and hsa_circ_0000739/hsa_circ_0000347/hsa_circ_0001053-hsa-miR-107-CTSG. Pearson correlation analysis showed that IGF1 ( r = 0.52, adjusted P = 3.1e-14) and FGF2 ( r = 0.54, adjusted P = 2.7e-15) were significantly correlated with Macrophages M2. Molecular docking showed that the binding energy of MIF to Paclitaxel was − 12.33 kcal/mol. This study identified potential circRNA-miRNA-immune-related mRNA regulatory axes in breast cancer, providing a theoretical basis for deciphering immune mechanisms and exploring candidate immunotherapeutic targets.