MicroRNA–Gene Networks Distinguish Hormone Receptor Status in HER2-Low Breast Cancer: An Integrative Transcriptomic Analysis

<b>Background:</b> HER2-low breast cancer is a biologically heterogeneous subgroup in which hormone receptor (HR) expression critically shapes prognosis and treatment, but the underlying regulatory mechanisms remain unclear. MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression and may contribute to HR heterogeneity. This study aimed to identify deregulated miRNAs and associated gene networks distinguishing HER2-low/HR-positive from HER2-low/HR-negative tumors, elucidating the molecular mechanisms underlying this divergence. <b>Methods:</b> Differential expression analyses of miRNAs and genes were performed using Wilcoxon tests and DESeq2 (|log₂FC| > 1; FDR-adjusted <i>p</i>-value < 0.05). Survival analyses were conducted using Cox proportional hazards models to evaluate the individual miRNAs and miRNA signature. Functional enrichment analyses, including GO, KEGG and Reactome pathways, were performed. Correlation analysis and the miRNA target prediction were integrated to identify regulatory interactions. <b>Results:</b> Comparisons between HER2-low/HR-positive and HER2-low/HR-negative tumors identified 165 significantly deregulated miRNAs and 170 strongly deregulated genes. Intersection analysis highlighted miR-9-5p, miR-532-5p and miR-576-5p as specifically associated with HR-negative status. Survival analyses showed non-significant trends for the overall survival and progression-free interval. Functional enrichment analysis revealed hormone-related pathways in HR-positive tumors and immune, inflammatory and proliferative pathways in HR-negative tumors. Integrative correlation and target prediction analyses identified two miRNA-mRNA regulatory axes, miR-576-5p/TGFBI and miR-9-5p/POU2F2. <b>Conclusions:</b> Our study demonstrated that HER2-low breast cancer exhibits distinct miRNA and gene expression profiles, which highlight different transcriptomic profiles according to HR status for the first time. Specific miRNA-gene networks may drive transcriptional heterogeneity, serving as potential biomarkers for stratification and as therapeutic targets. These findings provide insight into the molecular basis of HER2-low tumor diversity and support future development of HR-directed therapeutic strategies.