Twee-genen nomogram voorspelt recidief bij HER2-positieve borstkanker onder trastuzumab

BACKGROUND: Resistance to trastuzumab and subsequent relapse remain critical challenges in human epidermal growth factor receptor 2 (HER2)-positive breast cancer management. This study aimed to develop and validate a multivariable prediction model for relapse in HER2-positive breast cancer patients treated with trastuzumab and to explore the underlying biological mechanisms of the identified biomarkers. METHODS: This retrospective study utilized public gene expression profiles from the Gene Expression Omnibus (GEO) database and a clinical cohort from the First Affiliated Hospital of Xi'an Jiaotong University. The analysis included a training cohort (GSE55348, n=51), an internal validation cohort (GSE58984, n=94), and an external validation cohort (I-SPY2/GSE181574, n=127). Relapse-associated hub genes were identified via differential expression analysis and weighted gene co-expression network analysis (WGCNA). Independent predictors were determined through multivariate Cox regression to construct a nomogram for predicting 3-year relapse-free survival (RFS). Model performance was evaluated using time-dependent receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Biological mechanisms were investigated using gene set enrichment analysis (GSEA), immune infiltration analysis, and single-cell RNA sequencing (scRNA-seq). Clinical relevance was further supported by immunohistochemistry (IHC) in a pilot cohort of 12 patients. RESULTS: DYX1C1 and GNAI1 were identified as robust, independent predictors of relapse. The constructed two-gene nomogram demonstrated excellent predictive accuracy, with an area under the curve (AUC) of 0.894 in the training cohort and 0.829 in the validation cohort. Mechanistically, DYX1C1 expression was significantly associated with an immunosuppressive tumor microenvironment (TME) characterized by reduced infiltration of B cells and CD8+ T cells, whereas GNAI1 expression correlated with stromal activation and extracellular matrix remodeling via the TGF-β signaling pathway. Single-cell analysis confirmed distinct cellular localizations of DYX1C1 in epithelial cells and GNAI1 in endothelial and mesenchymal cells. IHC analysis indicated that high protein expression of both biomarkers was associated with poor pathological complete response (pCR) to neoadjuvant therapy. CONCLUSIONS: The DYX1C1- and GNAI1-based nomogram provides a simple, accurate tool for predicting relapse in HER2-positive breast cancer treated with trastuzumab. These biomarkers are associated with distinct pro-tumorigenic TME features-DYX1C1 with immune suppression and GNAI1 with stromal activation-offering hypothesis-generating insights into therapeutic resistance.