Molecular Classification of Breast Cancer Using a Cuproptosis Related Gene Panel and a Robust REO Ensemble Classifier

Abstract Background Cuproptosis is a mitochondria-dependent form of regulated cell death. Its interplay with cancer metabolism can modulate tumor aggressiveness. We hypothesized that cuproptosis-related gene expression defines distinct breast cancer (BRCA) subtypes and that a relative expression ordering (REO) ensemble classifier built on a 19-gene panel (CRG19) yields a technically robust, clinically translatable tool. Methods We curated a mechanistically grounded 19-gene panel (CRG19) and analyzed primary BRCA RNA-seq samples from TCGA (n = 986, split into training n = 838 and testing n = 148). Consensus clustering (k = 3) identified molecular subtypes. From 171 pairwise gene relations, the top 100 discriminative REO pairs (chi-square ranking) were used to build an ensemble of four machine-learning models (SVM, Random Forest, Elastic Net, XGBoost) within a nested 5x5 cross-validation framework. Tumor microenvironment (CIBERSORTx), pathway activity (GSVA), and drug sensitivity (oncoPredict/CTRP2) were evaluated. External validation was performed on an independent cohort (GSE202203, n = 3,207). Results Consensus clustering defined three reproducible subtypes (A, B, and C) with distinct biology and clinical outcomes (p = 0.035). Subtype A was enriched for basal-like/HER2-enriched PAM50 classes, showing pronounced cell cycle activation and poorer early survival. Subtype B was predominantly luminal with active hormone signaling. Subtype C exhibited a quiescent state and the best long-term prognosis. The REO ensemble achieved high probability calibration and stability between training and test sets (KS statistics 0.12–0.14). Subtype A showed higher predicted chemosensitivity, whereas Subtypes B/C were predicted to respond better to endocrine therapy. In external validation, differential pathway patterns across subtypes were highly reproducible (all-pathway Spearman r = 0.838–0.925, weighted direction consistency = 0.947). Conclusion The CRG19 taxonomy defines biologically and clinically distinct breast cancer subtypes. The accompanying REO ensemble classifier provides a technically robust, cross-platform tool suitable for clinical risk stratification and therapeutic decision-making.