Copper metabolism-related signature for prognosis prediction and MMP13 served as malignant factor for breast cancer

Objectives
This study aimed to comprehensively investigate the role of copper metabolism in breast cancer (BC) and develop a prognostic gene signature related to copper metabolism.

Methods
We identified copper metabolism-related genes from previous literature and selected them using Univariate Cox regression analysis. Cu-enrichment scores were computed using single-sample Gene Set Enrichment Analysis (ssGSEA). Differentially expressed genes (DEGs) between groups with high and low Cu-enrichment scores were identified using the *limma* package. A prognostic CuScore was then developed for BC using Random Survival Forest and LASSO regression. Kaplan-Meier survival analysis, ROC curves, and Cox regression LCL161 evaluated the CuScore’s prognostic utility. Genomic mutations were assessed with GISTIC, and immune cell infiltration was analyzed through ESTIMATE, ssGSEA, and TIMER. Functional enrichment was performed using the *clusterProfiler* and GSVA packages. Drug sensitivity predictions were made using the GDSC database and the *oncoPredict* package. MMP13 was selected for validation in in vitro experiments.

Results
Four copper metabolism-related genes (UBE2D2, SLC31A1, ATP7A, and MAPK1) were identified as having prognostic significance. Higher expression of these genes was associated with elevated Cu-enrichment scores, indicating greater malignancy in BC. Of 115 DEGs identified, 19 had prognostic value, with three (CEACAM5, MMP13, and CRISP3) highlighted by Random Survival Forest and LASSO. Elevated CuScores were linked to poorer outcomes and effectively predicted BC prognosis. CuScore and metastasis were independent prognostic factors. Additionally, tumors with lower CuScores exhibited higher infiltration of immune cells. GO and GSEA analyses suggested that six immune-related pathways were influenced by CuScore. Patients with higher CuScores had lower tumor mutational burden (TMB) and were more responsive to Sapitinib and LCL161, while those with lower CuScores were more likely to benefit from anti-PD1 therapy. MMP13 expression was found to promote BC malignancy, enhancing cell proliferation and migration.

Conclusion
The copper metabolism-related gene signature developed in this study shows promise for predicting prognosis and guiding treatment strategies in BC. Among these genes, MMP13 emerged as a key factor contributing to malignancy in breast cancer.