Multi-omics analysis of Cuproptosis-Related Signature Guides the Precision Immunotherapy and Prognosis of Breast Cancer

Breast cancer is a common malignancy in women, and its resistance to immunotherapy is a major challenge. Cuproptosis, a novel form of cell death associated with protein lipidation, tumor microenvironment, and immune response, may offer a potential solution. Aberrant expression of lncRNAs is important in BC initiation and progression, and the role of cuproptosis-related long non-coding RNAs (CRLs) in the immune regulation of BC is not fully understood. Breast cancer patient data from the TCGA database was used to identify cuproptosis-related genes (CRGs). Differential expression analysis of CRLs was performed using the 'limma' package in R. Prognostic CRLs were identified using co-expression and univariate Cox analysis. A prognostic model of six CRLs was established using Cox regression and the LASSO algorithm. Model performance was evaluated using K-M survival and ROC curve analysis. The predictive ability of the signature in immune microenvironment and immunotherapy was investigated. In vitro experiments validated AL138789.1 function. Our study identified a six-CRL prognostic signature that outperformed conventional clinicopathological characteristics in predicting survival outcomes in BC patients. The signature effectively stratified BC patients into high- and low-risk groups and showed potential in predicting the response to immunotherapy. Notably, significant differences were observed in immune cell abundance between the two groups. In vitro experiments demonstrated that AL138789.1 knockdown or overexpression significantly reduced the viability, proliferation, and invasion capacity of MDA-MB-231 or HCC1806 cells. Our 6-CRL signature has the potential as an independent biomarker for predicting prognosis and treatment response in BC patients, complementing existing clinicopathological characteristics.