Breast cancer (BC) is considered to be one of the primary causes of cancer deaths in women. Cuproptosis was suggested to play an important role in tumor proliferation and tumor immune microenvironment. Therefore, an investigation was conducted to identify the relationship between cuproptosis-related long non-coding RNAs (lncRNAs) and BC prognosis.
Based on The Cancer Genome Atlas (TCGA), nine cuproptosis-related lncRNAs were identified by Pearson’s analysis and Cox regression analysis to create a cuproptosis-related lncRNA signature. Subsequently, patients with BC were divided into high-risk and low-risk groups. The Kaplan–Meier curves and a time-dependent receiver operating characteristic (ROC) analysis were employed to elucidate the predictive capability of the signature. After that, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted by Gene Set Enrichment Analysis (GSEA), and the lncRNA–mRNA co-expression network was established by Cytoscape software. Furthermore, the ESTIMATE score was calculated, and the immune cell type component analysis was conducted. Eventually, immunotherapy response analysis was applied to identify the predictive power of cuproptosis-related lncRNAs to tumor immunotherapy response, including immune checkpoint gene expression levels, tumor mutational burden (TMB), and microsatellite instability (MSI).
Patients with BC in the low-risk groups showed better clinical outcomes. The KEGG pathways in the high-risk groups were mainly enriched in immune response and immune cell activation. Furthermore, the ESTIMATE scores were higher in the low-risk groups, and their immune cell infiltrations were dramatically different from those of the high-risk groups. The low-risk groups were shown to have higher infiltration levels of CD8+ T cells and TMB-high status, resulting in better response to immunotherapies.
The findings of this study revealed that the nine-cuproptosis-related lncRNA risk score was an independent prognostic factor for BC. This signature was a potential predictor for BC immunotherapy response. What we found will provide novel insight into immunotherapeutic treatment strategies in BC.