Bioinformatic analysis and experimental validation of six cuproptosis-associated genes as prognostic signatures in breast cancer

Abstract

Abstract Background Breast carcinoma (BRCA) is the life-threatening malignancy in women with poor prognosis. Cuproptosis is a novel mode of cell death, and its relationship with BRCA is unclear. This study endeavored to develop the cuproptosis-relevant prognostic genes and signature for BRCA. Methods Cuproptosis-relevant subtypes of BRCA patients were derived by consistent clustering. Disparate expression analysis was implemented in the ‘limma’ package. The univariate Cox and multivariate Cox analysis were executed to determine the cuproptosis-relevant prognostic signature. The signature was created and affirmed in distinct datasets. The Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA) were also conducted to uncover the molecular mechanisms involved in the prognostic signature. ESTIMATE and CIBERSORT algorithm were applied to probe the linkage between the gene signature and tumor microenviroment (TME). Immunotherapy responsiveness were projected by Tumor Immune Dysfunction and Exclusion (TIDE) website. Detection of the expression of cuproptosis-revelant prognostic genes in breast cancer cell lines was implemented by Real Time Quantitative PCR (RT-qPCR). Results A grand total of 38 cuproptosis-associated differentially expressed genes (DEGs) in BRCA were mined by consistent clustering and disparate expression analysis. Based on univariate Cox and multivariate Cox analysis, six cuproptosis-revelant prognostic genes, namely SAA1, KRT17, VAV3, IGHG1, TFF1 and CLEC3A, were mined to establish a cuproptosis-revelant signature. Then, we affirmed the signature by external validation set. GSVA and GSEA manifested that multiple cell cycle-linked and immune-related pathways and biological processes were connected to the signature. The ESTIMATE and CIBERSORT results revealed significantly different TMEs for the two Cusig score subgroups. Finally, the result of RT-qPCR of cell lines further affirmed the expression trend of SAA1, KRT17, IGHG1 and CLEC3A. Conclusion Taken together, this study authenticated the cuproptosis-revelant prognostic genes and developed a signature for the overall survival projection of BRCA, which will provide the basis for developing prognostic molecular biomarkers and in-depth understanding of the relationship between cuproptosis and BRCA.