The cuproptosis-related signature predicts prognosis and indicates immune microenvironment in breast cancer

Jia Li; Fei Wu; Chaofan Li; Shiyu Sun; Cong Feng; Huizi Wu; Xi Chen; Weiwei Wang; Yu Zhang; Mengji Liu; Xuan Liu; Yifan Cai; Yiwei Jia; Hao Qiao; Yinbin Zhang; Shuqun Zhang

doi:10.3389/fgene.2022.977322

The cuproptosis-related signature predicts prognosis and indicates immune microenvironment in breast cancer

Front Genet. 2022 Sep 26:13:977322. doi: 10.3389/fgene.2022.977322. eCollection 2022.

Authors

Jia Li¹, Fei Wu¹, Chaofan Li¹, Shiyu Sun¹, Cong Feng¹, Huizi Wu¹, Xi Chen¹, Weiwei Wang¹, Yu Zhang¹, Mengji Liu¹, Xuan Liu¹, Yifan Cai¹, Yiwei Jia¹, Hao Qiao², Yinbin Zhang¹, Shuqun Zhang¹

Affiliations

¹ Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
² Department of Orthopedics, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.

Abstract

Breast cancer (BC) is the most diagnosed cancer in women. Cuproptosis is new regulated cell death, distinct from known death mechanisms and dependent on copper and mitochondrial respiration. However, the comprehensive relationship between cuproptosis and BC is still blank until now. In the present study, we acquired 13 cuproptosis-related regulators (CRRs) from the previous research and downloaded the RNA sequencing data of TCGA-BRCA from the UCSC XENA database. The 13 CRRs were all differently expressed between BC and normal samples. Using consensus clustering based on the five prognostic CRRs, BC patients were classified into two cuproptosis-clusters (C1 and C2). C2 had a significant survival advantage and higher immune infiltration levels than C1. According to the Cox and LASSO regression analyses, a novel cuproptosis-related prognostic signature was developed to predict the prognosis of BC effectively. The high- and low-risk groups were divided based on the risk scores. Kaplan-Meier survival analysis indicated that the high-risk group had shorter overall survival (OS) than the low-risk group in the training, test and entire cohorts. GSEA indicated that the immune-related pathways were significantly enriched in the low-risk group. According to the CIBERSORT and ESTIMATE analyses, patients in the high-risk group had higher infiltrating levels of antitumor lymphocyte cell subpopulations and higher immune score than the low-risk group. The typical immune checkpoints were all elevated in the high-risk group. Furthermore, the high-risk group showed a better immunotherapy response than the low-risk group based on the Tumor Immune Dysfunction and Exclusion (TIDE) and Immunophenoscore (IPS). In conclusion, we identified two cuproptosis-clusters with different prognoses using consensus clustering in BC. We also developed a cuproptosis-related prognostic signature and nomogram, which could indicate the outcome, the tumor immune microenvironment, as well as the response to immunotherapy.

Keywords: bioinformatics; breast cancer; cuproptosis; prognostic signature; tumor immune microenvironment.