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Guo L, Ma X, Li H, Yan S, Zhang K, Li J. Single‑cell RNA‑seq necroptosis‑related genes predict the prognosis of breast cancer and affect the differentiation of CD4 + T cells in tumor immune microenvironment. Mol Clin Oncol 2024; 21:49. [PMID: 38872949 PMCID: PMC11170320 DOI: 10.3892/mco.2024.2747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 04/30/2024] [Indexed: 06/15/2024] Open
Abstract
Breast cancer (BC) is one of the most prevalent types of malignancy and a major cause of cancer-related death. The purpose of the present study was to identify prognostic models of necroptosis-related genes (NRGs) in BC at the single-cell RNA-sequencing level and reveal the role of NRGs in tumour immune microenvironment (TIME). A risk model was constructed based on Cox regression and LASSO methods. Next, high-scoring cell populations were searched through AUCell scores, and cell subtypes were then analyzed by pseudotime analysis. Finally, the expression level of the model genes was verified by reverse transcription-quantitative (RT-qPCR). A new prognostic model was constructed and validated based on five NRGs (BCL2, BIRC3, AIFM1, IFNG and VDAC1), which could effectively predict the prognosis of patients with BC. NRGs were found to be highly active in CD4+ T cells and differentially expressed in their developmental trajectories. Finally, the RT-qPCR results showed that most of the model genes were significantly overexpressed in MDA-MB-231 and MCF-7 cells (P<0.05). In conclusion, an NRG signature with excellent predictive properties in prognosis and TIME was successfully established. Moreover, NRGs were involved in the differentiation and development of CD4+ T cells in TIME. These findings provide potential therapeutic strategies for BC.
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Affiliation(s)
- Li Guo
- Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia Hui Autonomous Region 750003, P.R. China
| | - Xiuzhen Ma
- Department of Surgical Oncology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia Hui Autonomous Region 750004, P.R. China
| | - Hong Li
- Department of Surgical Oncology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia Hui Autonomous Region 750004, P.R. China
| | - Shuxun Yan
- Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia Hui Autonomous Region 750003, P.R. China
| | - Kai Zhang
- Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia Hui Autonomous Region 750003, P.R. China
| | - Jinping Li
- Department of Surgical Oncology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia Hui Autonomous Region 750004, P.R. China
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Li J, Wu F, Li C, Sun S, Feng C, Wu H, Chen X, Wang W, Zhang Y, Liu M, Liu X, Cai Y, Jia Y, Qiao H, Zhang Y, Zhang S. The cuproptosis-related signature predicts prognosis and indicates immune microenvironment in breast cancer. Front Genet 2022; 13:977322. [PMID: 36226193 PMCID: PMC9548612 DOI: 10.3389/fgene.2022.977322] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 09/06/2022] [Indexed: 11/20/2022] Open
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.
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Affiliation(s)
- Jia Li
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Fei Wu
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Chaofan Li
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Shiyu Sun
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Cong Feng
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Huizi Wu
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Xi Chen
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Weiwei Wang
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yu Zhang
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Mengji Liu
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Xuan Liu
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yifan Cai
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yiwei Jia
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Hao Qiao
- Department of Orthopedics, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yinbin Zhang
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- *Correspondence: Yinbin Zhang, ; Shuqun Zhang,
| | - Shuqun Zhang
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- *Correspondence: Yinbin Zhang, ; Shuqun Zhang,
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