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

被引:40
作者
Li, Jia [1 ]
Wu, Fei [1 ]
Li, Chaofan [1 ]
Sun, Shiyu [1 ]
Feng, Cong [1 ]
Wu, Huizi [1 ]
Chen, Xi [1 ]
Wang, Weiwei [1 ]
Zhang, Yu [1 ]
Liu, Mengji [1 ]
Liu, Xuan [1 ]
Cai, Yifan [1 ]
Jia, Yiwei [1 ]
Qiao, Hao [2 ]
Zhang, Yinbin [1 ]
Zhang, Shuqun [1 ]
机构
[1] Xi An Jiao Tong Univ, Dept Oncol, Affiliated Hosp 2, Xian, Peoples R China
[2] Xi An Jiao Tong Univ, Dept Orthoped, Affiliated Hosp 2, Xian, Peoples R China
基金
中国国家自然科学基金;
关键词
cuproptosis; breast cancer; prognostic signature; tumor immune microenvironment; bioinformatics; TUMOR MICROENVIRONMENT; TRACE-ELEMENTS; SERUM-LEVELS; COPPER; ZINC; TETRATHIOMOLYBDATE; DISULFIRAM; EXPRESSION; SELENIUM; SUBSETS;
D O I
10.3389/fgene.2022.977322
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
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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页数:15
相关论文
共 69 条
[11]   Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade [J].
Charoentong, Pornpimol ;
Finotello, Francesca ;
Angelova, Mihaela ;
Mayer, Clemens ;
Efremova, Mirjana ;
Rieder, Dietmar ;
Hackl, Hubert ;
Trajanoski, Zlatko .
CELL REPORTS, 2017, 18 (01) :248-262
[12]   Identification of a pyroptosis-related prognostic signature in breast cancer [J].
Chen, Hanghang ;
Luo, Haihua ;
Wang, Jieyan ;
Li, Jinming ;
Jiang, Yong .
BMC CANCER, 2022, 22 (01)
[13]   PTBP1 modulates osteosarcoma chemoresistance to cisplatin by regulating the expression of the copper transporter SLC31A1 [J].
Cheng, Cheng ;
Ding, Qiuyue ;
Zhang, Zhicai ;
Wang, Shangyu ;
Zhong, Binlong ;
Huang, Xin ;
Shao, Zengwu .
JOURNAL OF CELLULAR AND MOLECULAR MEDICINE, 2020, 24 (09) :5274-5289
[14]   A Prognostic Signature Consisting of Pyroptosis-Related Genes and SCAF11 for Predicting Immune Response in Breast Cancer [J].
Chu, Ling ;
Yi, Qiaoli ;
Yan, Yuanliang ;
Peng, Jinwu ;
Li, Zhilan ;
Jiang, Feng ;
He, Qingchun ;
Ouyang, Lingzi ;
Wu, Shangjun ;
Fu, Chencheng ;
Liu, Ying ;
Xu, Zhijie .
FRONTIERS IN MEDICINE, 2022, 9
[15]   Wilson disease [J].
Czlonkowska, Anna ;
Litwin, Tomasz ;
Dusek, Petr ;
Ferenci, Peter ;
Lutsenko, Svetlana ;
Medici, Valentina ;
Rybakowski, Janusz K. ;
Weiss, Karl Heinz ;
Schilsky, Michael L. .
NATURE REVIEWS DISEASE PRIMERS, 2018, 4
[16]   Identification of a novel immune-related prognostic signature associated with tumor microenvironment for breast cancer [J].
Ding, Shuning ;
Sun, Xi ;
Zhu, Li ;
Li, Yafen ;
Chen, Weiguo ;
Shen, Kunwei .
INTERNATIONAL IMMUNOPHARMACOLOGY, 2021, 100
[17]  
Emens LA, 2012, EXPERT REV ANTICANC, V12, P1597, DOI [10.1586/ERA.12.147, 10.1586/era.12.147]
[18]   CD8+ cytotoxic T lymphocytes in cancer immunotherapy: A review [J].
Farhood, Bagher ;
Najafi, Masoud ;
Mortezaee, Keywan .
JOURNAL OF CELLULAR PHYSIOLOGY, 2019, 234 (06) :8509-8521
[19]   An introduction to ROC analysis [J].
Fawcett, Tom .
PATTERN RECOGNITION LETTERS, 2006, 27 (08) :861-874
[20]   Regularization Paths for Generalized Linear Models via Coordinate Descent [J].
Friedman, Jerome ;
Hastie, Trevor ;
Tibshirani, Rob .
JOURNAL OF STATISTICAL SOFTWARE, 2010, 33 (01) :1-22