Identification of cuproptosis and immune-related gene prognostic signature in lung adenocarcinoma

被引:8
|
作者
Zhang, Wentao [1 ]
Qu, Haizeng [2 ]
Ma, Xiaoqing [3 ]
Li, Liang [4 ]
Wei, Yanjun [5 ]
Wang, Ye [6 ]
Zeng, Renya [1 ]
Nie, Yuanliu [6 ]
Zhang, Chenggui [7 ]
Yin, Ke [8 ]
Zhou, Fengge [1 ]
Yang, Zhe [1 ]
机构
[1] Shandong First Med Univ, Tumor Res & Therapy Ctr, Shandong Prov Hosp, Jinan, Shandong, Peoples R China
[2] Dongming Peoples Hosp, Radiotherapy Dept, Heze, Shandong, Peoples R China
[3] Shandong First Med Univ, Radiotherapy & Minimally Invas Grp 1, Affiliated Hosp 2, Tai An, Shandong, Peoples R China
[4] Shandong Univ, Shandong Prov Hosp, Cheeloo Coll Med, Dept Thorac Surg, Shandong, Peoples R China
[5] Weifang Peoples Hosp, Dept Radiat Oncol, Weifang, Peoples R China
[6] Shandong Univ, Shandong Prov Hosp, Cheeloo Coll Med, Tumor Res & Therapy Ctr, Jinan, Shandong, Peoples R China
[7] Shandong First Med Univ, Dept Orthoped, Shandong Prov Hosp, Jinan, Shandong, Peoples R China
[8] Shandong Univ, Shandong Prov Hosp, Cheeloo Coll Med, Dept Pathol, Jinan, Shandong, Peoples R China
来源
FRONTIERS IN IMMUNOLOGY | 2023年 / 14卷
关键词
cuproptosis; immune; LUAD; prognosis; signature; INHIBITOR PROTEIN EXPRESSION; TYROSINE KINASE 2; TCA CYCLE; TUMOR MICROENVIRONMENT; CANCER; COPPER; PYK2; PROGRESSION; METASTASIS; RKIP;
D O I
10.3389/fimmu.2023.1179742
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
BackgroundCuproptosis is a novel form of programmed cell death that differs from other types such as pyroptosis, ferroptosis, and autophagy. It is a promising new target for cancer therapy. Additionally, immune-related genes play a crucial role in cancer progression and patient prognosis. Therefore, our study aimed to create a survival prediction model for lung adenocarcinoma patients based on cuproptosis and immune-related genes. This model can be utilized to enhance personalized treatment for patients. MethodsRNA sequencing (RNA-seq) data of lung adenocarcinoma (LUAD) patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The levels of immune cell infiltration in the GSE68465 cohort were determined using gene set variation analysis (GSVA), and immune-related genes (IRGs) were identified using weighted gene coexpression network analysis (WGCNA). Additionally, cuproptosis-related genes (CRGs) were identified using unsupervised clustering. Univariate COX regression analysis and least absolute shrinkage selection operator (LASSO) regression analysis were performed to develop a risk prognostic model for cuproptosis and immune-related genes (CIRGs), which was subsequently validated. Various algorithms were utilized to explore the relationship between risk scores and immune infiltration levels, and model genes were analyzed based on single-cell sequencing. Finally, the expression of signature genes was confirmed through quantitative real-time PCR (qRT-PCR), immunohistochemistry (IHC), and Western blotting (WB). ResultsWe have identified 5 Oncogenic Driver Genes namely CD79B, PEBP1, PTK2B, STXBP1, and ZNF671, and developed proportional hazards regression models. The results of the study indicate significantly reduced survival rates in both the training and validation sets among the high-risk group. Additionally, the high-risk group displayed lower levels of immune cell infiltration and expression of immune checkpoint compared to the low-risk group.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Cuproptosis and Immune-Related Gene Signature Predicts Immunotherapy Response and Prognosis in Lung Adenocarcinoma
    Sun, Zihao
    Chen, Xiujing
    Huang, Xiaoning
    Wu, Yanfen
    Shao, Lijuan
    Zhou, Suna
    Zheng, Zhu
    Lin, Yiguang
    Chen, Size
    LIFE-BASEL, 2023, 13 (07):
  • [2] Identification of a cuproptosis-related lncRNA prognostic signature in lung adenocarcinoma
    Chen, Ran
    Luo, Haichao
    Chen, Qitian
    Wang, Changying
    CLINICAL & TRANSLATIONAL ONCOLOGY, 2023, 25 (06) : 1617 - 1628
  • [3] Identification and Validation of Immune-Related LncRNA Prognostic Signature for Lung Adenocarcinoma
    Wu, Guomin
    Wang, Qihao
    Zhu, Ting
    Fu, Linhai
    Li, Zhupeng
    Wu, Yuanlin
    Zhang, Chu
    FRONTIERS IN GENETICS, 2021, 12
  • [4] Identification of a RNA-Seq Based Prognostic Signature with Seven Immune-Related lncRNAs for Lung Adenocarcinoma
    You, Jianbin
    Fang, Wenting
    Zhao, Qiurong
    Chen, Liqing
    Chen, Liangyuan
    Chen, Falin
    CLINICAL LABORATORY, 2021, 67 (03) : 785 - 795
  • [5] Construction and validation of a prognostic and therapeutic cuproptosis- and immune-related gene signature in hepatocellular carcinoma
    Cheng, Qianqian
    Wang, Wei
    Lv, Zhenyu
    Ji, Wenbin
    Liu, Jing
    Zhou, Xueli
    Yang, Yan
    TRANSLATIONAL CANCER RESEARCH, 2024, 13 (06) : 2629 - 2646
  • [6] Identification of immune-related gene signature predicting survival in the tumor microenvironment of lung adenocarcinoma
    Zhao, Mengnan
    Li, Ming
    Chen, Zhencong
    Bian, Yunyi
    Zheng, Yuansheng
    Hu, Zhengyang
    Liang, Jiaqi
    Huang, Yiwei
    Yin, Jiacheng
    Zhan, Cheng
    Feng, Mingxiang
    Wang, Qun
    IMMUNOGENETICS, 2020, 72 (9-10) : 455 - 465
  • [7] Identification of a cuproptosis-related lncRNA prognostic signature in lung adenocarcinoma
    Ran Chen
    Haichao Luo
    Qitian Chen
    Changying Wang
    Clinical and Translational Oncology, 2023, 25 : 1617 - 1628
  • [8] Establishment of Immune-related Gene Pair Signature to Predict Lung Adenocarcinoma Prognosis
    Jiang, Xueping
    Gao, Yanping
    Zhang, Nannan
    Yuan, Cheng
    Luo, Yuan
    Sun, Wenjie
    Zhang, Jianguo
    Ren, Jiangbo
    Gong, Yan
    Xie, Conghua
    CELL TRANSPLANTATION, 2020, 29
  • [9] A novel prognostic signature of immune-related lncRNA pairs in lung adenocarcinoma
    Liu, Yang
    Wu, Qiuhong
    Fan, Xuejiao
    Li, Wen
    Li, Xiaogang
    Zhu, Hui
    Zhou, Qinghua
    Yu, Jinming
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [10] Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma
    Lv, Yanju
    Xiao, Yajie
    Cui, Xiaoli
    Luo, Haitao
    Xu, Long
    FRONTIERS IN GENETICS, 2022, 13