Disulfidptosis-related lncRNA prognosis model to predict survival therapeutic response prediction in lung adenocarcinoma

被引:1
|
作者
Sun, Xiaoming [1 ]
Li, Jia [2 ]
Gao, Xuedi [3 ]
Huang, Yubin [4 ]
Pang, Zhanyue [1 ]
Lv, Lin [2 ]
Li, Hao [4 ]
Liu, Haibo [1 ]
Zhu, Liangming [2 ]
机构
[1] Jinan Cent Hosp, Dept Thorac Surg, Jinan 250013, Shandong, Peoples R China
[2] Shandong Univ, Jinan Cent Hosp, Dept Thorac Surg, 105 Jie Fang Rd, Jinan 250013, Shandong, Peoples R China
[3] Jinan Mingshui Eye Hosp, Dept Ophthalmol, Jinan 250200, Shandong, Peoples R China
[4] Shandong First Med Univ, Jinan Cent Hosp, Dept Thorac Surg, Jinan 250013, Shandong, Peoples R China
关键词
lung adenocarcinoma; disulfidptosis; lncRNA; disulfidptosis-related lncRNA; disulfidptosis related lncRNA signature; TUMOR IMMUNE MICROENVIRONMENT; CELL; ORGANIZATION; ACTIN;
D O I
10.3892/ol.2024.14476
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, and disulfidptosis is a newly discovered mechanism of programmed cell death. However, the effects of disulfidptosis-related lncRNAs (DR-lncRNAs) in LUAD have yet to be fully elucidated. The aim of the present study was to identify and validate a novel lncRNA-based prognostic marker that was associated with disulfidptosis. RNA-sequencing and associated clinical data were obtained from The Cancer Genome Atlas database. Univariate Cox regression and lasso algorithm analyses were used to identify DR-lncRNAs and to establish a prognostic model. Kaplan-Meier curves, receiver operating characteristic curves, principal component analysis, Cox regression, nomograms and calibration curves were used to assess the reliability of the prognostic model. Functional enrichment analysis, immune infiltration analysis, somatic mutation analysis, tumor microenvironment and drug predictions were applied to the risk model. Reverse transcription-quantitative PCR was subsequently performed to validate the mRNA expression levels of the lncRNAs in normal cells and tumor cells. These analyses enabled a DR-lncRNA prognosis signature to be constructed, consisting of nine lncRNAs; U91328.1, LINC00426, MIR1915HG, TMPO-AS1, TDRKH-AS1, AL157895.1, AL512363.1, AC010615.2 and GCC2-AS1. This risk model could serve as an independent prognostic tool for patients with LUAD. Numerous immune evaluation algorithms indicated that the low-risk group may exhibit a more robust and active immune response against the tumor. Moreover, the tumor immune dysfunction exclusion algorithm suggested that immunotherapy would be more effective in patients in the low-risk group. The drug-sensitivity results showed that patients in the high-risk group were more sensitive to treatment with crizotinib, erlotinib or savolitinib. Finally, the expression levels of AL157895.1 were found to be lower in A549. In summary, a novel DR-lncRNA signature was constructed, which provided a new index to predict the efficacy of therapeutic interventions and the prognosis of patients with LUAD.
引用
收藏
页数:21
相关论文
共 50 条
  • [41] A novel disulfidptosis-related LncRNA prognostic risk model: predicts the prognosis, tumor microenvironment and drug sensitivity in esophageal squamous cell carcinoma
    Ye, Chunlin
    Xu, Chuan
    Tang, Yongchao
    Qi, Yingcheng
    Peng, Xiaoyue
    Wei, Guangxia
    Jiang, Lei
    BMC GASTROENTEROLOGY, 2024, 24 (01)
  • [42] Disulfidptosis-related gene SLC7A11 predicts prognosis and indicates tumor immune infiltration in lung adenocarcinoma
    Zhu, Jing
    Ge, Hui
    Chen, Yinsong
    Zhang, She
    Wu, Junjie
    Nai, Weiping
    Min, Lingfeng
    TRANSLATIONAL CANCER RESEARCH, 2024, 13 (09) : 5064 - 5072
  • [43] Identification of disulfidptosis-related subgroups and prognostic signatures in lung adenocarcinoma using machine learning and experimental validation
    Wang, Yuzhi
    Xu, Yunfei
    Liu, Chunyang
    Yuan, Chengliang
    Zhang, Yi
    FRONTIERS IN IMMUNOLOGY, 2023, 14
  • [44] Signature Construction and Disulfidptosis-Related Molecular Cluster Identification for Better Prediction of Prognosis in Glioma
    Zhuang, Yekun
    Chen, Jiewen
    Mai, Zhuohao
    Huang, Wanting
    Zhong, Wenyu
    JOURNAL OF MOLECULAR NEUROSCIENCE, 2024, 74 (02)
  • [45] A novel cuproptosis-related lncRNA signature to predict prognosis and immune landscape of lung adenocarcinoma
    Wang, Xinyi
    Jing, Hui
    Li, Hecheng
    TRANSLATIONAL LUNG CANCER RESEARCH, 2023, 12 (02) : 230 - +
  • [46] Predictive value of cuproptosis and disulfidptosis-related lncRNA in head and neck squamous cell carcinoma prognosis and treatment
    Liao, Hongming
    He, Benchao
    HELIYON, 2024, 10 (18)
  • [47] Integrated Bioinformatics and Experimental Validation to Identify a Disulfidptosis-Related lncRNA Model for Prognostic Prediction in Papillary Renal Cell Carcinoma
    Zhu, Yidong
    Jin, Xiaoyi
    Liu, Jun
    COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING, 2024, : 883 - 898
  • [48] Development of a disulfidptosis-related prognostic model for endometrial cancer with potential therapeutic target
    Li, Chunmei
    Fan, Xuefei
    Wang, Xue
    Yao, Yulan
    Huang, Bing
    Chen, Linlin
    Cao, Lu
    Peng, Tao
    Lin, Yingying
    Cai, Rong
    DISCOVER ONCOLOGY, 2024, 15 (01)
  • [49] Exploring the role of disulfidptosis-related signatures in immune microenvironment, prognosis and therapeutic strategies of cervical cancer
    Jin, Tianzhe
    Yin, Taotao
    Xu, Ruiyi
    Liu, Hong
    Yuan, Shuo
    Xue, Yite
    Zhang, Jianwei
    Wang, Hui
    TRANSLATIONAL ONCOLOGY, 2024, 44
  • [50] Correlation analysis of disulfidptosis-related gene signatures with clinical prognosis and immunotherapy response in sarcoma
    Xu, Juan
    Guo, Kangwen
    Sheng, Xiaoan
    Huang, Yuting
    Wang, Xuewei
    Dong, Juanjuan
    Qin, Haotian
    Wang, Chao
    SCIENTIFIC REPORTS, 2024, 14 (01)