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pmid:36338763
Comprehensive analysis of the cuproptosis-related model to predict prognosis and indicate tumor immune infiltration in lung adenocarcinoma.
Minle Wu · Jie Bao · Youfeng Lei · Shuai Tao · Qiurong Lin · Liang Chen · Yinpeng Jin · Xiaohong Ding · Yufeng Yan · Ping Han
Frontiers in oncology · 2022 doi:10.3389/fonc.2022.935672
Paper
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Experiment
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Data
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Analysis
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Execution
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Complete file
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However, the roles of cuproptosis-associated genes (CAGs) in lung adenocarcinoma (LUAD) have not been explored comprehensively.\nMethods: We obtained CAGs and utilized consensus molecular clustering by \"non-negative matrix factorization (NMF)\" to stratify LUAD patients in TCGA (N = 511), GSE13213 (N = 117), and GSE31210 (N = 226) cohorts. The ssGSEA and CIBERSORT algorithms were used to evaluate the relative infiltration levels of immune cell types in tumor microenvironment (TME). The risk score based on CAGs was calculated to predict patients' survival outcomes.\nResults: We identified three cuproptosis-associated clusters with different clinicopathological characteristics. We found that the cuproptosis-associated cluster with the worst survival rates exhibited a high enrichment of activated CD4/8+ T cells. In addition, we found that the cuproptosis-associated risk score could be used for patients' prognosis prediction and provide new insights in immunotherapy of LUAD patients. 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