Pharmacogenomics and Personalized Medicine (Jun 2024)

Cuproptosis-Related lncRNA Predict Prognosis and Immune Response of LUAD

  • Zhou Q,
  • Liu Y,
  • Gao Y,
  • Quan L,
  • Wang L,
  • Wang H

Journal volume & issue
Vol. Volume 17
pp. 319 – 336

Abstract

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Qianhui Zhou,1 Yi Liu,1 Yan Gao,1 Lingli Quan,1 Lin Wang,1 Hao Wang2 1Department of Respiratory and Critical Care Medicine, Zhuzhou Central Hospital, Zhuzhou, 412000, People’s Republic of China; 2Department of Urology, The First Affiliated Hospital, Hengyang Medical School, University of South China, HengYang, Hunan, 421005, People’s Republic of ChinaCorrespondence: Hao Wang, Email [email protected]: Lung cancer is the leading cause of cancer deaths worldwide, primarily due to lung adenocarcinoma (LUAD). However, the heterogeneity of programmed cell death results in varied prognostic and predictive outcomes. This study aimed to develop an LUAD evaluation marker based on cuproptosis-related lncRNAs.Methods: First, transcriptome data and clinical data related to LUAD were downloaded from the Cancer Genome Atlas (TCGA), and cuproptosis-related genes were analyzed to identify cuproptosis-related lncRNAs. Univariate, LASSO, and multivariate Cox regression analyses were conducted to construct cuproptosis-associated lncRNA models. LUAD patients were categorized into high-risk and low-risk groups using prognostic risk values. Kaplan-Meier analysis, PCA, GSEA, and nomograms were employed to evaluate and validate the results.Results: 7 cuproptosis-related lncRNAs were identified, and a risk model was created. High-risk tumors exhibited cuproptosis-related gene alterations in 95.54% of cases, while low-risk tumors showed alterations in 85.65% of cases, mainly involving TP53. The risk value outperformed other clinical variables and tumor mutation burden as a predictor of 1-, 3-, and 5-year overall survival. The cuproptosis-related lncRNA-based risk model demonstrated high validity for LUAD evaluation, potentially influencing individualized treatment approaches. Expression analysis of four candidate cuproptosis-related lncRNAs (AL606834.1, AL161431.1, AC007613.1, and LINC02835) in LUAD tissues and adjacent normal tissues revealed significantly higher expression levels of AL606834.1 and AL161431.1 in LUAD tissues, positively correlating with tumor stage, lymph node metastasis, and histopathological grade. Conversely, AC007613.1 and LINC02835 exhibited lower expression levels, negatively correlating with these factors. High expression of AL606834.1 and AL161431.1 indicated poor prognosis, while low expression of AC007613.1 and LINC02835 was associated with unfavorable outcomes. Univariate and multivariate analyses confirmed these lncRNAs as independent risk factors for LUAD prognosis.Conclusion: The 4 cuproptosis-related (lncRNAsAL606834.1, AL161431.1, AC007613.1, and LINC02835) can accurately predict the prognosis of patients with LUAD and may provide new insights into clinical applications and immunotherapy.Keywords: lung adenocarcinoma, tumor mutation load, cuproptosis, long noncoding RNA, immunotherapeutic response

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