Bioinformatics-based Identification of Cuproptosis Genes Associated with Prognosis and Immune Microenvironment in Lung Cancer

Yang LI; Wen JIANG; Rong LIU; Chaomin LIU; Longyu XU; Wenjing ZHANG

doi:10.12259/j.issn.2095-610X.S20250405

Volume 46 Issue 4

Apr. 2025

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Article Navigation > Journal of Kunming Medical University > 2025 > 46(4): 29-35

Yang LI, Wen JIANG, Rong LIU, Chaomin LIU, Longyu XU, Wenjing ZHANG. Bioinformatics-based Identification of Cuproptosis Genes Associated with Prognosis and Immune Microenvironment in Lung Cancer[J]. Journal of Kunming Medical University, 2025, 46(4): 29-35. doi: 10.12259/j.issn.2095-610X.S20250405

Citation:

Yang LI, Wen JIANG, Rong LIU, Chaomin LIU, Longyu XU, Wenjing ZHANG. Bioinformatics-based Identification of Cuproptosis Genes Associated with Prognosis and Immune Microenvironment in Lung Cancer[J]. Journal of Kunming Medical University, 2025, 46(4): 29-35. doi: 10.12259/j.issn.2095-610X.S20250405

Citation:

Yang LI, Wen JIANG, Rong LIU, Chaomin LIU, Longyu XU, Wenjing ZHANG. Bioinformatics-based Identification of Cuproptosis Genes Associated with Prognosis and Immune Microenvironment in Lung Cancer[J]. Journal of Kunming Medical University, 2025, 46(4): 29-35. doi: 10.12259/j.issn.2095-610X.S20250405

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Bioinformatics-based Identification of Cuproptosis Genes Associated with Prognosis and Immune Microenvironment in Lung Cancer

doi: 10.12259/j.issn.2095-610X.S20250405

1.
Medical School，Kunming University of Science and Technology，Kunming Yunnan 650031
2.
Department of Thoracic Surgery
3.
Department of Oncology, The First People’s Hospital of Yunnan Province/Affiliated Hospital of Kunming University of Science and Technology，Kunming Yunnan 650032，China

Received Date: 2024-11-11
Available Online: 2025-04-05
Publish Date: 2025-04-25

Abstract

Abstract

Objective To identify the cuproptosis genes associated with prognosis and immune microenvironment in lung cancer with the use of bioinformatics. Methods The lung cancer dataset used in this study was obtained from the TCGA database. The cuproptosis-related genes （CRGs） were obtained from the previously reported literature. The R software Deseq2 package was used to identify the differentially expressed genes （DEGs） in lung cancer. The intersection of DEGs and CRGs was taken to obtain the differentially expressed CRGs （DE-CRGs）. COX analysis and R software rms package were used to identify DE-CRGs associated with the prognosis of lung cancer. Estimate and Cibersort algorithms were applied to identify the correlation of DE-CRGs with the immune microenvironment. Results Compared to the normal tissues, a total of 5, 269 DEGs were present in lung cancer tissues in the TCGA database, and there were 11 shared genes between DEGs and CRGs. The 11 DE-CRGs mainly regulated the energy metabolism, carbon metabolism and amino acid metabolism. In the DE-CRGs, LIPT1 was an independent risk factor for lung cancer, and the column chart constructed with the clinical features （age, TNM staging, and residual tumor） predicted the survival of lung cancer patients in a manner similar to their actual outcomes. LIPT1 showed a positive correlation with the infiltration of M1 and M2 type macrophages, activated natural killer cells cells and CD8⁺ T cells, and showed a significant negative correlation with M0 type macrophages, activated mast cells, neutrophils and Treg cells （P < 0.05）. Conclusion LIPT1 may serve as a prognostic and immune microenvironment-associated cuproptosis gene, which is a novel biomarker for lung cancer therapy.
- Lung cancer,
- Bioinformatics,
- Cuproptosis,
- Prognosis,
- Immune microenvironment

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