Non-small cell lung cancer (NSCLC) remains a leading cause of cancer mortality, and it remains challenging to predict immunotherapy responses. This study integrates RNA sequencing data from five NSCLC immunotherapy cohorts to identify three molecular subtypes, with a copper-dependent proliferation subtype showing poor prognosis and an immunosuppressive tumor microenvironment. We developed a prognostic model that stratifies patients into high- and low-risk groups by a machine learning pipeline combining 101 algorithmic models. The low-risk group exhibited higher immune infiltration and better progression-free survival, characterized by activation of immune-related pathways, such as IL-2/STAT5 and IFN-γ signaling. CEACAM5(+) epithelial cells were identified as a high-risk subgroup linked to poorer survival and immunotherapy response via mapping the score of the model and clinical information into single-cell sequencing data. Finally, analysis of clinical specimens with different immunotherapy responses confirmed, by western blot and immunohistochemistry, that expression of CEACAM5(+) epithelial cells related markers was significantly higher in epithelial cells of the non-MPR group compared with the MPR group. Our findings highlight the importance of genes related to cuproptosis and copper hemostasis as biomarkers for immunotherapy prediction and prognosis stratification.
Integrative analysis reveals prognostic value of cuproptosis and copper hemostasis related genes in immunotherapy for non-small cell lung cancer.
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作者:Dong Dong, Wang Yaxin, Lu Tong, Han Yichao, Shi Liqiang, Cao Yuqin, Zhang Jiahao, Zhang Yajie, Li Hecheng
| 期刊: | npj Precision Oncology | 影响因子: | 8.000 |
| 时间: | 2025 | 起止号: | 2025 Nov 20; 9(1):368 |
| doi: | 10.1038/s41698-025-01138-7 | ||
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