The activity of cuproptosis pathway calculated by AUCell algorithm was employed to construct cuproptosis landscape in lung adenocarcinoma

作者：Weixian Lin, Jiaren Wang, Jing Ge, Rui Zhou, Ya‐Hui Hu, Lushan Xiao, Quanzhou Peng, Zemao Zheng · 发表于：Discover Oncology · 年份：2023 · DOI：10.1007/s12672-023-00755-7 · 被引用次数：15 · 研究领域：Ferroptosis and cancer prognosis、Cancer, Lipids, and Metabolism、Cancer Genomics and Diagnostics

Cuproptosis is a recently described copper-dependent cell death pathway. Consequently, there are still few studies on lung adenocarcinoma (LUAD)-related cuproptosis, and we aimed to deepen in this matter. In this study, data from 503 patients with lung cancer from the TCGA-LUAD cohort data collection and 11 LUAD single-cells from GSE131907 as well as from 10 genes associated with cuproptosis were analyzed. The AUCell R package was used to determine the copper-dependent cell death pathway activity for each cell subpopulation, calculate the CellChat score, and display cell communication for each cell subpopulation. The PROGENy score was calculated to show the scores of tumor-related pathways in different cell populations. GO and KEGG analyses were used to calculate pathway activity. Univariate COX and random forest analyses were used to screen prognosis-associated genes and construct models. The ssGSEA and xCell algorithms were used to calculate the immunocyte infiltration score. Based on data from the GDSC database, the drug sensitivity score was calculated using oncoPredict. Finally, in vitro experiments were performed to determine the role of TLE1, the most important gene in the prognostic model. The 11 LUAD single-cell samples were classified into 8 different cell populations, from which epithelial cells showed the highest copper-dependent cell death pathway activity. Epithelial cell subsets were significantly positively correlated with MAKP, hypoxia, and other pathways. In...