Hao Huang,1 Zhiping Long,2 Ying Deng,3 Zhicong Huang,3 Zhonghua Lv,4 Qian Sun,4 Hui Liu,4 Hongsheng Liang,5 Fulan Hu6 

1Department of Preventive Medicine, Zhuhai Campus of Zunyi Medical University, Zhuhai, Guangdong, People’s Republic of China; 2Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, Heilongjiang, People’s Republic of China; 3Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, People’s Republic of China; 4Department of Neurosurgery, Third Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People’s Republic of China; 5Department of Neurosurgery, First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People’s Republic of China; 6Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China

Correspondence: Fulan Hu, Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China, Email hufu1525@163.com Hao Huang, Department of Preventive Medicine, Zhuhai Campus of Zunyi Medical University, Zhuhai, Guangdong, People’s Republic of China, Email hhxiaowo@163.com

Purpose: Mitochondrial metabolism is essential for energy production and the survival of brain cells, particularly in astrocytes. Cuproptosis is a newly identified form of programmed cell death that occurs due to the disruption of mitochondrial metabolism caused by excessive copper toxicity. However, the relationship between cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) and the prognosis of gliomas remains unclear.
Patients and Methods: In this study, we utilized 32,293 cells obtained from three in-house single-cell RNA sequencing (scRNA-seq) datasets, along with 6,148 cells acquired from the Chinese Glioma Genome Atlas (CGGA) involving 14 glioma patients, to identify and validate the TME of gliomas.
Results: Based on an analysis of 32,293 single cells, we investigated intra-tumor heterogeneity, intercellular communication, and astrocyte differentiation trajectories in gliomas. Our findings revealed that the TGFβ signaling pathway exhibited a higher relative strength in astrocyte subpopulations. Additionally, we identified a novel three-gene signature (CDKN2A, SOX2, and MPC1) was identified for prognostic prediction. Furthermore, glioma patients with a high-risk score demonstrated poorer overall survival (OS) compared to those with a low-risk score in both training and testing datasets (Ptraining set < 0.001; Ptest set = 0.037).
Conclusion: Our study revealed the prognostic value of the CRGs in astrocytes exhibiting tumor immunosuppressive characteristics in glioma. We established a novel three-gene prognostic model that offers new insights into the prognosis and treatment strategies for gliomas.

Keywords: scRNA-seq, gliomas, astrocyte, cuproptosis, prognosis