ISSN: 1837-9664Journal of Cancer
Global reach, higher impact
J Cancer 2024; 15(9):2486-2504. doi:10.7150/jca.94200 This issue Cite
Research Paper
Identification of PANoptosis-related predictors for prognosis and tumor microenvironment by multiomics analysis in glioma
1. College of Biomedicine and Health, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, China.
2. Center for Neurological Disease Research, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
3. Department of Neurosurgery, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
4. Central Laboratory, Hubei Cancer Hospital, Wuhan, China.
5. Department of Radiation Oncology, Hubei Cancer Hospital, Wuhan, China.
Abstract
PANoptosis is a newly described inflammatory programmed cell death, that highlights coordination between pyroptosis, apoptosis and necroptosis. However, the functions of PANoptosis-related genes in glioma progression still remain to be explored. This study aims to identify PANoptosis-related predictors that may be utilized for prognosis prediction and development of new therapeutic targets. Firstly, bulk and single-cell RNA-seq (scRNA-seq) data of glioma patients were extracted from TCGA, CGGA and GEO database. Genetic analysis indicates a considerably high mutation frequency of PANoptosis-related genes (PANRGs) in glioma. Consensus clustering was applied to reveal different subtypes of glioma based on PANRGs. Two PANoptosis subtypes with distinct prognostic and TME characteristics were identified. Then, with LASSO-Cox regression analysis, four PANoptosis-related predictors (MYBL2, TUBA1C, C21orf62 and KCNIP2) were determined from bulk and scRNA-seq analysis. Predictive PANRG score model was established with these predictors and its correlation with tumor microenvironment (TME) was investigated. The results showed that patients with low PANRG score, had higher infiltration of anti-tumor immune cells, higher MSI score and lower TIDE score, which are more likely to benefit from immunotherapy. Further analysis identified 16 potential drugs associated with PANoptosis-related predictors. Moreover, the expression levels of four PANoptosis-related predictors were examined in clinical samples and the results were consistent with those analyzed in the database. Besides, we also confirmed the biological functions of two oncogenic predictors (MYBL2 and TUBA1C) by cell experiments, which revealed that knockdown of MYBL2 or TUBA1C could significantly inhibit the proliferation and migration of glioma cells. These findings highlight the prognostic value and biological functions of PANRGs in glioma, which may provide valuable insights for individualized treatment.
Keywords: Glioma, PANoptosis, Tumor immune microenvironment, Prognostic model, MYBL2, TUBA1C
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