AUTHOR=Guo Kai , Duan Xinxin , Zhao Jiahui , Sun Boyu , Liu Xiaoming , Zhao Zongmao
TITLE=A novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk RNA sequencing
JOURNAL=Frontiers in Molecular Biosciences
VOLUME=9
YEAR=2022
URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2022.984712
DOI=10.3389/fmolb.2022.984712
ISSN=2296-889X
ABSTRACT=Background: Glioma is the most fatal neoplasm among the primary intracranial cancers. Necroptosis, a form of programmed cell death, is correlated with tumor progression and immune response. But, the role of necroptosis-related genes (NRGs) in glioma has not been well-uncovered.
Methods: Single-cell and bulk RNA sequencing data, obtained from publicly accessed databases, were used to establish a necroptosis-related gene signature for predicting the prognosis of glioma patients. Multiple bioinformatics algorithms were conducted to evaluate the efficacy of the signature. The relative mRNA level of each signature gene was validated by quantitative real-time reverse transcription PCR (qRT-PCR) in glioma cell lines compared to human astrocytes.
Results: In this predicted prognosis model, patients with a high risk score showed a shorter overall survival, which was verified in the testing cohorts. The signature risk score was positively related with immune cell infiltration and some immune check points, such as CD276 (B7-H3), CD152 (CTLA-4), CD223 (LAG-3), and CD274 (PD-L1). Single-cell RNA sequencing analysis confirmed that the glioma microenvironment consists of various immune cells with different markers. The eight NRGs of the signature were detected to be expressed in several immune cells. QRT-PCR results verified that all the eight signature genes were differentially expressed between human astrocytes and glioma cells.
Conclusion: The eight NRGs correlate with the immune microenvironment of glioma according to our bioinformatics analysis. This necroptosis-related gene signature may evaluate the precise methodology of predicting prognosis of glioma and provide a novel thought in glioma investigation.