Identification of TNFAIP6 as a reliable prognostic indicator of low-grade glioma

• Published in: Heliyon Vol. 10; no. 12; p. e33030
• Main Authors: Huang, Qinhong, Liang, Hui, Shi, Shenbao, Ke, Yiquan, Wang, Jihui
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 30.06.2024; Elsevier
• Subjects: Glioma immune microenvironment; Glioma stem cell-related genes; Low-grade glioma; Machine learning; TNFAIP6; Glioma immune microenvironment; TNFAIP6; Glioma stem cell-related genes; Low-grade glioma; Machine learning
• ISSN: 2405-8440; 2405-8440
• DOI: 10.1016/j.heliyon.2024.e33030

Glioma is the most common primary malignant tumor in the brain, characterizing by high disability rate and high recurrence rate. Although low-grade glioma (LGG) has a relative benign biological behavior, the prognosis of LGG patients still varies greatly. Glioma stem cells (GSCs) are considered as the chief offenders of glioma cell proliferation, invasion and resistance to therapies. Our study screened a series of glioma stem cell-related genes (GSCRG) based on mDNAsi and WCGNA, and finally established a reliable single-gene prognostic model through 101 combinations of 10 machine learning methods. Our result suggested that the expression level of TNFAIP6 is negatively correlated with the prognosis of LGG patients, which may be the result of pro-cancer signaling pathways activation and immunosuppression. In general, this study revealed that TNFAIP6 is a robust and valuable prognostic factor in LGG, and may be a new target for LGG treatment.