Prediction of target genes and establishment of related prognostic model for the treatment of glioblastoma with stigmasterol
- VernacularTitle:豆甾醇治疗胶质母细胞瘤靶基因预测及相关预后模型的建立
- Author:
Qiang ZHU
1
;
Ruichun LI
2
;
Shiwen GUO
2
;
Chen LIANG
2
Author Information
- Publication Type:Journal Article
- Keywords: stigmasterol; glioblastoma (GBM); prognostic model
- From: Journal of Xi'an Jiaotong University(Medical Sciences) 2024;45(6):909-917
- CountryChina
- Language:Chinese
- Abstract: [Objective] To predict potential target genes for the treatment of glioblastoma (GBM) with stigmasterol and construct a relevant prognostic model, in order to reveal its antiglioma mechanism and the role of these target genes in the prognosis of GBM patients. [Methods] Differential expression genes in GBM and stigmasterol target genes were obtained via online databases. Venn diagram was used to select potential target genes for stigmasterol treatment of GBM, and enrichment analysis was performed using R language. Univariate COX regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were made to select stigmasterol target genes related to the prognosis of GBM patients and construct a relevant prognostic model. Real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) and Western blotting analyses were used to detect the effect of stigmasterol on the expressions of related target genes. [Results] In this study, a total of 31 potential target genes for the treatment of GBM with stigmasterol were identified. Enrichment analysis showed that these target genes were associated with the activation of the G protein coupled receptor (GPCR) signaling pathway and the regulation of lipid metabolism. Regression analysis identified two stigmasterol target genes, namely, fatty acid binding protein 5 (FABP5) and alpha 1B adrenergic receptor (ADRA1B), which are associated with the prognosis of GBM. A prognostic model constructed based on these two genes could accurately predict the prognosis of GBM patients. Finally, stigmasterol inhibited the expressions of these two genes in GBM cells (FABP5: t=9.909, P=0.001; ADRA1B: t=3.319, P=0.029). [Conclusion] Stigmasterol’s anti-tumor effect may be linked to its regulation of GPCR signaling pathways and lipid metabolism. By inhibiting the expressions of FABP5 and ADRA1B, stigmasterol could potentially enhance the prognosis for GBM patients. Additionally, a prognostic model based on the expression levels of FABP5 and ADRA1B can be valuable for predicting patient outcomes and monitoring therapeutic efficacy in GBM.
