Abstract

To construct a risk model using 760 tumor microenvironment-related gene expressions in glioblastoma patients treated with precision medicine thyrointegrin alpha v beta 3 antagonist and explore the relationships between prognosis and other clinical features and risk model is the objective of the study.Firstly, we obtained 760 tumor microenvironment-related gene expressions in the glioblastoma cells treated with 30 µM concentration of thyrointegrin alpha v beta 3 antagonist. Meanwhile, we selected genes that are significantly related to prognosis using univariable Cox regression methods. Least absolute shrinkage and selection operator analysis was applied to further select genes that are significantly related to prognosis. We weighted those selected genes with their coefficients and constructed a risk model. The risk score was calculated. We compared overall survival between low risk group and high risk group and investigated whether risk score could serve as an independent factor affecting prognosis. Furthermore, the key immune infiltrations in high and low risk groups were also deeply explored.Low risk group exhibited a better prognosis than high risk group. The multivariate Cox analysis demonstrated that risk score was an independent factor for glioblastoma prognosis. High risk group was related to a higher degree of immune infiltration.The risk model constructed by 760 tumor microenvironment-related gene expression in glioblastoma was significantly related to prognosis and this model provided several beneficial hints for the novel precision drug administration.