A bioinformatic study of IGFBPs in glioma regarding their diagnostic, prognostic, and therapeutic prediction value.

ABSTRACT

BACKGROUND: It is essential to develop better biomarkers for diagnosis, prediction, and treating glioma patients to ensure successful clinical outcomes. The clinical application of Insulin-Like Growth Factor Binding Proteins (IGFBPs) for glioma is yet to be investigated. METHODS: Cohorts were obtained from TCGA, GTEx, CGGA, HPA, Oncomine, CancerSEA, TISCH, etc. The expressions, methylation, and survival association of IGFBPs were analyzed. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to construct a prognostic model. The correlation of IGFBPs and immune cells or immune molecules was analyzed. The effect of IGFBPs on immune therapy and chemotherapy was analyzed. The top 500 correlated genes of IGFBPs were enriched in GO terms. Correlations between IGFBPs and functional states in glioma single-cells and correlations between IGFBPs and chemokines in samples were analyzed. RESULTS: IGFBPs were overexpressed in glioma. Malignant cells were the major cell types that expressed IGFBPs. Higher-grade glioma had a higher expression of IGFBPs, which were associated with worse survival. A survival model of IGFBPs for glioma patients was trained and validated. A nomogram was generated. Generally, IGFBPs mRNA expression was negatively correlated with B cells and T cells. IGFBPs were associated with multiple immune molecules and drug sensitivity. CONCLUSION: IGFBPs were powerful diagnostic, prognostic, and therapeutic prediction biomarkers for glioma.