The levels of immunosuppressive checkpoint protein PD-L1 and tumor-infiltrating lymphocytes were integrated to reveal the glioma tumor microenvironment

In spite of significant strides in the realm of cancer biology and therapeutic interventions, the clinical prognosis for patients afflicted with glioblastoma (GBM) remains distressingly dismal. The tumor immune microenvironment (TIME), a crucial player in the progression, treatment response, and prognostic trajectory of glioma, warrants thorough exploration. Within this intricate microcosm, the immunosuppressive checkpoint protein PD-L1 and tumor-infiltrating lymphocytes (TILs) emerge as pivotal constituents, underscoring their potential role in deciphering glioma biology and informing treatment strategies. However, prognostic models based on the association between PD-L1 expression and TIL infiltration in the tumor immune microenvironment have not been established. The aim of this study was to explore TIME genes associated with PD-L1 expression and TIL invasion and to construct a risk score for predicting the overall survival (OS) of GBM patients based on these genes. The samples were separately classified according to the PD-L1 expression level and TIL score and TIME-related genes were identified using differential expression and weighted gene co-expression network analysis. The DEGs were subjected to least absolute contraction and selection operator (LASSO) -Cox regression to construct TIME associated risk score (TIMErisk). A TIMErisk was developed based on STEAP3 and CXCL13 genes. The STLEAP3 was demonstrated to be involved in glioma progression. The results showed that the patients in the high TIMErisk group had poor OS compared with subjects in the low TIMErisk group. The biological phenotypes associated with TIMErisk were analyzed in terms of functional enrichment, tumor immune profile, and tumor mutation profile. The results on tumor immune dysfunction and exclusion dysfunction (TIDE) score and immune surface score (IPS) showed that GBM patients with different TIME risks had different responses to immunotherapy. Tumor purity analysis indicated that PD-L1 and TIL scores were positively correlated with TIMErisk score and negatively correlated with tumor purity. These results show that the TIMErisk-based prognostic model had high predictive value for the prognosis and immune characteristics of GBM patients. Immunohistochemical staining images of patients in the high and low TIMErisk groups were analyzed, showing that the degree of immune cell infiltration was higher in the high TIMErisk group relative to the low TIMErisk group. The present study provides a basis for understanding glioma tumor microenvironment and a foundation for conducting comprehensive immunogenomic analysis.