A liquid biopsy-based approach identifies myeloid cells, STAT3 and arginase-1 as predictors of glioma risk score and patients' survival

Background Although gliomas are strictly confined to the central nervous system, their negative influence over the immune system can extend to peripheral circulation. The immune suppression exerted by myeloid cells is capable of affecting both response to therapy and disease outcome. Here we analyzed the expansion of several myeloid parameters in the blood of low- and high-grade gliomas and assessed their relevance as biomarkers of disease and clinical outcome. Methods Peripheral blood was obtained from 134 low- and high-grade glioma patients before surgery and treatment. Myeloid cell subsets such as total CD14+, CD14+/p-STAT3+, CD14+/PD-L1+, CD15+ cells and 4 myeloid derived suppressor cell (MDSC) subsets, were evaluated by multiparametric flow cytometry. Arginase-1 (ARG1) quantity and activity was determined in the plasma. Principal component analysis was performed to define correlations between myeloid markers. Multivariable logistic regression model was used to obtain a diagnostic score to discriminate glioma patients from healthy controls, and between each glioma grade. A glioblastoma prognostic model was determined by multiple Cox regression using clinical and myeloid parameters. Results In the blood of glioma patients, changes in myeloid parameters associated with immune suppression were identified and allowed us to define a diagnostic score calculating the risk of being a glioma patient, that included CD15+ cells, MDSC1, MDSC3, p-STAT3 and ARG1 activity. Of note, the same parameters, together with age, can also be used to calculate the risk score in differentiating each glioma grade. Finally, a prognostic model for glioblastoma patients stemmed out from a Cox multiple analysis, highlighting the role of MDSC, p-STAT3 and ARG1 activity together with clinical parameters in predicting the patient outcome. Conclusions This work emphasizes the role of systemic immune suppression carried out by myeloid cells in gliomas. The identification of biomarkers associated with immune landscape, diagnosis and outcome of glioblastoma patients lays the ground for their clinical use for stratification and follow up.