The predictive value of peripheral blood monocytic myeloid-derived suppressor cells for survival and immunotherapy responses in tumor patients.

BACKGROUND AND OBJECTIVES

The identification of affordable and easily accessible indicators to predict overall survival is important for tumor immunotherapy. Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of immature myeloid cells, which promote tumor immune escape in the tumor microenvironment (TME). This study aimed to determine whether peripheral blood MDSCs could determine their potential as predictors of survival in tumor patients with immunotherapy.

METHODS

Flow cytometry was used to detect peripheral blood monocytic myeloid-derived suppressor cells (M-MDSCs) and granulocytic myeloid-derived suppressor cells (G-MDSCs) in 126 patients. Multivariate Cox regression analysis was conducted to examine the associations between peripheral blood MDSCs and patient survival. The receiver operating characteristic (ROC) curve determined the optimal cutoff value for peripheral blood MDSCs and grouped the indicators. The relationship between peripheral blood M-MDSCs and the prognosis and treatment outcome of tumor patients was explored.

RESULTS

The proportion of peripheral blood M-MDSCs was associated with the prognosis of patients with tumors, as were tumor metastasis, the red blood cell count, absolute neutrophil count, absolute monocyte count, and BMI. Multivariate Cox regression analysis revealed that M-MDSCs, absolute lymphocyte value, and tumor metastasis were independent risk factors affecting the prognosis of patients with tumors. Detection of peripheral blood M-MDSCs obtained high sensitivity and specificity for tumor diagnosis. Patients with high M-MDSCs percentage demonstrated reduced survival durations and diminished responses to immunotherapy compared to those with low M-MDSCs percentage.

CONCLUSIONS

Peripheral blood M-MDSCs may be used to predict overall survival and immunotherapy efficacy outcomes. This study provides a putative predictive biomarker for clinicians to choose from to predict tumor patients' survival and the selection of receiving immunotherapy regimens.