Project Summary/Abstract Meningioma is the most common intracranial tumor and affects approximately 150,000 individuals in the USA. Approximately 10-20% of them will eventually develop recurrent disease despite standard surgery and radiation therapy (RT). There is currently no effective salvage therapy for radiation-relapsed meningioma. Preclinical models suggest possible synergy when immune checkpoint inhibitors of the programmed-death-1 (PD-1) and cytotoxic T-lymphocyte- associated protein 4 (CTLA-4) pathways are administered with concurrent RT, and anti-PD-1 inhibitor has shown promising activity against meningioma in cases reports. The ETCTN 10186 study is a phase I/II study that evaluates the safety and efficacy of combining anti-PD-1 and anti-CTLA-4 inhibitors with multi-fraction stereotactic radiosurgery for radiation-relapsed high- grade meningioma. Although predictive biomarkers for immunotherapy response have not been well established, specific T-cells or myeloid cells in peripheral blood have shown correlations with the treatment response to anti-PD-1 or anti-CTLA-4 inhibitors in previous clinical trials for solid tumors. The objective of the proposed study is to leverage the blood samples collected in the ETCTN study to discover potential biomarkers to predict immunotherapy response. The specific aim is to determine if peripheral T-cell or myeloid dynamics as assessed using multiparameter flow cytometry would correlate with treatment response. Twelve patients have already been enrolled in the ongoing ETCTN study, and their peripheral blood mononuclear cells (PBMCs) at baseline and weeks 4 and week 12 during treatment have been centrally processed and cryopreserved. These PBMC samples will be analyzed by multiparameter flow cytometry to evaluate the phenotype changes of peripheral T-cells and myeloid cells during treatment. The changes over time and the correlation with radiological response will be examined to generate candidate peripheral blood biomarkers for further development and validation. Once specific candidate phenotypes are identified, the reproducibility of quantifying these cellular subsets using flow cytometry will also be evaluated.