Description
We characterized tumor and immune microenvironment (TiME) of malignant pleural mesothelioma (MPM) using immunoproteomic approach to comprehensively understand the landscape to affect prognosis and possibly to predict response to immunotherapy. Time-of-Flight Mass Cytometry (CyTOF) was performed on the tumors of 12 MPM patients. We comprehensively analyzed TiME by developing intuitive models for visualizing single-cell data with statistical inference and performed unsupervised clustering of cell frequency. A clinically relevant protein signature through mass spectrometry and mRNA transcriptome array was tested for its ability to reflect prognosis in three independent cohorts (n=330) and to predict response to immune checkpoint inhibitor therapy in publicly available data and in 10 patients of MPM treated with anti-PD1 therapy. A systematic understanding of antitumor immunity by immunoproteomic characterization of TiME envisions significant progress in developing rational immunotherapeutic strategies in MPM.