Thymic epithelial tumors (TETs) belong to a group of tumors that rarely occur, but have unresolved mechanisms and heterogeneous clinical behaviors. Current care of TET patients demands biomarkers of high sensitivity and specificity for accurate histological classification and prognosis management. In this study, 90 fresh-frozen tissue samples were recruited to generate a quantitative and systematic view of proteomic landscape of TETs by data independent acquisition mass spectrometry (DIA-MS) leading to discovery of novel classifying molecules among different TET subtypes.