Abstract Crosstalk between the tumor and surrounding microenvironment has emerged as an important regulator of tumor growth, metastasis and drug response. Patient-derived breast xenografts (PDXs) closely mimic the tumor microenvironment including the tumor architecture and interactions among cancer cells and stromal cells. PDXs provide a unique opportunity to study tumor-stroma interactions and the regulation of protein expression in the tumor microenvironment since species-specific amino acid sequences of the tumor (human) can be distinguished from the stroma (mouse) by LC-MS. However, quantitative proteomics workflows usually do not report species-specific peptides. We therefore developed a proteomics workflow based on 10-plex isobaric tagging to quantitatively profile the protein expression of PDXs and their associated microenvironment. Three biological replicates of seven breast cancer PDXs, representing three breast cancer subtypes, were profiled. Selecting only gene- and species-specific peptides for quantification of protein expression, we identified 8,113 human proteins (4,867 genes) and 2,251 mouse proteins (1,763 genes). Surprisingly, hierarchical clustering by mouse protein expression tightly clustered 4 of the 7 PDXs, with each of the 3 biological replicates next to one another. Notably, the 4 tightly clustered PDXs were from tumors with claudin-low, Her2-E and luminal B subtypes, whereas the biological replicates of three basal subtypes in the dataset were not tightly clustered. Gene set enrichment analysis of the stromal protein expression revealed upregulation of MTORC1 signaling, EMT, and interferon gamma response signaling with false discovery rates below 5%. We further investigated expression of signaling proteins in the tumor microenvironment by enriching active kinases with multiplexed kinase inhibitor beads. 152 mouse kinases were identified in the tumor microenvironment many tumor-specific differences in kinase levels. Taken together, our results imply that individual patient-derived breast tumors can actively and consistently orchestrate unique alterations in the proteins expressed in their microenvironment. Furthermore, we demonstrate the utility of our proteomic analysis workflow to delineate tumor-stroma signaling networks in PDXs. Citation Format: Xuya Wang, Petra Erdmann-Gilmore, Rosa Viner, Matthew Meyer, Tim Stuhlmiller, Sherri Davies, Shunqiang Li, Qiang Zhang, Arshag Mooradian, Kuan-lin Huang, Ryan Bomgarden, Li Ding, Matthew Ellis, John Rogers, Gary Johnson, Reid Townsend, David Fenyo, Jason M. Held. The proteomic landscape of patient-derived breast cancer xenografts reveals tumor-specific differences in the breast tumor microenvironment. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-267.