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Neurofibromatosis 2 (NF2) is a rare tumor suppressor syndrome that manifests with multiple schwannomas and meningiomas. There are no effective drug therapies for these benign tumors and conventional therapies have limited efficacy. Various model systems have been created and several drug targets have been implicated in NF2-driven tumorigenesis based on known effects of the absence of merlin, the product of the NF2 gene. We tested priority compounds based on known biology with traditional dose-concentration studies in meningioma and schwann cell systems. Concurrently, we studied functional kinome and gene expression in these cells pre- and post-treatment to determine merlin deficient molecular phenotypes. Cell viability results showed that three agents (GSK2126458, Panobinostat, CUDC-907) had the greatest activity across schwannoma and meningioma cell systems, but merlin status did not significantly influence response. In vivo, drug effect was tumor specific with meningioma, but not schwannoma, showing response to GSK2126458 and Panobinostat. In culture, changes in both the transcriptome and kinome in response to treatment clustered predominantly based on tumor type. However, there were differences in both gene expression and functional kinome at baseline between meningioma and schwannoma cell systems that may form the basis for future selective therapies. This work has created an openly accessible resource (www.synapse.org/SynodosNF2) of fully characterized isogenic schwannoma and meningioma cell systems as well as a rich data source of kinome and transcriptome data from these assay systems before and after treatment that enables single and combination drug discovery based on molecular phenotype.

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.