Toward High Spatially Resolved Proteomics Using Expansion Microscopy.

Expansion microscopy (EM) is an emerging approach for morphological examination of biological specimens at nanoscale resolution using conventional optical microscopy. To achieve physical separation of cell structures, tissues are embedded in a swellable polymer and expanded several fold in an isotropic manner. This work shows the development and optimization of physical tissue expansion as a new method for spatially resolved large-scale proteomics. Herein we established a novel method to enlarge the tissue section to be compatible with manual microdissection on regions of interest and MS-based proteomic analysis. A major issue in expansion microscopy is the loss of protein information during the mechanical homogenization phase due to the use of proteinase K. For isotropic expansion, different homogenization agents were investigated, both to maximize protein identification and to minimize protein diffusion. Best results were obtained with SDS for homogenization. Using our modified protocol, we were able to enlarge a tissue section more than 3-fold and identified up to 655 proteins from 1 mm in size after expansion, equivalent to 330 µm in their real size corresponding thus to an average of 260 cells. This approach can be performed easily without any expensive sampling instrument. We demonstrated the compatibility of sample preparation for expansion microscopy and proteomic study in a spatial context.

Spatial analysis of the glioblastoma proteome reveals specific molecular signatures and markers of survival.

Molecular heterogeneity is a key feature of glioblastoma that impedes patient stratification and leads to large discrepancies in mean patient survival. Here, we analyze a cohort of 96 glioblastoma patients with survival ranging from a few months to over 4 years. 46 tumors are analyzed by mass spectrometry-based spatially-resolved proteomics guided by mass spectrometry imaging. Integration of protein expression and clinical information highlights three molecular groups associated with immune, neurogenesis, and tumorigenesis signatures with high intra-tumoral heterogeneity. Furthermore, a set of proteins originating from reference and alternative ORFs is found to be statistically significant based on patient survival times. Among these proteins, a 5-protein signature is associated with survival. The expression of these 5 proteins is validated by immunofluorescence on an additional cohort of 50 patients. Overall, our work characterizes distinct molecular regions within glioblastoma tissues based on protein expression, which may help guide glioblastoma prognosis and improve current glioblastoma classification.