Description:
Abstract Glioblastoma is the most frequent and malignant brain tumor, with a median survival of approximately 14 months. The tumor microenvironment is composed of different cell types and is known to support the glioblastoma cells and contribute to poor patient prognosis. Since accumulating studies report discordance between mRNA and protein abundances both on population and single-cell levels, and since proteins are the effector molecules of the cells and the actual target molecules of most drugs, our aim is to dissect the tumor microenvironment by spatial LC-MS based proteomics. Glioblastoma formalin-fixed paraffin-embedded (FFPE) tissue was sectioned and placed on membrane glass slides suitable for laser capture microdissection (LCM), followed by precise isolation of single cells from the heterogeneous tumor microenvironment. We used the Zeiss Palm MicroBeam laser microdissection instrument, combined with an Orbitrap Eclipse Tribrid Mass Spectrometer running our in-house sensitivity tailored Data Independent Acquisition method (WISH-DIA) to analyze and quantify the proteomes. We obtained up to 3000 proteins out of only 100 cells and were able to demonstrate the feasibility of collecting and analyzing various cell types at the single-cell level. The proteins identified belonged to many different classes/families of proteins and were able to distinguish the different cell types. In conclusion, this on-going study demonstrates our ability to isolate single cells from the highly heterogeneous tumor microenvironment of glioblastoma with ultra-high sensitivity, thereby allowing the characterization of the proteome of the glioblastoma microenvironment followed by identification of potential therapeutic and/or diagnostic targets. Citation Format: Kartikey Saxena, Rune Daucke, Vilde Pedersen, Pia Helene Klausen, Erwin Schoof, Bjarne Winther Kristensen. Deep spatial proteomics: A new approach for obtaining insight into the glioblastoma microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1161.