Abstract 3772: Tissue-niche-based and cell-type-selective in-depth proteomics

Abstract Introduction: The development, physiology function, and pathogenesis of the tissues are intricately orchestrated by the spatial organization of diverse cell populations. Proteins are the fundamental components within individual cells that control every function. Therefore, by integrating both information on cellular location and molecular profiling, spatial proteomics has emerged as an indispensable field for understanding mechanisms governing tissue homeostasis, disease progression, and therapeutic responses. Here, I introduce a spatial proteomics method designed to target selective cell phenotypes within definite tissue niches for in-depth spatial biology analysis. Method: In this approach, we developed a sequential pipeline highlighted with immunofluorescence staining, microscopic photobleaching, fluorescence cell sorting, and liquid chromatography-mass spectrometry (LC-MS) analysis. The process begins with staining 400-μm-thick tissue macrosections with fluorescence-conjugated antibodies to visualize specific cell types of interest. We employed two different fluorescence-conjugated antibodies of the same clone (e.g., Alexa488-anti-CD11c and Alexa647-anti-CD11c antibodies) for the staining on every targeted cell (e.g., CD11c+ immune cells). We then introduced “photobleaching barcodes” using a confocal microscope to photobleach/exhaust either one of the fluorescence signals stained on cells by exposing it to the matched laser. This allows us to create differentiable fluorescence barcodes that label cells at distinct regions, incorporating cell spatial information into our fluorescence detection. After tissue dissociation, barcoded cells were sorted into different groups which were also classified by their original locations in the macrosection. Finally, protein extraction and LC-MS analysis were conducted on the collected cells to enable comprehensive spatial proteomic analysis. Results: The initial application in investigating dendritic cell (DC) subsets in mouse spleen during lipopolysaccharide (LPS)-induced inflammation reveals significant proteome differences among three splenic DC subsets, categorized by their locations in or outside spleen T-cell zones as well as control DCs. Our result aligns with previously published proteome data in splenic DCs, underscoring the feasibility and reliability of our technology. Currently, we are in the process of evaluating breast cancer cell heterogeneity in human biopsy specimens using our approach to profile the tumor-immune microenvironment. Conclusion: Spatial proteomic findings from both applications are poised to discover potential drug targets that benefit treatment efficacy for inflammatory diseases and breast cancer. This technology features deep protein profiling for cell-type-specific spatial proteomics and is designed for broad applications across diverse tissue specimens in various diseases. Citation Format: Yi-Chien Wu, Elie Abi Khalil, Samuel Weng, Steve Lee. Tissue-niche-based and cell-type-selective in-depth proteomics [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 3772.