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Pathology enters the proteomic era. cell-type resolved mass spectrometry to unravel mechanisms of disease
Pathology enters the proteomic era. cell-type resolved mass spectrometry to unravel mechanisms of disease
Each cell has a place in the order of the human body. Acting in synergy with each other, different cells assemble in conserved and self-organized structures, thereby generating tissues of diverse functionalities. The integrity of these functional units is crucial for human physiology and their imbalance may cause dysfunctionality or disease. The importance of tissue architecture was already acknowledged early on leading to the foundation of the field of pathology with fundamental discoveries form the entire organ down to the roles of single cells. In modern pathology, tissue-centered studies and omics technologies converge based on a broad portfolio of technologies, recently enhanced by artificial intelligence. Proteins provide the closest proxy to the actual phenotype of a cell; therefore, the field of proteomics is set to play a major role in modern pathology, informing on molecular protagonists in complex diseases. In particular, technological advances in mass spectrometry (MS)-based proteomics now allow sensitivity down to the single-level and enable high-throughput workflows, creating the pre-requisites for its application in the clinic. This PhD thesis integrates pathology and MS-based proteomics to help develop a new era of molecular tissue analyses. It follows the transition from bulk to single-cell and single-cell type resolved proteomics while demonstrating the importance of spatial information on the proteome. To this end, I first contributed to the workflow optimization for formalin-fixed paraffin-embedded (FFPE) tissue, thereby enabling the processing of FFPE tissue in a high-throughput format while ensuring the robustness of the downstream data acquisition. Thereafter, I showcased this workflow on the interdisciplinary investigation of thrombosis in brown bears using laser-capture microdissection (LCM). Facing the global COVID-19 pandemic, I further streamlined the preparation of FFPE tissue and explored the impact of COVID-19 across organs and in particular, the heart during myocardial inflammation. My proteomics study demonstrates the importance of true tissue-specific effects beyond the systemic inflammatory response. Thereafter, the thesis transitions toward the characterization of single cell types in the context of the architecture of tissue. I co-developed and optimized the novel technology of Deep Visual Proteomics (DVP) that integrates high-content imaging, artificial intelligence, LCM and ultra-sensitive mass spectrometry to uncover functional cellular heterogeneity in the native tissue environment. With this technology in hands, I set out to investigate serous borderline ovarian tumors in women of reproductive age and their transition to invasive low-grade serous cancer and subsequent metastasis. Here, we uncover mechanisms and key players in the malignant transition, such as the alternative splicing regulator NOVA2, and identify borderline tumors with micropapillary features as the intermediate transition stage. Next to the functional confirmation of these results, this study is also the very first to integrate DVP with spatial transcriptomics. Finally, I contributed to developing multiplexed MS data acquisition and its application to uncover the spatial human liver zonation at a single-cell level. In summary, proteomics-driven pathology has clearly become a powerful approach to study disease mechanisms and to enable precision medicine.
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Schweizer, Lisa
2023
English
Universitätsbibliothek der Ludwig-Maximilians-Universität München
Schweizer, Lisa (2023): Pathology enters the proteomic era: cell-type resolved mass spectrometry to unravel mechanisms of disease. Dissertation, LMU München: Faculty of Chemistry and Pharmacy
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Abstract

Each cell has a place in the order of the human body. Acting in synergy with each other, different cells assemble in conserved and self-organized structures, thereby generating tissues of diverse functionalities. The integrity of these functional units is crucial for human physiology and their imbalance may cause dysfunctionality or disease. The importance of tissue architecture was already acknowledged early on leading to the foundation of the field of pathology with fundamental discoveries form the entire organ down to the roles of single cells. In modern pathology, tissue-centered studies and omics technologies converge based on a broad portfolio of technologies, recently enhanced by artificial intelligence. Proteins provide the closest proxy to the actual phenotype of a cell; therefore, the field of proteomics is set to play a major role in modern pathology, informing on molecular protagonists in complex diseases. In particular, technological advances in mass spectrometry (MS)-based proteomics now allow sensitivity down to the single-level and enable high-throughput workflows, creating the pre-requisites for its application in the clinic. This PhD thesis integrates pathology and MS-based proteomics to help develop a new era of molecular tissue analyses. It follows the transition from bulk to single-cell and single-cell type resolved proteomics while demonstrating the importance of spatial information on the proteome. To this end, I first contributed to the workflow optimization for formalin-fixed paraffin-embedded (FFPE) tissue, thereby enabling the processing of FFPE tissue in a high-throughput format while ensuring the robustness of the downstream data acquisition. Thereafter, I showcased this workflow on the interdisciplinary investigation of thrombosis in brown bears using laser-capture microdissection (LCM). Facing the global COVID-19 pandemic, I further streamlined the preparation of FFPE tissue and explored the impact of COVID-19 across organs and in particular, the heart during myocardial inflammation. My proteomics study demonstrates the importance of true tissue-specific effects beyond the systemic inflammatory response. Thereafter, the thesis transitions toward the characterization of single cell types in the context of the architecture of tissue. I co-developed and optimized the novel technology of Deep Visual Proteomics (DVP) that integrates high-content imaging, artificial intelligence, LCM and ultra-sensitive mass spectrometry to uncover functional cellular heterogeneity in the native tissue environment. With this technology in hands, I set out to investigate serous borderline ovarian tumors in women of reproductive age and their transition to invasive low-grade serous cancer and subsequent metastasis. Here, we uncover mechanisms and key players in the malignant transition, such as the alternative splicing regulator NOVA2, and identify borderline tumors with micropapillary features as the intermediate transition stage. Next to the functional confirmation of these results, this study is also the very first to integrate DVP with spatial transcriptomics. Finally, I contributed to developing multiplexed MS data acquisition and its application to uncover the spatial human liver zonation at a single-cell level. In summary, proteomics-driven pathology has clearly become a powerful approach to study disease mechanisms and to enable precision medicine.