Biology subjects

Bzorek, M.

Publications and source records attributed to Bzorek, M..

5 recordsLinked to original sources

bioRxiv2026

Immunopeptidomics reveals peptide antigens preferentially presented in psoriasis lesional skin of HLA-C*06:02 carriers

BackgroundHuman leukocyte antigen (HLA)-C*06:02 is a major genetic risk factor for psoriasis and understanding the HLA-C*06:02-presented peptide antigen repertoire (immunopeptidome) in the skin of patients is crucial for identifying autoantigens. Yet, no skin immunopeptidome data from patients stratified by their HLA-C*06:02 status exists. ObjectiveWe analysed biopsies from lesional and non-lesional skin of patients with psoriasis vulgaris (n=12), guttate psoriasis (n=8), or from skin of healthy controls (n=16). MethodsHLA class I and class II peptide complexes were isolated by serial immunoprecipitation and HLA-bound peptides identified by liquid chromatography-tandem mass spectrometry. HLA-C*06:02 genotyping was performed by polymerase chain reaction. ResultsOver 99,000 non-redundant peptide ligands were identified across all samples. Substantially more HLA class I and class II peptides were detected in lesional psoriatic skin compared to matched non-lesional and healthy skin. Three peptides predicted to bind HLA-C*06:02, including MRASSFLIV from the known psoriasis marker peptidase inhibitor 3 (PI3), were identified in all lesions of HLA-C*06:02-positive patients but were rarely detected or absent in HLA-C*06:02-negative patient lesional skin and not detected at all in unaffected skin. Keratinocyte differentiation-associated protein (KRTDAP) was a notable source of lesion-specific HLA class II ligands contributing three out of six peptides detected in more than half of the lesional samples. ConclusionActive psoriatic lesions display an altered and expanded immunopeptidome compared to unaffected skin. We have identified numerous unreported, lesion-specific HLA-bound peptides and their source proteins. These findings offer insights into the pathobiology of psoriasis and provide a resource for future functional studies. CAPSULE SUMMARYA selection of immunopeptides is presented exclusively in lesional skin of HLA-C*06:02+ patients with psoriasis that may represent antigenic drivers of disease.

immunology↗

bioRxiv2024

Deep Visual Proteomics Unveils Precision Medicine Insights in Composite Small Lymphocytic and Classical Hodgkin Lymphoma

Coexistence of two cancer types in the same organ presents challenges for clinical decision-making, calling for personalized treatment strategies. Deep Visual Proteomics (DVP) combines AI driven single cell type analysis with laser microdissection and ultrasensitive mass spectrometry. In a composite case of classical Hodgkin lymphoma (cHL) and small lymphocytic lymphoma (SLL) in a single patient, we investigated the potential of DVP to inform precision oncology. We quantified the proteomic landscapes in the cHL and SLL to a depth of thousands of proteins. Our analysis revealed distinct proteome profiles in cHL and SLL populations, highlighting their clonal unrelatedness. Our data suggested standardized chemotherapy and interleukin-4 inhibition as potential strategies to manage chemo-resistance - instead of bone marrow transplantation. DVP highlighted minichromosome maintenance protein and proteasome inhibitors for cHL and H3K27 methylation and receptor tyrosine kinase inhibitors for SLL as subtype-specific treatments. Thus cell-type specific insights of DVP can guide personalized oncological treatments.

cancer biology↗

bioRxiv2023

A standardized and reproducible workflow for membrane glass slides in routine histology and spatial proteomics

Defining the molecular phenotype of single cells in-situ is essential for understanding tissue heterogeneity in health and disease. Powerful imaging technologies have recently been joined by spatial omics technologies, promising unparalleled insights into the molecular landscape of biological samples. One approach involves laser microdissection in combination with membrane glass slides for the isolation of single cells from specific anatomical regions for further analysis by spatial omics. However, so far this is not fully compatible with automated staining platforms and routine histology procedures such as heat-induced epitope retrieval, limiting reproducibility, throughput and integration of advanced staining procedures. This study describes a robust workflow for routine use of glass membrane slides, allowing precise extraction of tissue in combination with automated and multicolor immunofluorescence staining. The key advance is the addition of glycerol to standard heat-induced epitope retrieval protocol, preventing membrane distortion while preserving antigen retrieval properties. Importantly, we show that glycerol is fully compatible with mass-spectrometry based proteomics and does not affect proteome depth or quality. Further, we enable single focal plane imaging by removing remaining trapped air pockets with an incision. We demonstrate our workflow using the recently introduced Deep Visual Proteomics technology on the single-cell type analysis of adjacent suprabasal and basal keratinocytes of human skin. Our protocol extends the utility of membrane glass slides and enables much more robust integration with routine histology procedures, high-throughput multiplexed imaging and sophisticated downstream spatial omics technologies.

pathology↗

bioRxiv2021

AI-driven Deep Visual Proteomics defines cell identity and heterogeneity

The systems-wide analysis of biomolecules in time and space is key to our understanding of cellular function and heterogeneity in health and disease1. Remarkable technological progress in microscopy and multi-omics technologies enable increasingly data-rich descriptions of tissue heterogeneity2,3,4,5. Single cell sequencing, in particular, now routinely allows the mapping of cell types and states uncovering tremendous complexity6. Yet, an unaddressed challenge is the development of a method that would directly connect the visual dimension with the molecular phenotype and in particular with the unbiased characterization of proteomes, a close proxy for cellular function. Here we introduce Deep Visual Proteomics (DVP), which combines advances in artificial intelligence (AI)-driven image analysis of cellular phenotypes with automated single cell laser microdissection and ultra-high sensitivity mass spectrometry7. DVP links protein abundance to complex cellular or subcellular phenotypes while preserving spatial context. Individually excising nuclei from cell culture, we classified distinct cell states with proteomic profiles defined by known and novel proteins. AI also discovered rare cells with distinct morphology, whose potential function was revealed by proteomics. Applied to archival tissue of salivary gland carcinoma, our generic workflow characterized proteomic differences between normal-appearing and adjacent cancer cells, without admixture of background from unrelated cells or extracellular matrix. In melanoma, DVP revealed immune system and DNA replication related prognostic markers that appeared only in specific tumor regions. Thus, DVP provides unprecedented molecular insights into cell and disease biology while retaining spatial information.

systems biology↗

bioRxiv2020

Spatially and cell-type resolved quantitative proteomic atlas of healthy human skin

Human skin provides both physical integrity and immunological protection from the external environment using functionally distinct layers, cell types and extracellular matrix. Despite its central role in human health and disease, the constituent proteins of skin have not been systematically characterized. Here, we combined advanced tissue dissection methods, flow cytometry and state-of-the-art proteomics to describe a spatially-resolved quantitative proteomic atlas of human skin. We quantified 10,701 proteins as a function of their spatial location and cellular origin. The resulting protein atlas and our initial data analyses demonstrate the value of proteomics for understanding cell-type diversity within the skin. We describe the quantitative distribution of structural proteins, known and novel proteins specific to cellular subsets and those with specialized immunological functions such as cytokines and chemokines. We anticipate that this proteomic atlas of human skin will become an essential community resource for basic and translational research (www.skin.science).

cell biology↗