Biology subjects

Bruch, P.-M.

Publications and source records attributed to Bruch, P.-M..

9 recordsLinked to original sources

bioRxiv2026

Spatial organization of fibroblast subpopulations and niches across acute repair and chronic fibrotic remodeling of the human myocardium

Myocardial fibrosis is a common end point of acute and chronic cardiovascular injury, yet the spatially organized fibroblast (Fb) and immune-cell states that sustain fibrotic remodeling across etiologies remain incompletely defined. We applied cyclic in situ hybridization (cISH)-based spatial transcriptomics to myocardial biopsies from patients with acute myocardial infarction (AMI), ischemic cardiomyopathy (ICM), hypertrophic cardiomyopathy (HCM), postviral myocardial fibrosis (PVMF), and systemic sclerosis associated primary heart involvement (SSc-pHI). CODEX-based protein imaging provided orthogonal support for cell subpopulations and cellular neighborhoods. Spatially informed clustering identified six Fb subpopulations: COL1A1hi/POSTNhi, NOTCH3+, TIMP1hi, GSNhi/DCNhi, AP1hi Fbs, and myofibroblasts. COL1A1hi/POSTNhi and NOTCH3+ Fbs were enriched in AMI, whereas GSNhi/DCNhi Fbs and myofibroblasts predominated in chronic fibrotic remodeling. These subpopulations displayed distinct extracellular matrix, inflammatory, and vasoregulatory programs. Infarction-associated reparative niches were enriched in COL1A1hi/POSTNhi or NOTCH3+ Fbs and SPP1+ or APOE+ macrophages (M{Phi}), whereas chronic fibroinflammatory niches were enriched in GSNhi/DCNhi or AP1hi Fbs or myofibroblasts with C1Q+ M{Phi} and plasma cells. The GSNhi/DCNhi Fb niche marked areas of subendocardial fibrosis, whereas the AP1hi Fb niche localized to perivascular fibrosis. In SSc-pHI, the actively fibrogenic COL1A1hi/POSTNhi Fb state characteristic of infarct scar formation was present at higher frequency than in other chronic entities and was individually associated with cardiac dysfunction, whereas the chronic GSNhi/DCNhi Fb niche was associated with the extent of interstitial fibrosis and anti-topoisomerase I autoantibodies. These data show that human myocardial fibrosis is organized into spatially distinct Fb subpopulations that assemble into context-specific fibroinflammatory niches across chronic fibrotic remodeling and repair after AMI.

cell biology↗

bioRxiv2026

Universal oligo adapters for high-efficiency DNA-barcoded antibody panel generation

DNA-barcoded antibodies are central to a broad range of spatial and dissociative assays and applications, including multiplexed imaging, single-cell profiling, and proximity detection. Direct modification of primary antibodies with defined DNA barcodes enables flexible panel design for multiplexed labeling of proteins. However, conventional antibody-oligonucleotide conjugation methods are inefficient, low-throughput, and prone to batch variability, limiting the reliable generation of orthogonally barcoded antibody panels. These challenges are particularly acute during initial panel development, where lengthy protocols, conjugation failures, large antibody input requirements, and the need for custom antibody formulations increase experimental cost and effort. Site-specific conjugation strategies based on antibody Fc-domain binders offer a promising alternative. We streamlined this foundational approach to establish its compatibility with multiplexed imaging in cells and tissues; however, generating a full barcoded library is still resource-intensive. This is because every unique DNA barcode must first be chemically linked to a separate binder before it can be attached to an antibody. To overcome the prominent bottleneck of rapidly and reliably generating DNA-barcoded antibody panels, we introduce the universal oligo adapter (UnO) strategy. UnO fundamentally changes the workflow from barcode-specific conjugation to universal barcode conversion. We build on the established photoreactive protein G binder and combine it with a universal oligonucleotide carrying a second ultrafast photocrosslinking group, 3-cyanovinylcarbazole (cnvK). This creates a dual-functional adapter: one photoreactive group enables covalent attachment to the antibody, while the cnvK-containing universal oligo simultaneously captures a user-defined DNA barcode through hybridization and UV crosslinking in a single step. Rather than preparing separate conjugation reactions for dozens of barcodes, UnO acts as a single reagent that covalently couples any desired barcode onto small quantities of off-the-shelf primary antibodies in minutes. We validate the generalizability and modularity of this approach across subcellular Immuno-SABER and tissue-based CODEX workflows for multiplex immunostaining. By converting antibody barcoding into a modular, one-step nucleic-acid adapter workflow, UnO reduces the cost, time, and complexity of generating DNA-barcoded antibody panels and provides an efficient, accessible solution to a central bottleneck in DNA-enabled multiplexed protein detection.

bioengineering↗

bioRxiv2025

Spatialproteomics - an interoperable toolbox for analyzing highly multiplexed fluorescence image data

SummaryHighly multiplexed immunofluorescence imaging is a recent method to characterize tissues at single-cell resolution on the protein level, offering low cost, high scalability, and the ability to analyze paraffin-embedded tissue samples. However, the analysis of these data involves a sequence of steps, including segmentation, image processing, marker quantification, cell type classification, and neighborhood analysis, each of which involves a multitude of method and parameter choices that need to be adapted to the data and analytical objective at hand. Moreover, variations in data quality can be high and unpredictable, which necessitates further flexibility and interactivity. While individual components exist, there is an unmet need for a coherent toolbox that offers end-to-end coverage of the workflow, flexibility, and automation. We present spatialproteomics, a Python package that addresses these challenges. Built on top of xarray and dask, spatialproteomics can process images that are larger than the working memory. It supports synchronization of shared coordinates across data modalities such as images, segmentation masks, and expression matrices, which facilitates easy and safe subsetting and transformation. We demonstrate spatialproteomics on a set of images of reactive lymph nodes or different forms of B cell Non-Hodgkin lymphomas (BNHL) from 132 patients. We showcase an end-to-end analysis from raw images to statistical characterization of cell type composition and spatial distribution across indolent and aggressive lymphomas. Furthermore, we show how spatialproteomics can process gigapixel whole slide images. Altogether, we propose spatialproteomics as an easy-to-install, easy-to-learn, comprehensive toolbox for constructing powerful end-to-end image analysis solutions for highly multiplexed immunofluorescence imaging. Availability and ImplementationThe source code for spatialproteomics is freely available at https://github.com/sagar87/spatialproteomics under the MIT license. Contactwolfgang.huber@embl.org, Peter-Martin.Bruch@med.uni-duesseldorf.de

bioinformatics↗

bioRxiv2022

Multimodal and spatially resolved profiling identifies distinct patterns of T-cell infiltration in nodal B-cell lymphoma entities

T-cell-engaging immunotherapies have improved the treatment of nodal B-cell lymphoma, but responses vary highly. Future improvements of such therapies require better understanding of the variety of lymphoma-infiltrating T-cells. We employed single-cell RNA and T-cell receptor sequencing alongside quantification of surface proteins, flow cytometry and multiplexed immunofluorescence on 101 lymph nodes from healthy controls, and patients with diffuse large B-cell, mantle cell, follicular, or marginal zone lymphoma. This multimodal resource revealed entity-specific quantitative and spatial aberrations of the T-cell microenvironment. Clonal PD1+ TCF7- but not PD1+ TCF7+ cytotoxic T-cells converged into terminally exhausted T-cells, the proportions of which were variable across entities and linked to inferior prognosis. In follicular and marginal zone lymphoma, we observed expansion of follicular helper and IKZF3+ regulatory T-cells, which were clonally related and inversely associated with tumor grading. Overall, we portray lymphoma-infiltrating T-cells with unprecedented comprehensiveness and decipher both beneficial and adverse dimensions of T-cell response.

cancer biology↗

bioRxiv2022

Proteogenomics refines the molecular classification of chronic lymphocytic leukemia

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterized the proteome and transcriptome in-depth alongside genetic and ex-vivo drug response profiling in a clinically well annotated CLL discovery cohort (n= 68). Unsupervised clustering of the proteome data revealed six subgroups. Five of these proteomic groups were associated with genetic features, while one group was only detectable at the proteome level. This new group was characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). We developed classifiers to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n= 165, n= 169) and confirmed that ASB-CLL comprises about 20 % of CLL patients. The inferior overall survival observed in ASB-CLL was independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling. Single sentence summaryWe performed the largest proteogenomic analysis of CLL, linked proteomic profiles to clinical outcomes, and discovered a new poor outcome subgroup (ASB-CLL).

cancer biology↗

bioRxiv2022

Imaging-based coculture model for high-throughput compound screening in hematological cancers

Large-scale compound screens are a powerful model system for understanding variability of treatment response and for discovering druggable tumor vulnerabilities of hematological malignancies. However, as mostly performed in a monoculture of tumor cells, these assays disregard modulatory effects of the in vivo microenvironment. It is an open question whether and to what extent coculture with bone marrow stromal cells could improve the biological relevance of drug testing assays over monoculture. Here, we measured ex vivo sensitivity of 108 primary blood cancer samples to 50 drugs in monoculture and in coculture with bone marrow stromal cells. Stromal coculture conferred resistance to 52 % of compounds in chronic lymphocytic leukemia (CLL) and to 36% of compounds in acute myeloid leukemia (AML), including chemotherapeutics, BCR inhibitors, proteasome inhibitors and BET inhibitors. While most of the remaining drugs were similarly effective in mono- and coculture, only the JAK inhibitors ruxolitinib and tofacitinib exhibited increased efficacy in AML and CLL stromal coculture. We further confirmed the importance of JAK-STAT signaling for stroma-mediated resistance by showing that stromal cells induce phosphorylation of STAT3 in CLL cells. We genetically characterized the 108 cancer samples and found that drug-gene associations agreed well between mono- and coculture. Overall, effect sizes were lower in coculture, thus more drug-gene associations were detected in monoculture than in coculture. Our results suggest a two-step strategy for drug perturbation testing, with large-scale screening performed in monoculture, followed by focused evaluation of potential stroma-mediated resistances in coculture.

cancer biology↗

bioRxiv2021

Haplotype-aware single-cell multiomics uncovers functional effects of somatic structural variation

Somatic structural variants (SVs) are widespread in cancer genomes, however, their impact on tumorigenesis and intra-tumour heterogeneity is incompletely understood, since methods to functionally characterize the broad spectrum of SVs arising in cancerous single-cells are lacking. We present a computational method, scNOVA, that couples SV discovery with nucleosome occupancy analysis by haplotype-resolved single-cell sequencing, to systematically uncover SV effects on cis-regulatory elements and gene activity. Application to leukemias and cell lines uncovered SV outcomes at several loci, including dysregulated cancer-related pathways and mono-allelic oncogene expression near SV breakpoints. At the intra-patient level, we identified different yet overlapping subclonal SVs that converge on aberrant Wnt signaling. We also deconvoluted the effects of catastrophic chromosomal rearrangements resulting in oncogenic transcription factor dysregulation. scNOVA directly links SVs to their functional consequences, opening the door for single-cell multiomics of SVs in heterogeneous cell populations.

genomics↗

bioRxiv2021

Mapping drug-microenvironment-genetic interplay in CLL reveals trisomy 12 as a modulator of microenvironmental signals

The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited to small scale studies and systematic analyses are lacking. We chose Chronic Lymphocytic Leukaemia (CLL), the most common leukaemia in adults, as a model disease to study this complex interplay systematically. We performed a combinatorial assay using 12 drugs individually co-applied with each of 17 microenvironmental stimuli in 192 primary CLL samples, generating a comprehensive map of drug-microenvironment interactions in CLL. This data was combined with whole-exome sequencing, DNA-methylation, RNA-sequencing and copy number variant annotation. Our assay identified four distinct CLL subgroups that differed in their responses to the panel of microenvironmental stimuli. These subgroups were characterized by distinct clinical outcomes independently of known prognostic markers. We investigated the effect of CLL- specific recurrent genetic alterations on microenvironmental responses and identified trisomy 12 as an amplifier of multiple microenvironmental stimuli. We further quantified the impact of microenvironmental stimuli on drug response, confirmed known interactions such as Interleukin (IL) 4 mediated resistance to B cell receptor (BCR) inhibitors, and identified new interactions such as Interferon-{gamma} induced resistance to BCR inhibitors. Finally, we identified interactions which were limited to genetic subgroups. Resistance to chemotherapeutics, such as Fludarabine, induced by Toll-Like Receptor (TLR) agonists could be observed in IGHV unmutated patient samples and IGHV mutated samples with trisomy 12. In-vivo relevance was investigated in CLL-infiltrated lymph nodes, which showed increased IL4 and TLR signalling activity compared to healthy samples (p<0.001). High IL4 activity in lymph nodes correlated with faster disease progression (p=0.038). We provide a publicly available resource (www.dietrichlab.de/CLL_Microenvironment/) which uncovers tumour cell extrinsic influences on drug response and disease progression in CLL, and how these interactions are modulated by cell intrinsic molecular features.

cancer biology↗

bioRxiv2019

Dissecting intratumor heterogeneity of nodal B cell lymphomas on the transcriptional, genetic, and drug response level

Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer drugs, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

cancer biology↗