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Matuck, B. F.

Publications and source records attributed to Matuck, B. F..

4 recordsLinked to original sources

STARComm Scalably Detects Emergent Modules of Spatial Cell-Cell Communication in Inflammation and Cancer.

In humans, cell-cell communication orchestrates tissue organization, immune coordination, and repair, yet spatially mapping these interactions remains a challenge for biology. We introduce STARComm, a scalable-interpretable computational method that identifies Multicellular Communication Interaction Modules (MCIMs) by detecting spatially co-located receptor-ligand activity from high-plex spatial transcriptomics in 2D and 3D. Applied to an atlas of >14million cells across 8 cancers, STARComm revealed 24 conserved and tumor-specific MCIMs, including a fibro-immune module with targetable axes linked to immune exclusion and immunotherapy resistance. In chronic graft-versus-host disease, STARComm identified three salivary gland MCIMs predictive of patient death and two druggable axes (CXCL12-CXCR4, CCL5-SDC4), both with FDA-approved therapeutics. STARComm demonstrated that peripheral tissue profiling can forecast fatality nearly 3 years in advance using minor salivary glands. By enabling scalable biomarker discovery, drug targeting, and spatially resolved precision profiling, STARComm bridges the gap between spatial biology and clinical translation, advancing the field of spatial medicine. SUMMARYDespite major advances in spatial biology, no framework has yet linked spatially resolved intercellular communication networks, independent of cell types, to clinical outcomes in human disease. Here, we present STARComm, a scalable method that identifies Multicellular Interaction MCIMs (MCIMs). Applying STARComm to minor salivary gland biopsies from patients with chronic graft-versus-host disease (GVHD), we identify MCIMs that not only distinguish healthy from diseased tissue but also stratify patient survival. High-risk MCIMs are enriched for actionable immune and stromal pathways, including those targetable with existing therapies. These findings establish the first outcome-linked spatial communication framework in any human disease and highlight the translational potential of oral tissues as minimally invasive platforms for real-time immune diagnostics, prognostic modeling, and therapeutic screening.

bioinformatics↗

The Single-Cell Landscape of Peripheral and Tumor-infiltrating Immune Cells in HPV- HNSCC

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. HPV-negative HNSCC, which arises in the upper airway mucosa, is particularly aggressive, with nearly half of patients succumbing to the disease within five years and limited response to immune checkpoint inhibitors compared to other cancers. There is a need to further explore the complex immune landscape in HPV-negative HNSCC to identify potential therapeutic targets. Here, we integrated two single-cell RNA sequencing datasets from 29 samples and nearly 300,000 immune cells to investigate immune cell dynamics across tumor progression and lymph node metastasis. Notable shifts toward adaptative immune cell populations were observed in the 14 distinct HNSCC-associated peripheral blood mononuclear (PBMCs) and 21 tumor-infiltrating immune cells (TICs) considering disease stages. All PBMCs and TICs revealed unique molecular signatures correlating with lymph node involvement; however, broadly, TICs increased ligand expression among effector cytokines, growth factors, and interferon-related genes. Pathway analysis comparing PBMCs and TICs further confirmed active cell signaling among Monocyte-Macrophage, Dendritic cell, Natural Killer (NK), and T cell populations. Receptor-ligand analysis revealed significant communication patterns shifts among TICs, between CD8+ T cells and NK cells, showing heightened immunosuppressive signaling that correlated with disease progression. In locally invasive HPV-negative HNSCC samples, highly multiplexed immunofluorescence assays highlighted peri-tumoral clustering of exhausted CD8+ T and NK cells, alongside their exclusion from intra-tumoral niches. These findings emphasize cytotoxic immune cells as valuable biomarkers and therapeutic targets, shedding light on the mechanisms by which the HNSCC sustainably evades immune responses.

cancer biology↗

Spatial Deconvolution of Cell Types and Cell States at Scale Utilizing TACIT

Identifying cell types and states remains a time-consuming and error-prone challenge for spatial biology. While deep learning is increasingly used, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we developed TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data, using unbiased thresholding to distinguish positive cells from background, focusing on relevant markers to identify ambiguous cells in multiomic assays. Using five datasets (5,000,000-cells; 51-cell types) from three niches (brain, intestine, gland), TACIT outperformed existing unsupervised methods in accuracy and scalability. Integration of TACIT-identified cell with a novel Shiny app revealed new phenotypes in two inflammatory gland diseases. Finally, using combined spatial transcriptomics and proteomics, we discover under- and overrepresented immune cell types and states in regions of interest, suggesting multimodality is essential for translating spatial biology to clinical applications.

bioinformatics↗

Polybacterial intracellular coinfection of epithelial stem cells in periodontitis

Periodontitis affects billions of people worldwide. To address interkingdom relationships of microbes and niche on periodontitis, we generated the first sin-gle-cell meta-atlas of human periodontium (34-sample, 105918-cell), harmo-nizing 32 annotations across 4 studies1-4. Highly multiplexed immunofluores-cence (32-antibody; 113910-cell) revealed spatial innate and adaptive immune foci segregation around tooth-adjacent epithelial cells. Sulcular and junctional keratinocytes (SK/JKs) within epithelia skewed toward proinflammatory phe-notypes; diseased JK stem/progenitors displayed altered differentiation states and chemotactic cytokines for innate immune cells. Single-cell metagenomics utilizing unmapped reads revealed 37 bacterial species. 16S and rRNA probes detected polybacterial intracellular pathogenesis ("co-infection") of 4 species within single cells for the first time in vivo. Challenging coinfected primary human SK/JKs with lipopolysaccharide revealed solitary and synergistic ef-fects. Coinfected single-cell analysis independently displayed proinflammatory phenotypes in situ. Here, we demonstrate the first evidence of polybacterial intracellular pathogenesis in human tissues and cells--potentially influencing chronic diseases at distant sites.

cell biology↗