Christian M. Schürch

This study identifies genomic features, particularly copy-number alterations, that predict metastatic progression in melanoma and defines a six-gene signature associated with relapse.

Eva is a foundation model for tissue imaging data that learns multi-scale spatial representations and performs various tasks like cross-modal inference and patient stratification.

The paper examines immune receptor clonality in melanoma-draining lymph nodes and finds that extreme high clonality is linked to immune dysfunction and poor survival.

HOPE learns tumor microenvironment signatures from paired H&E and spatial omics data to improve prognostic stratification using H&E images alone.

This study uses spatial multi-omics to compare EBV-positive and EBV-negative cHL, identifying distinct TME features and immunological signatures linked to EBV.

This study maps the spatiotemporal changes in the bone marrow microenvironment during CML progression using single-cell and 3D imaging, revealing immune evasion and niche disruption.

ROSIE generates multiplex immunofluorescence staining from H&E images by imputing protein expression and localization using deep learning.

This study identifies immune cell changes and gene expression patterns in Barrett's esophagus progression to cancer using spatial and multi-omic analyses.

This study identifies MCSP+ melanoma cells as early metastasis founder cells in lymph nodes and shows they activate immunosuppression to evade CD8 T cell attack.

This paper introduces IN-DEPTH and SGCC for spatial multi-omics analysis, revealing EBV-related immunomodulatory differences in DLBCL.

This paper introduces CombPlex, a combinatorial staining method combined with deep learning to measure more proteins at single-cell resolution without needing specialized imaging equipment.

The paper maps cell organization and function across human intestine regions using single nuclear RNA and open chromatin assays, revealing distinct cell neighborhoods and regulatory differences.

This paper introduces ion beam tomography (IBT), a 3D subcellular imaging technique, and demonstrates its ability to visualize genomic regions, RNA transcripts, and protein factors with high resolution.