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Updated: Aug 6, 2026
08:52
Spatial Molecular Imaging of the Glycome Using Mass Spectrometry
Published on: November 28, 2025
Spatial Glyco-Codes Define Human Liver Pathology and Progression
Xiaolong Tian1,2,3, Anthony Fung1,3, Xingbo Shang1,3
1Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
Biorxiv : the Preprint Server for Biology
|July 17, 2026
Summary
Spatial glyco-codes, unique glycan patterns, reveal cellular identity and disease states in liver tissues. This glycomic approach offers new biomarkers for histopathology and understanding disease progression.
Area of Science:
- Glycobiology and Systems Biology
- Biotechnology and Bioengineering
- Cancer Research and Pathology
Background:
- Glycosylation is crucial for cellular functions and disease, but spatial glycan profiling in archival tissues is challenging.
- Current methods lack the resolution to map glycans alongside proteins and transcripts at a single-cell level in clinical samples.
Purpose of the Study:
- To develop a multimodal platform for simultaneous spatial profiling of glycans, proteins, and transcripts in archival FFPE tissues.
- To identify and characterize spatial glyco-codes and their association with cellular identity, tissue organization, and liver pathologies.
Main Methods:
- Development of spatial-GPT, a platform enabling simultaneous profiling of glycans, proteins, and/or transcripts.
- Utilizing DNA-encoded lectins for sequencing-based spatial glycomics (DBiT-GPT) and imaging-based glycan-protein profiling (CODEX-GP).
- Analysis of 16 human liver specimens (steatosis, fibrosis, cirrhosis, HCC) and over 300 patient samples.
Main Results:
- Spatial glyco-codes, combinatorial glycan states, were identified and linked to distinct cell types, tissue features, and pathological processes.
- Glyco-codes alone could resolve major cell types, disease states, and HCC subtypes, indicating significant biological information within the glycome.
- Tumor-like glyco-codes were found in premalignant regions, suggesting glycan reprogramming precedes malignancy; specific glyco-codes defined immune-evasion and fibrotic niches.
Conclusions:
- Spatial glyco-codes represent a novel layer of tissue organization encoding cellular identity, function, and disease progression.
- Glyco-codes demonstrate potential as molecular histopathology biomarkers, capable of distinguishing liver pathologies across patient cohorts.
- The spatial-GPT platform advances high-resolution glycan analysis in archival tissues, opening new avenues for biomedical research and diagnostics.
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