Spatial characterization and stratification of colorectal adenomas by deep visual proteomics

Area of Science:

• Molecular biology
• Proteomics
• Oncology

Background:

• Colorectal adenomas (CRAs) are precancerous lesions.
• Current classification relies on morphology, limiting risk stratification.
• A molecular approach is needed for improved patient management.

Purpose of the Study:

• To develop a molecular feature-based risk stratification framework for CRAs.
• To utilize Deep Visual Proteomics (DVP) for detailed molecular profiling.
• To identify novel protein markers and metabolic insights for risk assessment.

Main Methods:

• Deep Visual Proteomics (DVP) applied to formalin-fixed, paraffin-embedded (FFPE) CRA tissues.
• Immunohistological staining for caudal-type homeobox 2 (CDX2).
• Ultra-high sensitive mass spectrometry for protein identification and quantification.

Main Results:

• DVP identified DMBT1, MARCKS, and CD99 as potential recurrence risk markers.
• Detected a metabolic shift towards anaerobic glycolysis in CDX2-expressing cells.
• Characterized cellular heterogeneity within distinct tissue regions and across patients.

Conclusions:

• Spatial proteomics offers a powerful tool for refining early-stage colorectal cancer detection.
• Identified protein markers can enhance risk assessment and personalized patient management.
• Novel insights into metabolic reprogramming in CRAs were provided.