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Spatially Resolved Proteomic Cartography Illuminates the Earliest Molecular Programs in Pancreatic Cancer Evolution
Mingyu Yang1, Rong Fan1,2,3
1Department of Biomedical Engineering, School of Engineering and Applied Science, Yale University, New Haven, Connecticut.
Cancer Discovery
|July 1, 2026
Summary
Artificial intelligence and deep visual proteomics mapped pancreatic cancer evolution. Metabolic and inflammatory changes occur early, before visible transformation, offering new precision oncology insights.
Area of Science:
- Proteomics
- Cancer Research
- Artificial Intelligence
Background:
- Pancreatic ductal adenocarcinoma (PDAC) is a deadly cancer with poor outcomes.
- Early detection of PDAC precursors remains a significant challenge.
- Understanding molecular changes during early pancreatic cancer evolution is crucial.
Purpose of the Study:
- To create a spatial proteomic atlas of pancreatic cancer precursor evolution.
- To identify molecular events preceding histologic transformation.
- To explore the integration of spatial proteomics with histopathology and molecular pathology.
Main Methods:
- Utilized artificial intelligence (AI)-powered deep visual proteomics.
- Generated a high-resolution spatial proteomic map of pancreatic cancer precursors.
- Analyzed proteomic data in conjunction with histologic features.
Main Results:
- Identified significant metabolic and inflammatory reprogramming in early pancreatic cancer precursors.
- Demonstrated that these molecular changes precede overt histologic transformation.
- Revealed a spatial proteomic landscape of precursor evolution.
Conclusions:
- Spatial proteomics and multiomics can bridge histopathology and molecular pathology.
- Early metabolic and inflammatory reprogramming are key events in pancreatic cancer development.
- This approach holds potential for advancing precision oncology and early detection strategies.
