AI-Powered Deep Visual Proteomics Reveals Critical Molecular Transitions in Pancreatic Cancer Precursors
A partir de l'analyse par protéomique visuelle profonde de différentes régions de pancréas issus de donneurs et de patients atteints d'un adénocarcinome canalaire du pancréas, cette étude met en évidence, dans les cellules précancéreuses, des transitions moléculaires critiques pouvant offrir des opportunités pour la détection précoce de la maladie
Pancreatic ductal adenocarcinoma (PDAC) evolves through precursors, yet the protein programs governing early progression remain poorly defined. We applied Deep Visual Proteomics (DVP)—integrating computational pathology, laser microdissection, and mass spectrometry (MS)—to profile normal ducts, acinar-to-ductal metaplasia (ADM), low-grade (LG) and high-grade (HG) pancreatic intraepithelial neoplasia (PanIN), and invasive carcinoma from organ donors and patients with PDAC. Quantifying 9,181 proteins from
∼
100 cells per region, we uncovered a molecular field effect in histologically normal ducts and proteomic divergence of LG-PanINs by cancer context. We identified four stage-associated molecular programs. Stress adaptation and immune engagement emerged early in cancer-associated normal ducts. Metabolic reprogramming initiated in normal ducts and intensified across PanIN progression. Mitochondrial remodeling became prominent in HG-PanINs before invasion. MS detected KRAS hotspot mutant peptides within incidental precursor lesions from cancer-free individuals. These findings demonstrate that molecular reprogramming precedes histologic transformation, creating opportunities for earlier detection of lethal cancer.
Cancer Discovery , article en libre accès, 2026