Proteomics

Dataset Information

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AI-powered Deep Visual Proteomics unmasks critical molecular transitions in pancreatic cancer precursors


ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) evolves through precursors, yet the protein programs that govern early progression remain poorly defined. We applied Deep Visual Proteomics - computational pathology, laser microdissection, and mass spectrometry (MS) - to profile normal ducts, acinar-to-ductal metaplasia (ADM), low- and high-grade 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 showed that low-grade PanINs diverge by cancer context. Four programs - stress adaptation, immune engagement, metabolic reprogramming, and mitochondrial remodeling - emerged early and intensified with progression. High-grade PanINs exhibited distinct metabolic signatures preceding invasion. Notably, mass spectrometry detected KRAS hotspot mutant peptides directly within PanINs and ADM, providing protein-level evidence of oncogenic alteration in precursor lesions. These findings demonstrate that molecular reprogramming precedes histological transformation, creating opportunities for earlier detection of this lethal cancer.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Malignant Cell, Pancreatic Ductal Adenocarcinoma Cell, Panin Cell, Epithelium Of Pancreatic Duct, Pancreatic Duct

DISEASE(S): Pancreatic Ductal Adenocarcinoma

SUBMITTER: Lisa Schweizer  

LAB HEAD: Andreas Mund

PROVIDER: PXD072559 | Pride | 2026-03-31

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
DIANN_SEARCH_RESULTS.zip Other
DIANN_SEARCH_RESULTS_KRAS.zip Other
MS_mzML_FILES.zip Other
Reference_File.csv Csv
checksum.txt Txt
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