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We applied Deep Visual Proteomics (DVP)\u2014integrating computational pathology, laser microdissection, and mass spectrometry (MS)\u2014to 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 \u223c100 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Significance:<\/jats:title>\n                    <jats:p>Artificial intelligence (AI)\u2013guided DVP represents the first in-depth assessment of the proteomic landscapes observed during the multistep progression of pancreatic adenocarcinoma, including histologically normal ducts, ADM, and LG- and HG-PanIN lesions. These data represent a unique resource of candidate biomarkers and interception targets against this lethal disease.<\/jats:p>\n                    <jats:p>See related commentary by Yang and Fan, p. 1255<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1158\/2159-8290.cd-25-1119","type":"journal-article","created":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T20:02:01Z","timestamp":1776801721000},"page":"1323-1340","update-policy":"https:\/\/doi.org\/10.1158\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["AI-Powered Deep Visual Proteomics Reveals Critical Molecular Transitions in Pancreatic Cancer Precursors"],"prefix":"10.1158","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2309-7875","authenticated-orcid":false,"given":"Jimin","family":"Min","sequence":"first","affiliation":[{"name":"1Laura and Isaac Perlmutter Cancer Center, Department of Medicine, New York University Grossman School of Medicine, NYU Langone Health, New York, 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