ADC Target Profiling in NSCLC: Generalizable AI Separates TROP-2 and cMET Phenotypes.

doi:10.1158/1078-0432.CCR-25-4513

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Article

ADC Target Profiling in NSCLC: Generalizable AI Separates TROP-2 and cMET Phenotypes.

Clinical cancer research : an official journal of the American Association for Cancer Research - 1 Jul 2026

Anders Philipp, Sextro Marvin, Lingelbach Katja, Standvoss Kai, Pandhe Suhas, Ghosh Sandip, Böhm Cornelius, Tietz Stephan, Krupar Rosemarie, Tharun Lars, Eich Marie-Lisa, Ribbat-Idel Julika, Ramberger Evelyn, Liang Xizi, Aumiller Verena, Merkelbach-Bruse Sabine, Quaas Alexander, Frost Nikolaj, Schlachtenberger Georg, Heldwein Matthias, Keilholz Ulrich, Hekmat Khosro, Rückert Jens-Carsten, Büttner Reinhard, Grohe Christian, Horst David, Alber Maximilian, Ruff Lukas, Klauschen Frederick, Dernbach Gabriel, Seegerer Philipp, Schallenberg Simon

Abstract excerpt

PURPOSE: Antibody-drug conjugates (ADC) targeting trophoblast cell surface antigen 2 (TROP-2) and cMET are entering clinical trials in non-small cell lung cancer (NSCLC). Their translation depends on reliable biomarker assessment, a task still dominated by subjective visual scoring and inconsistent reproducibility. EXPERIMENTAL DESIGN: We built a modular Artificial Intelligence (AI) pipeline that detects cells,...

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PMID: 41945491
DOI: 10.1158/1078-0432.CCR-25-4513
PMCID: PMC13325400

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