Evidence map›Paper›PMID 41945491›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2026

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

Philipp Anders, Marvin Sextro, Katja Lingelbach, Kai Standvoss, Suhas Pandhe, Sandip Ghosh, Cornelius Böhm, Stephan Tietz, Rosemarie Krupar, Lars Tharun and 22 more

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Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

32 authors.

Philipp Anders *Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.ORCID 0000-0001-6036-9342
Marvin Sextro *Aignostics GmbH, Berlin, Germany.ORCID 0000-0002-1792-2699
Katja LingelbachAignostics GmbH, Berlin, Germany.ORCID 0009-0005-2843-4198
Kai StandvossAignostics GmbH, Berlin, Germany.ORCID 0000-0002-5739-6726
Suhas PandheAignostics GmbH, Berlin, Germany.ORCID 0009-0008-1169-8623
Sandip GhoshAignostics GmbH, Berlin, Germany.ORCID 0009-0008-7342-1064
Cornelius BöhmAignostics GmbH, Berlin, Germany.ORCID 0009-0007-3754-4182
Stephan TietzAignostics GmbH, Berlin, Germany.ORCID 0009-0001-5069-3648
Rosemarie KruparAignostics GmbH, Berlin, Germany.ORCID 0009-0007-8119-9419
Lars TharunInstitute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.ORCID 0000-0001-7375-0775
Marie-Lisa EichInstitute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.ORCID 0000-0002-8601-4598
Julika Ribbat-IdelAignostics GmbH, Berlin, Germany.ORCID 0000-0003-1262-6572
Evelyn RambergerAignostics GmbH, Berlin, Germany.ORCID 0000-0003-2760-2696
Xizi LiangInstitute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.ORCID 0000-0001-9690-5397
Verena AumillerAignostics GmbH, Berlin, Germany.ORCID 0000-0003-2819-7557
Sabine Merkelbach-BruseInstitute of Pathology, Medical Faculty, University Hospital Cologne, Cologne, Germany.ORCID 0000-0002-0312-5760
Alexander QuaasInstitute of Pathology, Medical Faculty, University Hospital Cologne, Cologne, Germany.ORCID 0000-0002-3537-6011
Nikolaj FrostDepartment of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.ORCID 0000-0001-7452-7129
Georg SchlachtenbergerDepartment of General, Visceral, Oncological and Thoracic Surgery, University of Cologne, Cologne, Germany.ORCID 0000-0001-7118-8432
Matthias HeldweinDepartment of General, Visceral, Oncological and Thoracic Surgery, University of Cologne, Cologne, Germany.ORCID 0000-0002-2084-795X
Ulrich KeilholzCharité Comprehensive Cancer Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.ORCID 0000-0001-6773-9406
Khosro HekmatDepartment of General, Visceral, Oncological and Thoracic Surgery, University of Cologne, Cologne, Germany.ORCID 0009-0007-6888-4083
Jens-Carsten RückertDepartment of General, Visceral, Vascular and Thoracic Surgery, Charité - Universitätsmedizin Berlin, Berlin, Germany.ORCID 0000-0002-3940-4630
Reinhard BüttnerInstitute of Pathology, Medical Faculty, University Hospital Cologne, Cologne, Germany.ORCID 0000-0001-8806-4786
Christian GroheKlinik für Pneumologie, Evangelische Lungenklinik, Berlin, Germany.ORCID 0000-0003-2724-7647
David HorstInstitute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.ORCID 0000-0003-4755-5743
Maximilian AlberInstitute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.ORCID 0009-0006-2162-6477
Lukas RuffAignostics GmbH, Berlin, Germany.ORCID 0000-0002-9707-297X
Frederick KlauschenInstitute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.ORCID 0000-0002-9131-2389
Gabriel Dernbach *Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.ORCID 0000-0002-0356-6582
Philipp Seegerer *Aignostics GmbH, Berlin, Germany.ORCID 0000-0002-4707-7991
Simon Schallenberg *Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.ORCID 0000-0002-7897-7116

Funding

Berlin's development bank 10191964Bundesministerium für Forschung, Technologie und Raumfahrt (BMBF) 13GW0645BBundesministerium für Forschung, Technologie und Raumfahrt (BMBF) 16LW0239K
6 · The paper itself

Abstract

purposeAntibody-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

designWe built a modular Artificial Intelligence (AI) pipeline that detects cells, classifies carcinoma cells, and quantifies membranous and cytoplasmic expression. A membranous scorer trained on TROP-2 was applied zero-shot to cMET, human epidermal growth factor receptor 2 (HER2), and PD-L1. For TROP-2, cMET, and HER2, expression was quantified using the H-score, defined as (1× % weakly positive cells) + (2× % moderately positive cells) + (3× % strongly positive cells), with negative cells excluded (range, 0-300), and categorized as negative (0-50), weakly positive (50-100), moderately positive (100-200), or strongly positive (200-300). PD-L1 expression was assessed using both the H-score and the tumor proportion score (TPS), defined as the percentage of viable tumor cells showing membranous PD-L1 staining relative to all viable tumor cells, multiplied by 100. The analysis covered 1,142 resected NSCLCs, integrating expression maps with clinicopathologic, molecular, and tumor microenvironment (TME) features.

resultsThe AI scorer recapitulated pathologist annotations with near-perfect correlation [Pearsons's correlation (r) = 0.98-0.99, Spearman's rho (ρ) = 97-98, Kendall's tau (τ) = 0.88-0.89, Lin's concordance correlation coefficient (CCC) = 0.97-0.98] for TROP-2 and generalized to other markers [cMET r = 0.99, ρ = 0.96, τ = 0.91, CCC = 0.96; HER2 r = 0.93, ρ = 0.72, τ = 0.60, CCC = 0.92; and PD-L1 (TPS) r = 0.85, ρ = 0.84, τ = 0.68, CCC = 0.82/(H-score) r = 0.87, ρ = 0.86, τ = 0.70, CCC = 0.85]. Its agreement with six pathologists matched interobserver variability (0.86-0.96). Expression maps revealed contrasting spatial and cellular patterns: TROP-2 dominated lung squamous cell carcinoma [LUSC; mean H-Scores 141.3/103.2 vs. 74.5/45.7 in lung adenocarcinoma (LUAD) for membrane/cytoplasm] and marked immune-deserted tumors. cMET prevailed in LUAD (mean 50.4 vs. 20.6 in LUSC), colocalized with fibroblast-rich, immune-active TME, and KRAS mutations.

conclusionsFoundation model-based scoring produces expert-level, scalable biomarker quantification. The resulting TME phenotypes-TROP-2-high immune-deserted versus cMET-high, immune-active-reveal therapeutic implications for combining ADCs with immunotherapies or kinase inhibitors.

Indexed as

Antigens, NeoplasmArtificial IntelligenceCarcinoma, Non-Small-Cell LungCell Adhesion MoleculesImmunoconjugatesLung NeoplasmsB7-H1 AntigenBiomarkers, TumorErb-b2 Receptor Tyrosine KinasesFemaleHumansPhenotypeAntigens, NeoplasmB7-H1 AntigenBiomarkers, TumorCell Adhesion MoleculesERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesImmunoconjugatesTACSTD2 protein, human

Identifiers

PMID41945491
PMCPMC13325400

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