ADC target profiling in NSCLC: Generalizable AI separates TROP-2 and cMET phenotypes

This dataset accompanies the paper "ADC target profiling in NSCLC: Generalizable AI separates TROP-2 and cMET phenotypes" and provides comprehensive clinicopathological, molecular, and expression data for a cohort of resected non-small cell lung cancer (NSCLC) patients. Contents: Patient Data Table (cohort_data.csv) QC flags (tumor content, rejection criteria for cMET/TROP-2) Clinical characteristics (age, sex, smoking status, ECOG) Tumor characteristics (histological subtype, grade, diameter) Pathological staging (pTNM, UICC 8th edition) Molecular pathology (mutation status for EGFR, KRAS, ALK, ROS1, TP53, and others) Survival outcomes (OS) AI-derived H-scores for: TROP-2 (membranous) TROP-2 (cytoplasmic) cMET (membranous) AI-derived cell phenotype counts per patient TMA Spot Images Immunohistochemistry-stained tissue microarray (TMA) spots for TROP-2 and cMET Linked via case_uuid to the patient data table