biostudies-literatureUnknown64Bar J<h4>Background and purpose</h4>c-Met (also known as MET) protein is encoded by the MET proto-oncogene. In non-small cell lung cancer (NSCLC), c-Met protein overexpression (OE) drives tumorigenesis and is a therapeutic target, given recent US Food and Drug Administration approval of telisotuzumab vedotin-tllv. This retrospective analysis of tumor samples and clinical data from real-world patients with non-squamous NSCLC characterized the prevalence of c-Met protein OE, its association with messenger ribonucleic acid (mRNA) expression, MET gene amplification, programmed-death ligand 1 (PD-L1) expression, and its impact on prognosis.<h4>Patients and methods</h4>A patient cohort was selected for manual abstraction of clinical data from electronic health records. Patients were selected based onActa oncologica (Stockholm, Sweden)https://www.ebi.ac.uk/biostudies/studies/S-EPMC12640106biostudies-literaturePrevalence, molecular characterization, and prognosis of c-Met protein overexpression in a real-world cohort of patients with non-squamous non-small cell lung cancer.PMC12640106Ratajczak CBaijal SJiang FZhao WCai MHChoi YCLiede AAnsell PJVasilopoulos ABar JRoberts-Rapp LCamidge DRLu SSimmons AfalsePrevalence, molecular characterization, and prognosis of c-Met protein overexpression in a real-world cohort of patients with non-squamous non-small cell lung cancer.<h4>Background and purpose</h4>c-Met (also known as MET) protein is encoded by the MET proto-oncogene. In non-small cell lung cancer (NSCLC), c-Met protein overexpression (OE) drives tumorigenesis and is a therapeutic target, given recent US Food and Drug Administration approval of telisotuzumab vedotin-tllv. This retrospective analysis of tumor samples and clinical data from real-world patients with non-squamous NSCLC characterized the prevalence of c-Met protein OE, its association with messenger ribonucleic acid (mRNA) expression, MET gene amplification, programmed-death ligand 1 (PD-L1) expression, and its impact on prognosis.<h4>Patients and methods</h4>A patient cohort was selected for manual abstraction of clinical data from electronic health records. Patients were selected based on2025-01-01T00:00:00Z2025 Nov2026-06-05T17:31:58.102Z2026-06-05T03:07:38.038ZS-EPMC126401064125499610.2340/1651-226X.2025.44344