Abstract
Lung adenocarcinoma (LUAD) constitutes a major cause of cancer-related fatalities worldwide. Early identification of malignant pulmonary nodules constitutes the most effective approach to reducing the mortality of LUAD. Despite the wide application of low-dose computed tomography (LDCT) in the early screening of LUAD, the identification of malignant pulmonary nodules by it remains a challenge. In this study, CEACAM6 (also called CD66c) as a potential biomarker is investigated for differentiating malignant lung nodules. Then, the CEACAM6-targeting monoclonal antibody (mAb, tinurilimab) is radiolabeled with (89)Zr and (131)I for theranostic applications. In terms of diagnosis, machine learning confirms CEACAM6 as a specific extracellular marker for discrimination between LUAD and benign nodules. The (89)Zr-labeled mAb is highly specific uptake in CEACAM6-positive LUAD via positron emission tomography (PET) imaging, and its ability to distinguish in malignant pulmonary nodules are significantly higher than that of (18)F Fluorodeoxyglucose (FDG) by positron emission tomography/magnetic resonance (PET/MR) imaging. While the (131)I-labeled mAb serving as the therapeutic aspect has significantly suppressed tumor growth after a single treatment. These results proves that (89)Zr/(131)I-labeled tinurilimab facilitates the differential capacity of malignant pulmonary nodules and radioimmunotherapy of LUAD in preclinical models. Further clinical evaluation and translation of this CEACAM6-targeted theranostics may be significant help in diagnosis and treatment of LUAD.