Abstract
Early diagnosis of lung adenocarcinoma (LUAD) is crucial. The National Lung Screening Trial showed a 20% reduction in lung cancer mortality in high risk individuals using low-dose helical computed tomography (CT). CT is highly sensitive for detecting lung nodules, but is limited by low specificity, especially for LUAD. On CT, LUAD may appear as solid or subsolid nodules. Most subsolid nodules are not cancer, and many will remain stable or resolve; however, subsolid lesions can represent premalignancy or adenocarcinoma in situ. These lesions in the early spectrum of LUAD may persist for months to years before transforming into invasive disease. As a result, current standard of care is to follow these patients with CT imaging to monitor these indeterminate lesions for radiologic signs of malignant progression. The identification of novel biomarkers to predict the malignant potential of these nodules at their initial identification is of paramount importance. We have recently discovered that premalignant ad early invasive lesions of the LUAD spectrum rely on sodium-glucose transporter 2 (SGLT2) for glucose uptake, whereas advanced carcinomas up-regulate transporters of the GLUT family. This is consistent with the observation that positron emission tomography (PET) with 2-[18F] fluorodeoxyglucose (FDG), which detects GLUT but not SGLT activity, is a standard tool for staging advanced disease, but has low sensitivity for early-stage LUAD. We measured SGLT2 activity in vivo with the PET tracer methyl-4-[18F] fluorodeoxyglucose (Me4FDG). Me4FDG detects early-stage, FDG-negative LUAD in mouse models and in patients. Importantly, Me4FDG uptake correlates with tumor growth rate in patient-derived LUAD xenografts (fig. 1). Targeting SGLT2 with FDA-approved inhibitors significantly reduces tumor growth and prolongs survival in genetic and patient-derived murine models, confirming an important role of SGLT2 in early-stage LUAD. SGLT2 is a promising biomarker not only to diagnose early-stage tumors by PET imaging, but also to predict response to SGLT2 inhibitors.
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