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Targeted PET imaging strategy to differentiate malignant from inflamed lymph nodes in diffuse large B-cell lymphoma

Significance Diffuse large B-cell lymphoma (DLBCL) is the most common adult lymphoma, accounting for 37% of all non-Hodgkin lymphoma cases in the United States. Despite an approximate 50% cure rate, refractory or relapsed cases have a poor prognosis and require timely medical interventions. Therefore, accurate diagnostic methods play a pivotal role in managing DLBCL. 18F- fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) imaging, the current standard imaging modality for diagnosing DLBCL, often fails to differentiate inflamed from malignant lymph nodes in patients with DLBCL. To address this urgent medical need, we have developed a targeted PET imaging method that accurately distinguishes malignancy from inflammation in the lymph nodes. Our targeted PET imaging approach could play an essential role in the clinical development of therapies that induce significant inflammation in DLBCL. Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma in adults. DLBCL exhibits highly aggressive and systemic progression into multiple tissues in patients, particularly in lymph nodes. Whole-body 18F-fluodeoxyglucose positron emission tomography ([18F]FDG-PET) imaging has an essential role in diagnosing DLBCL in the clinic; however, [18F]FDG-PET often faces difficulty in differentiating malignant tissues from certain nonmalignant tissues with high glucose uptake. We have developed a PET imaging strategy for DLBCL that targets poly[ADP ribose] polymerase 1 (PARP1), the expression of which has been found to be much higher in DLBCL than in healthy tissues. In a syngeneic DLBCL mouse model, this PARP1-targeted PET imaging approach allowed us to discriminate between malignant and inflamed lymph nodes, whereas [18F]FDG-PET failed to do so. Our PARP1-targeted PET imaging approach may be an attractive addition to the current PET imaging strategy to differentiate inflammation from malignancy in DLBCL.